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Phenomenological Research
and Analysis
Authors:
Edwin C. May, Ph.D., Wanda L. W. Luke, and Nevin D. Lantz, Ph.D.
3 February 1993
SAIC
Science Applications International Corporation
An Employee-Owned Company
Presented to:
U. S. Government
Contract MDA908-91-C-0037
(Client Private)
Submitted by:
Science Applications International Corporation
Cognitive Sciences Laboratory
1010 El Camino Real, Suite 330, P.O. Box 1412, Menlo Park, CA 94025 · (415) 325-8292
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TABLE OF CONTENTS
LIST OF FIGURES
iii
LIST OF TABLES
iv
I
OBJECTIVE
1
II
BACKGROUND
3
1.
Historical Perspective
3
2.
Current Program
4
III
EXECUTIVE SUMMARY
5
1.
Target Dependencies
5
2.
Enhancing AC with Binary Targets
6
3.
AC in Lucid Dreams
7
4.
Magnetoencephalograph
8
5.
Enhancing AC of Binary Targets
9
IV
TARGET DEPENDENCIES
11
1.
Objective
11
2.
Introduction
11
3.
Approach
13
4.
Hypotheses
25
5.
Results and Discussion
25
V
ENHANCING DETECTION OF AC OF BINARY TARGETS
31
1.
Objective
31
2.
Background
31
3.
Approach
32
4.
Results and Discussion
36
VI
MAGNETOENCEPHALOGRAPH
1.
Introduction
39
2.
Approach
40
3.
Results
46
4.
Discussion
46
5.
Suggested Research
47
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VII
ENHANCING DETECTION OF AC WITH BINARY ENCODING
49
1.
Objective
49
2.
Background
49
3.
Approach
49
4.
Results
52
5.
Discussions and Conclusions
54
VIII
SUBCONTRACTS
57
1.
Edinburgh University .
57
2.
Psychophysical Research Laboratories (PRL)
57
3.
The Lucidity Institute
58
IX
OTHER ACTIVITY
61
1.
Correlations between AC and Geomagnetic Activity
61
2.
Assessment of Theoretical Constructs
62
3.
Anomalous Perturbation
63
4.
Fuzzy Set Analysis
63
5.
Empirical Training Overview
65
6.
A Potential New Training Method
68
X
GLOSSARY
71
REFERENCES
73
APPENDIX A: Target Elements for the Fuzzy Set Representation of AC Targets
77
APPENDIX B: The Ganzfeld Novice: Four Predictors of Initial ESP Performance
79
APPENDIX C: Impact of the Sender in Ganzfeld Communication:
Meta-Analysis and Power Estimates
81
APPENDIX D: Effects of the Sender on Anomalous Communication in the Ganzfeld
83
APPENDIX E: A Preliminary Study of Anomalous Perception During Lucid Dreaming
85
APPENDIX F: Possible Effects of Geomagnetic Fluctuations on the
Timing of Epileptic Seizures
87
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LIST OF FIGURES
1. City with a Mosque
14
2. Green Intensity Distribution for the City Target (Macro1-pixel 3,3)
15
3.
City with Mosque (|AS | = 1.88 bits)
15
4. Pacific Islands (|AS| = 1.45 bits)
16
5. Zener Target Cards (Average |AS | = 0.15 bits)
16
6. Cluster Diagram for Dynamic Targets
17
7.
Cluster Diagram for Static Targets
18
8.
Target and Response with a post hoc Rating of 7
22
9. Target and Response with a post hoc Rating of 4
23
10. Target and Response with a post hoc Rating of 1
24
11.
Correlation of Post Hoc Score with Static Target AS
27
12.
Correlation of Post Hoc Score with Dynamic Target AS
28
13. Two-tailed SA Decision Graph
33
14.
Operating Characteristic Function-1-Tail
34
15. Operating Characteristic Function-2-Tail
35
16. Sequence of Events for Stimuli Generation
41
17. Phase Calculation for a Single Stimulus
43
18.
A Two-by-Five, Error Correcting Block Code
52
19. Correlation: Levels of Visual Complexity with Post Hoc Ratings and Blind Ranking
for Post Hoc Scores Greater than Three (i.e., evidence for AC).
64
20.
Correlation: Levels of Visual Complexity with Post Hoc Ratings and Blind Rankings
65
for all Post Hoc Scores
21. Experimental Paradigm for Training
70
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LIST OF TABLES
1.
Effect Size as a Function of Target Type
12
2.
Experiment Conditions
19
3.
0-7 Point post hoc Assessment Scale
21
4.
Effect Sizes
25
5.
ANOVA Results
26
6.
Receiver 7
36
7.
Receiver 83
37
8.
Receiver 531
37
9.
Hypothesis Testing for Each Receiver
46
10.
Attributes for Ten Target Packs
50
11.
Statistics for the Sum-of-Ranks
53
12.
Statistics for First Place Ranks
53
13.
Receiver First Place Ranks
54
14.
Analyst First Place Ranks
54
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I. OBJECTIVE
The objective of this document is to provide a technical final report on tasks 6.2, "Basic Research," 6.3,
"Applied Research," and 6.4, as listed in the 1991 Statement of Work. This report covers the time peri-
od from 4 February 1991 to 30 June 1992, and includes all subtasks.
* This report constitutes the deliverable DI-MISC-80508 under contract number MIDA908-91-C-0037.
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Il. BACKGROUND
With regard to this final report, anomalous mental phenomena (AMP) can be divided into two
broad categories:"
· Anomalous Cognition (AC): A form of information transfer in which all known sensorial stimuli are
absent.
· Anomalous Perturbation (AP): A form of interaction with matter in which all known physical mecha-
nisms are absent.
For the purpose of this document, we define research that is primarily directed at understanding the
nature of AMP (e.g., signal transmission, neurophysiology, etc.) as basic. Research that is primarily
directed at improving the quality of output (e.g., analysis techniques, choice of target material, etc.) as
applied. Basic and applied research domains are broad and are highly interactive and mutually support-
ive. Understanding the technical details of AC phenomena, for example, will improve its application
potential, and likewise, being sensitive to the restrictions of a real-world problem may provide insight
into underlying mechanisms.
1. Historical Perspective
Serious government research of AMP began in 1973 when a modest effort began at SRI International in
Menlo Park, California, to determine if AMP could be verified and to assess the degree to which AMP
could be applied in practical situations.
In fiscal year 1986, SRI International conducted the first coordinated, long-term examination of AC
and AP phenomena. This program had three major objectives:
. Provide incontrovertible evidence for the existence of AC and AP.
. Determine the physiological and physical basis for AC and AP.
. Determine the degree to which AC data could be applied in practical situations.
The results and conclusions from this program were as follows:
. The first objective was partially met. An information transfer anomaly (i.e., AC) exists that could not
be explained by inappropriate protocols, incorrect analyses, or fraud; however, there was insufficient
evidence to conclude if AP existed.
· Significant progress was made in meeting the second objective. For example,
(1) The central nervous system (i.e., the brain) of individuals with known AC ability appeared to re-
spond to isolated AC stimuli.
* A definition of terms may be found in the Glossary in Section X on page 71.
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(2) Two physical models were constructed. One, called Decision Augmentation Theory, suggests a
possible physical transfer mechanism for AC data. The other is a speculative physical model for
the type of information that is sensed by AC.
Under the same research program, different physical systems were examined for their susceptibility to
putative AP effects. They included single-cell algae, single alpha particles, and electronic devices such
as random number generators and piezoelectric strain gauges. However, in these carefully controlled
experiments, some with experienced AP subjects, no evidence of AP was observed.
2. Current Program
Beginning in February 1991, the sponsor initiated a comprehensive, 18-month investigation of AMP at
Science Applications International Corporation. The primary thrusts of this effort were to:
· Prepare a comprehensive, integrated, 5-year research plan.
. Conduct basic and applied research of AMP.
This final report provides a comprehensive technical review of this program and suggests possible paths
of inquiry for the future. Major sections within this report are as follows:
· Primary experiments carried out under this program.
· Theoretical and analytical problems.
. Results from three subcontractors and their final reports.
In the following section, we provide an executive summary of this 18-month effort. The executive sum-
mary is designed for the non-technical reader; however, the technical and statistical details can be found
in the body of the report, which begins with Section IV on page 11. References to the statement of work
are given at the beginning of each section and elsewhere, where appropriate.
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III. EXECUTIVE SUMMARY
During the course of this 18-month contract, we conducted five experiments that were designed to ad-
dress specific issues of applied and basic research of AMP. Additionally, we conducted a variety of other
investigations that did not require further experimentation. As an example of the latter, we applied
fuzzy set theory to the data from one of the experiments. In this section, we provide a non-technical
summary of the five experiments. Details on all tasks may be found in the body of the report.
A well-designed experiment provides valuable information regardless of the particular outcome. In our
experimental effort during this contract, three studies produced positive outcomes and two did not. All,
however, provided useful guidelines for a follow-on effort.
1. Target Dependencies
1.1 Abstract
The purpose of this experiment was to determine if the quality of AC depends upon an intrinsic target
property, which is called the change of entropy (i.e., the amount of information contained in visual tar-
get material). This was examined for two different target types, photographs and short video clips. A
second objective was to determine if the quality of AC depends upon a sender (i.e., a person who is
isolated from the receiver but who is focusing upon the target material).
The experimental results indicate that the quality of AC does not require a sender to know about, or to
focus his or her attention on, the target. Most importantly, we found a strong correlation between the
quality of the AC and the change of entropy in a target: That is, the more information determined by
information theory contained in the target, the better the AC. Should this result replicate in other ex-
periments, it may be the first indication of an independent physical variable that is fundamental to AC.
If so, this information can be used to vastly improve many other types of AC experiments.
1.2 Approach
Each of five receivers, who had previously demonstrated an AC ability, contributed 40 trials each. All
receivers worked alone from their homes and, at a prearranged time, conducted an AC trial for a target
that was located no less than 500 km away. The target was either a photograph from the National
Geographic magazine or a short clip from a video movie. For half of the trials, the experimenter acted as
a sender, and for all trials, the receivers were unaware of the target type or if there was a sender. After
receiving the responses by facsimile machine, the experimenter mailed each receiver the target as feed-
back. Standard statistical procedures were use to determine whether there were differences in AC
quality among these various conditions.
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1.3 Results
Three of the five receivers independently demonstrated significant evidence for AC. AC of photographs
was statically significant while AC of videos was not, but the difference between them was not large enough
to demonstrate a meaningful preference for the photographs. Using the combined data for all receivers, we
found a significant correlation, as measured by a subjective post hoc technique, between the change of target
entropy (i.e., its information content) and the quality of the response.
. .. ....
We did not observe statistical evidence of AC when the targets were video clips, unlike previous re-
search by Honorton. We speculate that the receivers, who had rarely been exposed to this type of target,
were unable to discriminate AC from their internal, non-AC experiences. We expand this point in the
body of the report.
1.4 Conclusions
A sender is not an intrinsic requirement of AC; however, a sender might contribute to a conducive envi-
ronment for AC. In addition, it is unknown whether a sender facilitates the reception of specific target
elements. We are currently examining this last point with one of our subcontractors.
The total change of target entropy may be fundamental to the functioning of AC. This may shed impor-
tant light on the question, "What is being sensed by AC?" A number of replications are required, how-
ever, before we can be certain.
2. Enhancing Detection of AC of Binary Targets
2.1 Abstract
It is often thought that targets in AC experiments are much too complicated. Frequently they consist of
photographs of complex scenes such as a city near a mountain. This complexity makes it difficult to
quantitatively analyze the information contained in the target and the response. To eliminate this prob-
lem, researchers can use binary targets (e.g., red/black cards, 0/1), which are completely defined and can
be analyzed by simple statistics. Earlier experiments have used sophisticated mathematical procedures
to enhance the detection of AC of binary targets. The purpose of this experiment was to replicate these
earlier experiments.
In this experiment, one individual who had demonstrated an ability to use AC successfully when the
targets are single binary bits, continued to show his ability. In this case, however, we applied statistical
enhancement techniques from information theory to improve the scoring rate. We need to identify a
more robust statistical technique to improve the overall efficiency because the receiver was required to
"guess" over 21,000 times to reach 100 definite decisions about the binary targets. Of the 100 decisions,
he or she was correct 76 times.
2.2 Approach
Each of three receivers contributed 100 AC trials in a computer-driven, binary AC experiment. One
receiver had demonstrated consistent AC ability in similar experiments, whereas the other two receiv-
ers were inexperienced in binary target AC. It is beyond the scope of this summary to describe the math-
ematical technique since it may be found in detail in the body of the report. Simply stated, a sophisti-
cated procedure called sequential analysis was used to provide many redundant responses to a single
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binary number target (i.e., one or zero). Sequential analysis is particularly sensitive to whether there is
a "burst" of AC and can also determine to within statistical limits if no AC is present.
2.3 Results
The experienced receiver again produced significant evidence of AC of binary targets. That receiver's
hit rate of 51.6% before the application of sequential analysis was improved to 76% as a result of the
analysis. The other two receivers scored at chance expectation.
2.4 Conclusions
We confirmed earlier results that it is possible to enhance detection of AC with binary targets using
sequential analysis. A major difficulty, however, is that the receivers had to register a guess (i.e. by
pressing a computer mouse button) approximately 200 times for each sequential analysis trial. Thus the
technique, while capable of enhancing the detection of AC of binary targets, is particularly inefficient
due to excessive time expenditures.
3. AC in Lucid Dreams
3.1 Abstract
Throughout human experience, people have reported various types of AC in dreams, and laboratory
experiments in the 1970s confirmed that AC may occur in dreams. A lucid dream is defined as one in
which a dreamer becomes aware that she or he is dreaming. Extensive research has confirmed the exis-
tence of lucid dreaming, and that it is possible for the dreamer to signal the waking world about his or
her knowledge about the dream.
The purpose of this pilot study was to determine if AC could occur during lucid dreaming. We found
that AC can occur in lucid dreams. Because the dream-trials did not take place in the laboratory, there
was some difficulty in interpreting the results; however, it was clear that lucid dreams do not inhibit AC
functioning. Because of the success of this experiment, we will be repeating it in an appropriate sleep
laboratory.
3.2 Approach
This experiment was designed as a pilot effort. Seven receivers, three experienced in lucid dreaming and
four experienced as AC receivers, participated in the study. The four AC receivers were first trained in lucid
dreaming before the AC trials began. During each trial, a target was selected randomly from the established
pool of National Geographic magazine photographs and doubly sealed in two opaque envelopes. The
dreamer/receiver placed the envelope next to the bed and was instructed, when a dream became lucid, to
"open" the dream envelope (i.e., not the real envelope) while still dreaming, study its content, and report
the experience upon waking. The target was provided as feedback once the data had been presented to the
experimenter. Our standard rank-order analysis was performed to determine if AC occurred in the study.
Since the trials were conducted in each receiver's own bedroom rather than under laboratory conditions, it
was difficult to "induce" a lucid dream on demand. Thus, the total number of trials was small (i.e., 21).
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3.3 Results
Our analysis confirmed that robust AC occurred during the study; however, the number trials was insuf-
ficient to ascertain whether the lucid dream state improved AC functioning.
3.4 Conclusions
Because the size of the AC effect seen in this study is commensurate with that seen in other AC experi-
ments, we conclude that the lucid dream state, at least, does not hinder AC functioning. In the body of
the report we suggest a refined experiment to increase the number of lucid dream trials in order to de-
termine if lucid dreaming might enhance AC.
4. Magnetoencephalograph
4.1 Abstract
In this experiment, we attempted to replicate a study in which we found that slow brain-wave patterns
appeared to be affected by an isolated flashing light. We were unable to confirm that result; however,
important insights resulted from our effort. We did not attempt to show behavioral evidence of AC
while measuring the brain waves. That oversight prevented us from determining if the target system was
valid for AC. An analogy might be that it would be a mistake to use only a light stimulus in a study of the
brain's response to audio information. In addition, we found post hoc that in general the statistical na-
ture of brain waves might have fundamentally prevented us from correctly measuring the instantaneous
slow rhythms. We suggest that an appropriate follow-on experiment, which remedies these two over-
sights, be conducted, because the statistical evidence for AC in other experiments strongly suggests that
the central nervous system must be involved at some level.
4.2 Approach
Eight individuals were exposed to approximately 1,000 isolated light flashes while their brain activity
was being monitored by a magnetoencephalograph, an instrument that measures the magnetic fields
produced by active neurons in the brain. The receivers were chosen to participate in the study based on
their successful participation in other AC investigations. We searched for subtle changes in their brain
activity by measuring various parameters of their alpha rhythms immediately before and immediately
after each light flash. A large alpha rhythm usually indicates that the brain is not particularly attentive
to external events, moving the body, or thinking. More traditional central nervous system research has
shown that any of these activities can cause a change in the alpha rhythm; therefore, it seems reasonable
to expect that if AC is a genuine phenomenon, then it too should induce changes in the alpha rhythm.
To assure that any observed effects were not due to an artifact, an equivalent amount of data (i.e., con-
trol data) was collected without any receiver under the magneteoencephalograph.
4.3 Results
The earlier results could not be verified in this experiment. The mathematical analysis, which had been
used originally, did not reveal any unexpected changes in the subtle properties of the alpha rhythm. The
control data also showed no unexpected results.
We did, however, notice a difficulty in this analysis. Because brain waves are always present, there is
substantial activity that is considered to be noise (i.e., activity that is not directly related to reactions to
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stimuli). Our data contained substantial noise and, unfortunately, our analysis technique was so sensi-
tive to it that any brain response to the isolated flashing lights would not have been observed. Fortu-
nately, we have saved all the raw data from this experiment, so all that is required is to reanalyze the data
with improved techniques. We are currently engaged in that task.
4.4 Conclusion
Until this new analysis is complete, we are unable to determine whether the brain responds to isolated
stimuli. In the body of the report, we suggest that an improved protocol be implemented as part of the
continuing research effort.
5. Enhancing the Detection of AC with Binary Coding
5.1 Abstract
The literature reports many attempts at using various statistical approaches to enhance the detection of
AC. In this experiment, we used a standard technique from information theory (i.e., error correction
through redundancy coding). We were unable to demonstrate that this particular procedure was suc-
cessful. As a result of this experiment, we identified a number of improvements that might be applied in
new studies. For example, in our study, the statistical technique required special targets, which have not
been part of our usual collection. A replication will use a pool of targets that have been successfully used
in other experiments. We also learned that our statistical procedure was not sensitive to correct AC
responses that happened not to be part of the statistical procedure. We have identified a number of new
approaches that correct this problem.
5.2 Approach
Five receivers, who had previously demonstrated AC ability, contributed eight trials each. For each
trial, all receivers worked alone from their homes and, at a convenient time, conducted an AC trial for a
target that was located no less than 500 km away. The targets, which were photographs from the Nation-
al Geographic magazine, were chosen in accordance with specific design criteria and were available for
one week for each trial. To use error correcting coding, we identified a series of questions that per-
tained to the presence or absence of specified target elements. In this way, a target element, for exam-
ple water, could correspond to a single binary bit in the error correcting code. That is, if water were
present in the target, the value of one would be assigned to it, otherwise it would be assigned a value of
zero. We created ten different sets of five target elements and chose photographs that matched the
presence/absence criteria. The presence or absence of particular target elements was dictated by the
requirements of the 5-bit binary error correcting code that we used in this study. The principle behind
error correcting coding in an AC application is that a receiver could "miss" one of the target elements
but still arrive at the correct target. Error correction is a common technique found in the computer
industry and in deep space communications. We were adapting its use for AC experiments.
After a receiver had completed an AC trial, the response was sent by facsimile to an experimenter in our
laboratory in Menlo Park, CA. By return facsimile, the receiver was sent five questions that required yes/no
answers for the presence or absence of the target elements. Upon the receipt of the completed questionn-
aire, the experimenter sent the photograph back as feedback.
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Three separate analyses were performed on these data. We used blind rank-ordering of the target and
three decoys for each trial to determine if AC occurred during the experiment. In addition, an indepen-
dent analyst and the receiver separately answered the appropriate questions for each trial. The ana-
lyst's answers were compared with the receiver's answers after applying the error correcting code.
5.3 Results
We were unable to confirm the existence of AC in this experiment using the blind rank-order analysis.
While the receivers' answers to the questionnaires tended to be much more accurate than those provided by
the independent analyst, no answers were good enough to indicate AC using the error correcting coding.
5.4 Conclusions
As was the case in the target-dependencies experiment, we speculate that the receivers, who had rarely
been exposed to the type of targets that were used, were unable to discriminate the AC from their inter-
nal, non-AC experiences. We expand this point in the body of the report. In addition, we noticed that
the answer to a single question depended upon the correct perception of a single target element (i.e.,
water). This element might not be sensed, but others-not included in the five questions-might be
sensed. The method could not take into account these other responses. In the body of the report, we
suggest a new experiment that improves the target pool and connects the individual coding bits to
classes of elements, rather than single elements.
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IV. TARGET DEPENDENCIES
This section comprises the final report for SOW items 6.2.2.1 and 6.2.2.2.
1. Objective
There are two objectives of this pilot study:
(1) Explore the effects of target properties on AC quality.
(2) Determine the degree to which AC quality depends upon a sender.
2. Introduction
The field of parapsychology has been interested in improving the quality of responses to target material
since the 1930's, when J. B. Rhine first began systematic laboratory studies of extra sensory perception.
Since that time, much of the field's effort has been oriented toward psychological factors that may influ-
ence AC. In this section, we review the pertinent literature that categorizes targets that have been used
successfully in AC experiments.
At a recent conference, Delanoy reported on a survey of the literature for successful AC experiments.1
She categorized the target material according to perceptual, psychological, and physical characteristics.
Except for trends related to dynamic, multi-sensory targets, she was unable to observe systematic cor-
relations of AC quality with her target categories.
Watt examined the AC-target question from a psychological perspective.2 She concluded that the best
AC targets should be those that are psychologically meaningful, have emotional impact, and contain
human interest; those targets that have physical features that stand out from their backgrounds or con-
tain movement, novelty, and incongruity also should be good targets.
The difficulty with both the survey of the experimental literature and the psychologically oriented
theoretical approach is that understanding the sources of the variation in AC quality is problematical.
Using a vision analogy, energy sources of visual material are easily understood (i.e., photons); yet, the
percept of vision is not well understood. Psychological and possibly physiological factors influence what
we "see." In ACresearch, the same difficulty arises. Until we understand what factors influence the AC
percept, results of systematic studies of AC are difficult to interpret.
Yet, in a few cases, some progress has been realized. In 1990, Honorton et al. conducted a careful meta-
analysis of the experimental Ganzfeld literature.3 In Ganzfeld experiments, receivers are placed in a
state of mild sensory isolation and asked to describe their mental imagery. After each trial, the analysis
is performed by the receiver, who is asked to rank order four pre-defined targets, which include the
actual target and three decoys; the chance first-place rank hit rate is 0.25. In 355 trials collected from
241 different receivers, Honorton et al. found a hit rate of 0.31 (z = 3.89, p ≤5 x 10-5) for an effect
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size of 0.141. In addition, he found that AC quality was significantly enhanced when the targets were
video clips from popular movies (i.e., dynamic) as opposed to static photographs (i.e., effect sizes of
0.32 and 0.05, respectively). All trials were conducted with a sender.
In a carefully conducted meta-analysis, Honorton and Ferrari report significant hitting in forced-
choice, precognition experiments.4 They analyzed 53 years of experiments conducted by 62 different
investigators using a limited set of symbols (Zener cards) as target material. Fifty thousand receivers
contributed a total of approximately 2× 106 individual trials. The overall effect size was 0.020 corre-
sponding to a p-value of 6.3 x 10-25. Similarly, in an earlier review article, Honorton analyzed 7.5x 105
forced-choice Zener card trials that were collected from 1934 to 1939 and found a significant overall
effect size of 0.016+0.001.5
Puthoff and Targ published the results of 39 AC real-time trials where the targets were natural scenes in
the San Francisco Bay area.6 The effect size for the 39 trials was 1.15.
Table 1 summarizes these results for each target type:
Table 1.
Effect Size as a Function of Target Type
Target Type
Trials
Effect Size
Symbols (Real-Time)
7.5 × 105
0.016 ± 0.001
Symbols (Precognitive)
2.0 × 106
0.020 ± 0.001
Static Photographs
165
0.05 ± 0.08
Dynamic Photographs
190
0.32 ±0.07
Static Natural Scenes
39
1.15 ±0.16
"Significance may be computed as z = Effect Size / Error Shown.
The effect sizes shown in Table 1 are qualitatively monotonically related to target "complexity;" an ap-
propriate quantitative description for target type is currently unknown. Target "complexity," however,
was one of the experimentally observed and theoretically conceived attributes examined by Delanoy
and Watt, respectively.
A number of confounds exist in this database for the effect-size measures. For example, in all but the
Puthoff and Targ study (where targets were natural scenes), the receivers were unselected. That is, they
did not participate in the various experiments on the basis of their known ability as receivers. So, is the
large effect size for the Puthoff and Targ study because of the accomplished receivers, the natural-scene
targets, or some combination of both? While there are other exceptions, the preponderance of the data
was from unselected individuals. In many of the trials, a sender was concentrating on the target materi-
al, and as in most perception experiments, psychological factors and boredom contributed to the vari-
ance in the effect sizes.
In this pilot experiment, we applied one physical measure to static and dynamic photographs to quantify the
relationship between target type and AC quality. By careful selection of target content, we minimized the
psychological factors in perception. In addition, we minimized individual differences by conducting many
trials with each receiver and by only choosing receivers who had previously demonstrated excellent AC skill.
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Because the historical database included trials with and without senders, we explored the effects of a
sender on AC quality, as well.
3. Approach
3.1 Target-pool Selection
The static target material for this pilot study was a set of 50 National Geographic magazine photographs.
This set was divided into 10 sets of five photographs that were determined to be visually dissimilar by a
fuzzy set analysis.7 The dynamic target material was four sets of five 60 to 90 second clips from popular
video movies. These clips were selected because they had the following characteristics:
. Were thematically coherent.
· Contained obvious geometric elements (e.g., wings of aircraft).
. Were emotionally neutral in that they did not contain obvious arousing material.
The intent of these selection criteria was to control for cognitive surprise, to provide target elements
that are easily sketched, and to control for psychological factors such as perceptual defensiveness.
3.2 Target Preparation
The target variable that was considered in this experiment was the total change of Shannon entropy per
unit area, per unit time. We chose this quantity because it was qualitatively related to the "information"
contained in the target types shown in Table 1, and because it represented a potential physical variable
that is important in the detection of traditional sensory stimuli. In the case of image data, the entropy is
defined as:
NL-1
Sx= - 2 PM 1082(Pik), = 0 if PjŁ = 0,
where Pik is the probability of finding image intensity j of color k. In a standard, digitized, true color
image, each pixel (i.e., picture element) contains eight binary bits of red, green, and blue intensity, re-
spectively. That is, Nk is 256 (i.e., 28) for each k, k = r, g, b. The total change of the entropy in differential
form is given by:
ds = IVS.I . dr + |Sk dr.
(1)
That is, the total change of Shannon entropy is the change because of spatial variations in the static
targets added to the change resulting from frame-to-frame variations in the video targets.
We must specify the spatial and temporal resolution before we can compute the total change of entropy
for a real image. Henceforth, we drop the color index, k, and assume that all quantities are computed
for each color and summed.
3.2.1 Static Targets
To select the 50 static targets, 100 National Geographic magazine photographs were scanned at 100 dots per
inch (dpi) for eight bits of information of red, green, and blue intensity. At one centimeter spatial resolu-
tion, this scanning density provides 1,550 pixels for each 1-cm2 macro-pixel to compute the p.
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For a specified resolution, the target photograph was divided into an integral number of 1-cm2 macro-
pixels excluding a thin border, if necessary. The entropy for the (i,j) macro-pixel was computed as:
Sy =- = p,1080(p).
j=0
where p; was computed empirically from the pixels in the (i, j) macro-pixel only. For example, consider
the target photograph shown in Figure 1.
CPYRGHT
Figure 1. Chy with a Mosque
Figure 2 shows the probability density for the green intensity for macro-pixel (3,3), which is shown as a
white square in the upper left-hand corner of Figure 1." The probability density indicate that most of
the intensity in this patch is near zero value (i.e., no intensity of green in this case). In a similar fashion,
Sy is calculated for the entire scene.
* The original photograph was 8.5 x 11 inches, and we have standardized on one centimeter resolution.
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0.4
Probability Density
0.2
0.0
0
20
40
60
80
100
Intensity (j)
Figure 2. Green Intensity Distribution for the City Target (Macro-pixel 3,3)
We used a standard algorithm to compute the 2-dimensional spatial gradient of the entropy. Figure 3
shows contours of constant change of entropy (calculated from Equation 1) for the city target. The total
change per unit area is 1.88 bits/cm .*
- CPYRGHT
Figure 3. City with Mosque (JAS] = 1.88 bits)
The city target was chosen as an example because it was known (qualitatively) to be a "good" static
photograph for AC trials in earlier research. Figure 4 shows contours of constant change of entropy for
a photograph that was known not to be a "good" AC target.
* In this formalism, entropy is in units of bits and the maximum entropy is 24 bits.
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CPYRGHT
C
Figure 4. Pacific Islands (|4S ] = 1.45 bits)
For comparison, we show in Figure 5 the traditional Zener cards, which were used as targets in most of
the forced-choice experiments shown in Table 1.
F
C
Figure 5. Zener Target Cards (Average |AS] = 0.15 bits)
3.2.2 Dynamic Targets
The total change of entropy for the dynamic targets was calculated in much the same way. The video
targets were digitized at approximately one frame per second. The spatial term of Equation 1 was com-
puted exactly as it was for the static targets. The second term was computed from differences between
adjacent 1-second frames. Or,
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(2)
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251) ~ AS,(1) = |Sy(+ At) - Sy(1)
where At is one over the digitizing frame rate (i.e., one second). We can see immediately that the dy-
namic targets have a larger 4S than do the static ones because Equation 2 is zero for all static targets.
3.2.3 Cluster Analysis
Using Equations 1 and 2, we computed 4S for all the static and dynamic targets. These targets were
grouped, using standard cluster analysis, into relatively orthoginal clusters of relatively constant 4S. Fuzzy
set analysis and inspection were used to construct packets of five visually dissimilar targets from within each
cluster. Our interim report, which is dated 15 February 1992, details the cluster analysis.8 Figures 6 and 7
show the clusters from that report for the dynamic and static targets, respectively.
Difference of Averages (bits)
0.0
0.2
0.4
0.6
0.8
1.0
1
J
1.005 -
1.808 .
1.894
1.577
1.825
2L
2,354
2.201 -
1 2.248 -
0
2.248 -
1.970 -
2.007
2.058
2.041
1 2.032
3.033
2.794
2.904
3.583 .
3.312 -
For ease of reading, Figure 7 shows only those 50 static targets that were used to form the constant entropy
clusters, rather than the whole set of 100. We show the computed AS at the end of each cluster leaf.
3.3 Target Selection
For a specified target type (e.g., static photographs), a target pack was selected randomly and one target
of the five within that pack was also chosen randomly.
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Figure 6. Cluster Diagram for Dynamic Targets
At
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1.224
413
Figure 7. Cluster Diagram for Static Targets
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3.4 Receiver Selection
Each of five experienced receivers, who have produced significant AC effect sizes in previous investigations,
contributed 40 AC trials (i.e., ten trials under each of the conditions shown in Table 2). Two of the receivers
resided in California while the other three resided in Kansas, New York, and Virginia.
Table 2
Experiment Conditions
Condition
Target Type
Sender
1
Static
Yes
2
Static
No
3
Dynamic
Yes
4
Dynamic
No
3.5 Sender Selection
The sender for all trials was the principal investigator (PI), who was in Lititz, Pennsylvania.
3.6 Session Protocol
3.6.1 Target Preparation
Prior to beginning the experiment, an experiment coordinator randomly generated a unique set of 20
static and 20 dynamic targets for each of the five receivers. After a target was selected, it was immedi-
ately returned to the pool of possible targets and so could be used again. Within each target type, a
counter balanced set of sender/no sender conditions was also generated. A copy of each target was
placed in an envelope and a trial number, 1 through 40, was written on the outside. Those envelopes
containing targets from the no-sender condition were sealed while those for the sender condition re-
mained unsealed. Each set of 40 targets was packaged separately and shipped to the PI in Pennsylvania.
3.6.2 Trial Schedule
The experiment was conducted over a five month period. Individual schedules were developed with each
receiver so as to cause as little inconvenience to their daily routine as possible.
3.6.3 Session Sequence
For each trial and for each receiver, the PI proceeded as follows:
. Selected the appropriately numbered envelope from the box for the appropriate receiver.
. In the sender condition, looked at the selected target for 15 minutes and attempted to "transmit" it to the
intended receiver during that time period.
. In the no-sender condition for the static targets, placed the unopened envelope on an uncluttered
desk in the PI's office for the 15 minute trial period. In the no-sender condition for the dynamic tar-
gets, played the video repeatedly for 15 minutes with the sound turned off and the TV monitor in
another room.
. At the conclusion of the 15 minute trial period and after the receipt of the receiver's response by fac-
simile, sent a copy of the target material (i.e., either a photograph or video tape) to the receiver by
mail.
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During each trial, the receiver took these actions:
. At the prearranged time, withdrew to a quiet lighted room in his or her home and sat at a desk.
. For a period lasting up to 30 minutes, wrote and drew his or her impressions of the intended target
material, which was located in Lititz, PA.
. At the end of the AC trial, sent a copy of the response to the PI by facsimile machine.
. By mail, obtained a copy of the target as feedback for the trial. The target copy and original response
were subsequently sent to the experiment coordinator in Menlo Park, CA.
We did not provide specific instructions beyond logistical information to the receivers, because the re-
ceivers were all experienced at this type of task.
When the experiment coordinator received the receiver's response, all identifying information (i.e.
name, date, and time of trial) was removed from the response. Periodically during the course of the
experiment the experiment coordinator provided an analyst, who was blind to the target choice, with a
set of responses and associated target packs for analysis. Each target pack consisted of the real target
and four decoy targets of the same target type and similar AS.
3.7 Analysis
3.7.1 Rank-Order
For each trial, there was a single response and its associated target pack (i.e., either static or dynamic).
During the first part of the analysis, a judge, who was blind to the condition and target for the trial, was
asked to rank-order the targets within the given pack. This was a forced rank, so regardless of the quali-
ty of match between the response and targets within the pack, the judge had to assign a first place match
to a response, a second place match to a response, and so on for each of the five targets. The output
from this part of the analysis is a rank-order number (i.e., one to five, one corresponding to a first place
match) for the correct target. As was described above, the targets within each pack were chosen to be
visually different from one another, but they all possessed similar 4S. Thus, the rank number was not
biased because of entropy considerations.
For each receiver, target type, and condition there are 10 such rank-order numbers that constitute a
block of data. A rank-order effect size was computed for a block as:
RyJ - Ro
N2-1
12
(3)
where Ry is the average rank for target type i and sender condition j, and Ro is the expected average
rank, which for this study is equal to three for all cases. In Equation 3, N is the number of possible ranks
and is equal to five throughout this study. Reversing the sign in the numerator, Equation 3 reduces to:
By = 3- R1.
12
3.7.2 Analysis of Variance
A two-way analysis of variance (ANOVA) was computed for each receiver. The two primary variables
were target type and sender condition (i.e., ANOVA main effects). Each of these variables possessed
two states as shown in Table 2.
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Possible Effect of Geomagnetic Fluctuations
on the Timing of Epileptic Seizures
JAMES SPOTTISWOODE ERIK TAUBØLL
MICHAEL DUCHOWNY VERNON NEPPE
ADDRESSES: Science Applications International Corporation, Cognitive Science Laboratory, 1010 El Camino
Real Suite 330, Menlo Park, California 94025, USA (S.J.P.Spottiswoode, BSc); Department of Neurology, Rik-
shospitalet 0027, Oslo 1, Norway (E. Taubøll, MD); Department of Neurology, Miami Children's Hospital, Salo-
man Klein Pavilion, Miami, Florida 33155 USA (M.S.Duchowny, MD); Division of Neuropsychiatry, Universi-
ty of Washington, Seattle, Washington 98195 USA (V.M.Neppe, MD). Correspondence to S.J.P.Spottiswoode.
Running head:
Geomagnetism and epileptic seizure.
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Abstract
Some reports have suggested that epileptic seizures might occur more frequently at times of
enhanced disturbance of the geomagnetic field. This study examines this putative association
using 4101 seizures from 22 epileptic patients where the seizure times were known to within a
day or better. A measure of the geomagnetic fluctuation level for the seizure day, and the
days preceding the seizures, was derived from the geomagnetic index ap. This daily index
was significantly higher on the seizure days than on the day prior to the seizures (p = 0.007)
and slightly higher than for the preceding 10 days (p = 0.1). The effect size for the increase
for the increase of geomagnetic activity on seizure days from the previous days was inhomo-
geneous across this group of patients (p = 0.04), suggesting an uncontrolled factor. However,
a regression of age, sex, seizure type and frequency onto effect size failed to reveal any signif-
icant loadings.
Key words:
humans; geomagnetism; epilepsy; seizure; magnetic field
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Introduction
The reasons for the precise timing of epileptic seizures in most patients remain largely
unknown. Statistical studies of seizure timing have failed to identify clearly non-random
patterns such as clustering or periodicity in many patients.1,2 Several explanations for this
have been suggested, including the postulation of an inherently random endogenous
mechanism3 and the possibility that seizure occurrence might be more or less tightly coupled
to an exogenous variable which itself had nearly random statistics. In considering the second
of these hypotheses several workers have looked for a suitable environmental stimulus in the
very low frequency region of the electromagnetic (EM) spectrum. EM waves with
frequencies of 104 Hz or less have several natural sources, including lightning discharges and
ionospheric phenomena, and exhibit a complex distribution in time.4 These long wavelength
EM emissions are detectable everywhere on the globe and penetrate buildings and conducting
structures with little attenuation. Additionally there is some evidence that such low frequency
EM fields can interact with the functioning of biological systems, though the question is far
from settled.5,6 A connection between the triggering of epileptic seizure and low frequency
EM radiation therefore has a certain prima facie plausibility.
Some reports have suggested that epileptic seizure frequency may be correlated with
disturbances of the geomagnetic field (GMF).7,8,9 Fluctuations in the GMF are primarily
driven by changes in the sun's activity and major solar storms give rise to magnetic field
changes of up to 1000 nT at the earth's surface and cover a range of frequencies from
approximately 20 uHz to 10 Hz.4 The literature on the effects of magnetic field exposure
upon epileptic seizure, while not extensive, contains some suggestive avenues of research.
Venkatraman5 originally suggested that there might be an association between magnetic
storms and epileptic attacks but did not provide any statistics to support this conclusion.
Rajaram & Mitra6 reported that monthly averages of admissions of epileptic cases rose during
periods of increased GMF variation. However, no attempt was made to control for other
factors which influence hospital admissions. According to Keshavan et al7 a decrease in
convulsive threshold in rats was observed during the GMF variation associated with a solar
eclipse. Persinger10 has suggested that increases in the GMF noise level suppress nocturnal
melatonin levels, precipitating seizures and consequent cardiovascular instability. Significant
correlations have also been reported between epileptic seizure onset and 10 kHz and 28 kHz
atmospherics.11 However a laboratory study of audiogenic seizure susceptible rats failed to
find an association between EM at these frequencies and seizure timing.12 There is also
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evidence that exposure to relatively intense (105 nT) 60 Hz magnetic fields may actually
inhibit electrically kindled seizures in rats.13
Numerous biological effects from exposure to weak VLF and ULF magnetic fields
have been reported, as is demonstrated in reviews of this literature such as those by Adey5 and
Marino and Becker.6 Interest in the area has recently been stimulated by concern with the
possible carcinogenicity of the 50 and 60 Hz magnetic fields associated with power
generation and distribution. However, the physical mechanisms which might account for
biological sensitivity to weak, low frequency, magnetic fields such as the GMF remain
obscure. Adair14 has calculated the electric fields and other effects in cells and cell
membranes consequent upon 60 Hz magnetic fields of larger amplitude (and frequency) than
GMF fields. He finds that the induced electric fields are considerably smaller than the fields
due to thermal noise. However his arguments do not entirely rule out interactions involving
larger multicellular receptors. It is also possible that the putative association between
enhanced GMF disturbance and epileptic seizure may not be caused by the magnetic field
itself, but rather by some other environmental parameter15 which co-varies with the GMF
changes. The physics of possible mechanisms for electromagnetic triggering of epileptic
seizure is not well enough understood to suggest what frequency or amplitude of EM
radiation might be responsible for such an effect. While the epidemiological literature
suggests that a weak connection between seizure timing and enhanced GMF activity may
exist, the evidence is not statistically assessable.
This study examines one of the hypotheses raised by the earlier literature, specifically
whether epileptic seizure timing in humans is associated with increased GMF fluctuations at
the time of the seizures. Seizure diaries from 22 epileptic patients, containing timings of 4101
seizures, were analyzed to see whether these events occurred at times of enhanced GMF
activity. By using seizure diaries, rather than hospital admission records, many potentially
confounding factors can be avoided. In the light of the earlier studies it was hypothesized that
the days on which epileptic seizures occurred would show higher levels of GMF activity than
that of the preceding days.
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3.7.3 Post-Hoc Assessment
Rank-order analysis does not usually indicate the absolute quality of the AC. For example, a response
which is a near-perfect description of the target receives a rank of one. Yet a response which barely
matches the target, may also receive a rank of one. Table 3 shows the rating scale that we used to per-
form a post hoc assessment of the quality of the AC responses regardless of their rank. The quality of an
AC response is defined as its visual correspondence with the intended target.
Table 3.
0-7 Point Post Hoc Assessment Scale
Score
Description
7
Excellent correspondence, including good analytical detail, with essentially no
incorrect information.
6
Good correspondence with good analytical information and relatively little
incorrect information.
5
Good correspondence with unambiguous unique matchable elements, but
some incorrect information.
4
Good correspondence with several matchable elements intermixed with
incorrect information.
3
Mixture of correct and incorrect elements, but enough of the former to indicate
receiver has made contact with the target.
2
Some correct elements, but not sufficient to suggest results beyond chance
expectation.
1
Very little correspondence.
0
No correspondence.
To apply this subjective scale to a target-response trial, an analyst begins with a score of seven and deter-
mines if the description for that score is correct. If not, then the analyst tries a score of six and so on. In this
way the scale is traversed from seven toward zero until the score-description is correct for the trial.
Figures 8 through 10 illustrate the application of this scale and show that the quality of an AC response
is not necessarily indicated by its first-place rank. All three examples were given a rank of one in a blind
analysis. These examples were chosen from the experiment which is being described in this section (i.e.,
Section IV). The response to the waterfall target in Figure 8 included a number of pages of material
about a city and other man-made activity. In all of our analyses, we strictly adhere to the concept that
any material a receiver deletes from the response prior to feedback is not counted in the analysis. Thus,
the response in Figure 8 is considered as complete. The other examples are shown in their entirety.
The scale shown in Table 3 can be divided into two sections, 0-3 and 4-7. The upper portion of the scale
indicates clear contact, presumably by AC means, with the intended target material, while the remain-
der of the scale indicates little or no contact.
We used this scale to provide assessment scores to examine the correlation with the target entropy.
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CPYRGHT
. .. .
------
TARGET
rocks
water flowing
1) City, buildings seems to be a big leap
from what I am feeling about the target. I'll
restart.
waterfall
2) Troubled by city feeling. Could be that the
uprights are natural rather than man-
made. In which case the city interpretation
is incorrect and I am feeling MESA. I'll
check verticals.
vertical drop
3) DELETE Lights, structure, structures,
building, and city. We gots a waterfall,
dude.
turbulence
water spray in the air
Figure 8. Target and Response with a Post Hoc Rating of 7
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CPYRGHT
white rectangular box like an upside-down
sheet cake
1
short
long
same box
2
two circular shapes in front, like stepping
stones in a garden
long hollow tube, like crashing surf on a
beach - "Hawaii Pipeline"
3
dark interior
Figure 9. Target and Response with a Post Hoc Rating of 4
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CPYRGHT
BEGIN-10:30 AM
puffy balls - almost cotton-like. Cottony
puffy splotches. Movement - whizzing
through these cottony puffs fast. Damp-
ness. A long walkway & metal girders.
BREAK
I keep wanting to say - specifically - air-
field landing strip. Flat land. Big airplanes
would land here like naval carriers. Has a
broken white line down the center of strip &
you see it straight on - like you would be
coming in for a landing.
-
Figure 10. Target and Response with a Post Hoc Rating of 1
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4. Hypotheses
4.1 Null Hypothesis
The overall null hypothesis was that e = 0.
4.2 Sender and Target Condition
Using an F-test we tested the hypothesis that the quality of AC does not depend upon a sender regard-
less of target type. Similarly, we used an F-test to test the hypothesis that the quality of AC does not
depend upon target type regardless of the sender condition.
The ANOVA also tests for potential interactions between the target and sender conditions. For exam-
ple, it might be that a sender is required for dynamic targets and not for static ones.
4.3 Target Entropy
The AC quality (i.e., scores greater than three from the post hoc scale in Table 3) of each trial was corre-
lated with target 4S. A significant correlation would indicate that target entropy and AC quality may be
linearly related.
5. Results and Discussion
5.1 Effect Size Analysis
Five receivers completed 40 trials each. Table 4 shows the effect sizes (i.e., z / jn ) computed for the 10
trials in each cell. The shaded cells indicate 1-tailed significant results. Receiver 009 showed significant
evidence for AC in the static target, no-sender condition (p ≤ 0.02); receiver 372 in the static target,
sender condition (p ≤0.01); and receiver 518 in the static target, no-sender condition (p ≤ 0.05). See
the underscored values in Table 4.
Table 4.
Effect Sizes
Receiver
Sender
Static
No Sender
Dynamic
No Sender
Static
Sender
Dynamic
009
-0.071
0.141
0.636
-0.141
131
-0.071
0.495
-0.071
0.212
372
0.707
-0.283
0.141
-0.354
389
0.141
0.000
0.212
0.000
518
-0.088
0.283
0.530
-0.495
5.2 Analysis of Variance
Table 5 shows the results of an ANOVA on these data. Since there were 10 trials within each cell, the
degrees of freedom are the same for all receivers and, therefore, are only shown in the column headings.
Two receivers show significant main effects. Receiver 372 showed a tendency to favor static over dy-
namic targets (i.e., p ≤ 0.03), and receiver 518 showed a tendency to favor no sender (i.e., p ≤ 0.04).
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See the underscored values in Table 5. That is, for these receivers the ANOVA hypothesis that the data
are drawn from the same distribution is rejected. There were no significant interactions between target
type and sender condition.
Table 5.
ANOVA Results
Sender Condition
Target Type
Interaction
Receiver
F(1,36)
P-Value
F(1,36)
P-Value
F(1,36)
P-Value
009
0.38
0.54
0.68
0.42
2.08
0.16
131
0.18
0.67
1.66
0.21
0.18
0.67
372
1.01
0.32
5.47
0.03
0.61
0.44
389
0.01
0.91
0.33
0.57
0.01
0.91
518
4.43
0.04
0.97
0.33
0.06
0.81
When we combined the data for static targets regardless of the sender condition (i.e., 100 trials), the
sum-of-ranks was 265 (i.e., exact sum-of-rank probability of p ≤ 0.0073, effect size = 0.248). The total
sum-of-ranks for the dynamic targets was 300 (i.e., p ≤ 0.500, effect size = 0.000).
5.3 Post Hoc Assessment
Two analysts independently rated all 100 trials (i.e., 20 each from five receivers) from the static-target
sessions using the post hoc rating scale shown in Table 3. All differences of assignments were resolved in
discussion, thus the resulting scores represented a reasonable consensus of the visual quality of the AC
for each trial.
We had specified in advance that for the correlation with the change of target entropy, we would only use
the section of the post hoc rating scale that represented definitive, albeit subjective, AC contact with the
target (i.e., scores four through seven). Figure 11 shows a scatter diagram for the post hoc rating and the
associated AS for the 28 trials with static targets that met this requirement. Shown also is a linear least-
squares fit to the data and the linear correlation coefficient correlation (i.e., r = 0.461, df = 26).
This strong correlation suggests that AS is an intrinsic property of a static target and that the quality of
an AC response will be enhanced for targets with large AS. This correlation, however, might be a result
of AS and the post hoc rating independently correlating with the targets' visual complexity. For exam-
ple, an analyst is able to find more matching elements (i.e., a higher post hoc rating) in a visually complex
target than in a visually simple one. Similarly, AS may be larger for more complex targets. If these hy-
potheses were true, the correlation shown in Figure 11 would not necessarily support the hypothesis
that AS is an important intrinsic target property for successful AC.
To check the validity of the correlation, we used a definition of visual complexity that was derived from a
fuzzy set representation of the target pool.7 We had previously coded by consensus 131 different poten-
tial target elements for their visual impact on each of the targets in the pool. It is beyond the scope of
this report to provide the details of this technique since the details may be found in reference 7. It suf-
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fices to say, however, that the sigma-count (i.e., the sum of the membership values over all 131 visual
elements) for each target is proportional to its visual complexity. A list of these target elements may be
found in Appendix A.
2.5
Change of Spatial Entropy (bits/cm^2)
r = 0.461
df = 26
2.0
00
0
1.5
8
0
1.0
0
8
8
0.5
0.0
3
4
5
6
7
8
Post Hoc Score
Figure 11. Correlation of Post Hoc Score with Static Target AS
We computed the liner correlation coefficient for target complexity with the assigned post hoc rating.
For all 100 static targets used in this study we found r = 0.049, df = 98, and for target complexity with the
measured AS, we foundr = - 0.031, df = 98."
On closer inspection neither of these small correlations is surprising. While it is true that an analyst will
find more matchable elements in a complex target, so also are there many elements that do not match.
Since the rating scale (i.e., Table 3) is sensitive to correct and incorrect elements, the analyst is not
biased by visual complexity.
The change of Shannon entropy is derived from the intensities of the three primary colors (i.e., Equa-
tion 1 on page 13) and is unrelated to large-scale objects or meaning, which is inherent in the definition
of visual complexity. Thus, we would not expect a correlation between AS and visual complexity.
Visual complexity, therefore, cannot account for the correlation shown in Figure 11; thus, we are able to
conclude that the quality of an AC response depends upon the spatial information (i.e., change of Shan-
non entropy) in a static target.
A single analyst scored the 100 responses from the dynamic targets using the post hoc scale in Table 3.
Figure 12 shows the scatter diagram for the post hoc scores and the associated AS for the 24 trials with a
score greater than three for the dynamic targets . We found a linear correlation of r = 0.043, df = 22.
* Using just the 28 data points in Figure 11, we findr = - 0.216, df = 26 andr = 0.003, df = 26 for the correlation with the post hoc
score and AS, respectively. Since these correlations are negative or very small, they do not alter the conclusion.
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4
Change of Spatial Entropy (bits/cm^2)
0
0
0
0
0
0
8
O
2 -
8
8
0
0
r = 0.043
df = 22
0
3
4
5
6
7
8
Post Hoc Score
Figure 12. Correlation of Post Hoc Score with Dynamic Target AS.
This small correlation is not consistent with the result derived from the static targets; therefore, we will
examine this case carefully. The total sum of ranks for the dynamic-target case was exactly mean chance
expectation, which may indicate that little AC was observed (see Section 5.2, above). Twenty-four
trials, however, received a post hoc score of four or more. We see in Figure 12 that only two trials re-
ceived a score of seven, and those trials were among the lowest AS. It may be that the small correlation is
strongly influenced by these two data points, and a more accurate determination of a putative effect
with dynamic targets requires more trials in a future experiment. To determine if there is a trend with-
out the two data points with a score of seven, we computed the correlation for the remainder of the data
(i.e., r = 0.293, df = 20). Given the post hoc nature of this calculation, all we can conclude is that we
should conduct a similar experiment with dynamic targets to determine if a fundamental correlation
between AS and AC quality exists, as it does with the static targets.
There is a potentially more important reason that robust AC was not observed in the dynamic target set.
Most previous research has considered AC from a "systems" perspective in that the target and receiver
are thought of as a single AC unit.1,2 This is not particularly productive if we are searching for intrinsic
properties of target systems to guide target selection. An intrinsic target property is one that is in-
herently tied to the target (e.g., size, distance from the receiver, activity, entropy) and devoid of any
external interpretation. Interpretations, such as emotional impact, can be considered as extrinsic prop-
erties of the target or, more precisely, intrinsic properties of the receiver. Extrinsic target properties
are critical when AC is viewed from a systems point of view; however, if these properties can be con-
trolled in experiments, then it is possible to examine intrinsic target properties with little confounding
interference from the extrinsic ones.
As an aid in understanding extrinsic noise properties of targets, we define target pool bandwidth as a
qualitative indicator of the number of disparate target elements in the pool. The dynamic targets, which
were clips from video movies, represent a large-bandwidth pool; such disparate scenarios as Superman
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in space, a nature segment on the Grand Canyon, and a James Bond thriller can be included in the same
target pool. Conversely, the well-known Zener cards represent a vary narrow target bandwidth. The
static targets, which are constructed from a collection of National Geographic magazine photographs,
represent an intermediate bandwidth; the size and general content of the material is roughly the same
throughout the pool.
We hypothesize that the bandwidth of the target pool is a source of intrinsic noise in the receiver. We
assume that the information that is gained by AC is small compared to other sensory mechanisms, and
the primary mental task for a receiver is to discriminate the AC data from internally generated, target-
unrelated information. For large bandwidth target pools that may contain almost anything, a receiver is
unable to censor his/her internal experience. Thus, target-related and target-unrelated material are
equally reported; therefore, large bandwidth pools are extrinsically noisy. Small bandwidth pools are
also extrinsically noisy but for a different reason. If a receiver is cognizant of all of a limited set of target
elements (e.g., Zener cards), then he/she has an internal discrimination problem. All target possibili-
ties are experienced with equal intensity because of knowledge about the pool and vivid short-term
memory. Assuming there is weak AC information about the specific target, then target-extrinsic noise
is generated because of the very low signal-to-noise ratio.
Most of our receivers have participated in many earlier experiments which used the static target pool,
and were unfamiliar with target pools with large bandwidths such as the dynamic pool. Historically, we
have observed AC effect sizes for static targets 50% to 100% larger than we found in this experiment.
The current protocol did not include monitoring the AC trials, and the receivers were blind to the target
type. It is impossible to determine from this experiment which factor was predominant, but if the band-
width argument is correct, we would expect a decrease in functioning for even the static targets because
receivers would not be able to self-censor their responses .*
We recommend that a new target pool be developed that limits the bandwidth of the dynamic targets
and that the static targets be specific frames from within the dynamic target pool. In this way, we can
control for target bandwidth effects between the target types. We recommend that a new experiment be
conducted with these new target pools.
5.4 Overall Conclusions
Based upon the results of this pilot experiment, we provide the following tentative conclusions:
. The ANOVA results suggest that a sender is not fundamentally required for AC.
. Subject to the caveat suggested in the previous section, the ANOVA results suggest that AC quality
does not depend upon target type.
. AC quality for static targets is proportional to a target's spatial information (i.e., AS).
Because of the importance of determining if AS is an intrinsic target property for all AC targets, we urge
that this study be repeated with the improvements discussed above.
* It is important to recognize that limited, or even complete, knowledge of the target pool cannot bias the blind rank-order statis-
tic because it is a differential measure within the pool. It may, however, change the mean of the post hoc scores, but correlations
are insensitive to means. Thus, correlations based upon the post hoc assessment remain valid.
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V. ENHANCING DETECTION OF AC OF
BINARY TARGETS
This section constitutes the final report for SOW item 6.2.3.3.
1. Objective
The objective of this investigation was to replicate and extend an earlier study that enhanced the detec-
tion of AC of binary targets.
2. Background
In 1984, Puthoff used a majority vote procedure to statistically enhance the detection AC of binary tar-
gets.9 The chance probability of guessing a binary target correctly is 0.50. In Puthoff's experiment, his
best receiver, using AC methods, increased the probability to 60%. Using a majority vote of five guesses
per bit, the probability of guessing the target correctly was increased by 18.3% from 60 to 71 percent.
In fact, if the probability of guessing a binary target is given by
p = Po + 8,
(4)
where o is a non-negative constant much, much less than unity and po = 0.5, then it can be shown that a
majority vote procedure is the most efficient method for obtaining an arbitrarily accurate guess. Let n be
the number of bits in a majority vote procedure (i.e., n is assumed to be odd). Then the majority vote proba-
bility is given by a binomial sum as:
P(n) = p" + (n-1) pm-1(1 -p) + · +
n
n+ 1
2
p"21(1 - p)"21,
*+1
where p is the single bit probability given by Equation 4. By choosing n large, P(n) can approach unity.
The problem is that a majority vote procedure is predicated on the assumption that & is not a function of
time, an assumption that is known not to be true in AC experiments. Ryzl attempted to solve this problem
by modifying a majority vote scheme to include on-line checks.10 He was able to demonstrate a 100% accu-
rate guess of 15 decimal digits encoded as 50 binary digits (p = 10-15).
In 1985, Puthoff, May, and Thomson used a well-known technique called sequential analysis (SA) and,
for one receiver, realized a 3.7% enhancement 53.6 to 55.6 percent in a binary AC experiment.11 Dif-
fering from the usual statistical analysis, SA does not require that the sample size be specified in ad-
vance; however, by adjusting certain SA parameters, it is possible to set the expected number of trials in
the processes.
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In this pilot experiment, we set the expected number of trials in an SA algorithm to match the temporal
variation of 8(t). Thus, we expected to realize a significant enhancement of binary AC.
3. Approach
3.1 Theoretical
Letp be the probability that a binary random variable has the value one. With SA, we test the hypothesis Ho:
p = po against the hypothesis H1: p = p1. After accepting Ho as true, define a to be the probability that Ho
was false and that H1 was true (i.e., Type I error). Likewise, after accepting Hy as true, define B to be the
probability that H1 was false and that Ho was true (i.e., Type II error). Let n be the current sample number.
With parameters po, P1, a, and §, SA defines two lines as follows:
y1 = an + b1 and yo = an - bo, where
1 (+), bo = In(ta), and b = "(-)
A = In(!) + In(=).
. - P1
(5)
Let N be the accumulated number of ones in a Bernoulli sampling situation. Then the general SA deci-
sion algorithm is as follows:
. Collect one binary sample and add its value (i.e., zero or one) to the accumulated number of ones, N.
. Compare the accumulated value to y1 and yo in Equation 5.
. IfN ≥ y1 (n), then stop the sampling and conclude that hypothesis H1 is true with a risk of being wrong
of B.
. IfN ≤ yo(n), then stop the sampling and conclude that hypothesis Ho is true with a risk of being wrong
of a.
· If yo(n) ≤ N≤ y](n), then continuing sampling.
In the general theory of SA, this decision process always converges, and the expected number of samples
for a decision in favor of each hypothesis is given by:
(1 - a) In(-a)+ a in(1=)
EHO (n) =
po In(ft) - (1- po)In(=P;)
and
Bin(a) + (1 - B)In( == 2)
EH, (n) =
P1 In(%) - (1 - p1)In(2-52)
(6)
For an arbitrary value of p, we compute the probability that the SA algorithm will decide in favor of
hypothesis H1 (i.e., the operating characteristic function-OC) as:
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OC(p) = 1 -
(1=)" -1
( = ) - (-a)
« , where p is given by
1-P1
k
(6)- 1-
-
1-Po
'1-
-P1
p(h) =
, where -oo sh ≤ +00.
(7)
3.2 A Two-talled Example of Sequential Analysis
In this section we modify the formalism of SA to include a measure of the difference between the accu-
mulated number of ones and the expected number of ones. This will allow a two-tailed application of
SA. The only modification that is necessary to Equation 5 is that the slope, a, is now given by:
(2) po
1-PO
- Po-
(8)
In this example we assume that a = B, so that the curves (see Figure 13) that define the decision algo-
rithm are symmetric. Let 8 be the accumulated excess number of ones (i.e., the number of ones minus
the expected number of ones). In the two-tailed case, the two hypotheses that are tested by SA become
Ho: p = Po, and H]: p = p1 or p = 1 - p1.
Line y1
Accumulated Excess Number of Ones
Region 1
Line yo
0
Region 3
Line -yo
Region 2
Line -y1
Sample Number
Figure 13. Two-tailed SA Decision Graph
When 8 enters either Region 1 or 2, stop the sampling and assume Hy is true with a Type II error of B.
Likewise, if 8 enters Region 3, stop the sampling and assume Ho is true with a Type I error of a.
3.3 Hypotheses
The two hypotheses that were tested in this experiment are:
(1) Ho: p = po = 0.5, and
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(2) H1: p = p1 = 0.6 or p = 1 - p1 = 0.4.
We chose Po = 0.5 because that is the expected hit rate for binary guessing, and we chose p1 = 0.6 because
that was the approximate individual hit rate reported in Ryzl's and in Puthoff's experiment. We adjusted
the values of a and B such that the expected number of samples per SA decision was approximately 40, a
value that is consistent with anecdotal reports of how many trials can be collected during a single session
before a receiver becomes bored with the task. Figure 14 shows the OC curve for these parameters.
SA Parameters
1.0
p0 = 0.50
p1 = 0.60
a = 0.20
0.8
₿ = 0.20
Probability of P1 Decision
0.6
0.4
T
Majority Vote of 5
- Sequential Analysis
0.2
T
....
0.0
0.0
0.2
0.4
0.6
0.8
1.0
Event Probability
Figure 14. Operating Characteristic Function - 1-Tail
For comparison, we also show in Figure 14 the majority-vote-of-five curve that was successfully
employed in Puthoff's experiment. Using the SA method, we expect an enhancement of approximately
42% at 0.6 hitting rate compared to the 18% seen by Puthoff. In addition, our two-tailed formalism
allows a receiver to use AC to detect either a binary one or a binary zero. Another advantage of SA over
majority vote can be see from Figure 14. For p less than 0.5, the Type I error is sharply reduced. Thus,
the false-positive decisions are reduced accordingly.
Figure 15 shows the OC for the 2-tailed SA scheme displayed in Figure 13. For this calculation, we as-
sume that the accumulated deviations result in an extreme decision (i.e., lines :y1). That is, under the
null hypothesis, 80% of the decisions will be on the inner decision lines in Figure 13. Of the 20% re-
maining decisions, 50% will strike the upper decision line. This curve, therefore, demonstrates that
under the null hypothesis there will be no enhancement.
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SA Parameters
1.0
p0 = 0.40
p1 = 0.60
a = 0.20
₿ = 0.20
0.8
Probability of P1 Decision
T
0.6
0.4
0.2
0.0-
0.0
0.2
0.4
0.6
0.8
1.0
Event Probability
Figure 15. Operating Characteristic Function - 2-Tail
3.4 Protocol
3.4.1 Receiver Selection
Three receivers participated in this study. One (receiver 531) was selected because that individual had pro-
duced statistically significant results in earlier similar experiments.12,13 Two receivers (7 and 83) were se-
lected because of their interest and because of successes in free-response AC experiments.
3.4.2 Target Selection
A Sun Microsystem's SPARC workstation used a feedback shift register algorithm to generate a single
binary target for each SA decision trial.14
3.4.3 Trial Definition
A trial was defined as an assertive SA decision. That is, either p = p1 or p = 1 - p1. Decisions resulting
in p = po were tabulated, but otherwise ignored. Each receiver contributed 100 trials.
3.4.4 Sample Definition
An experimental control program oscillated a single binary bit between one and zero as rapidly as pos-
sible. When a mouse button was pressed, the state of that oscillating bit represented the value of the
single sample.
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3.4.5 Trial Protocol
Each trial proceeded as follows:
(1) The receiver started the experimental control program, which asked for the receiver's name.
(2) The program determined if the current trial was a continuation of an earlier trial, or the beginning
of a new one.
(3) If the trial was being continued from an earlier session, the program read the previously saved data
and indicated that the receiver may begin.
(4) If the trial was a new one, the computer randomly displayed a new target and indicated that the
receiver may begin.
(5) The receiver pressed a mouse button to indicate when the oscillating bit matched the predeter-
mined trial target bit. We emphasized that the task for the receiver is a precognition one; press the
mouse button at a time when the oscillating bit matches the displayed target bit.
(6) The value of this sample bit was used as input to the SA algorithm.
(7) The receiver ended the session at any time (i.e., either within a trial or at the end of one).
3.4.6 Analysis
The analysis was defined by the SA algorithm. The control program recorded the number of matches
between SA decisions (i.e., either one or zero) and the trial target bit. It also recorded the total number
of button presses and the number of po decisions that occurred during the 100 SA trials.
The binomial distribution was used to calculate a p-value for each receiver, but the normal approxima-
tion to the binomial distribution was used to compute the effect sizes.
4. Results and Discussion
Tables 6 through 8 show the results for receivers 7, 83, and 531, respectively. The z-scores for the binomial
methods of analysis are shown for comparison only; since SA does not specify the number of samples, the
results tend to be inflated from their correct value. The binomial (decision) method included only those
samples that led to a definite SA decision, whereas the binomial (all) method included all samples.
Table 6
Receiver 7
Analysis Method
Hits
Trials
Rate
Z-Score
Sequential Analysis
49
101
0.485
-0.299
-0.030
Binomial (decision)
2,256
4,569
0.494
-0.843
-0.125
Binomial (all)
7,856
15,747
0.499
-0.279
-0.002
Receiver 7 inadvertently produced one extra trial; however, it did not affect the overall score of mean
chance expectation (i.e., rate = 0.50). As shown in Section V.3.3, SA did not inflate the chance results
beyond what was expected.
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Table 7
Receiver 83
Analysis Method
Hits
Trials
Rate
Z-Score
Sequential Analysis
44
100
0.440
-1.20
-0.120
Binomial (decision)
1,916
3,966
0.483
-2.13
-0.034
Binomial (all)
9,422
18,937
0.498
-0.68
-0.005
Receiver 83 produced an overall score of mean chance expectation.
Table 8
Receiver 531
Analysis Method
Hits
Trials
Rate
Z-Score
Sequential Analysis
76
100
0.760
5.20
0.520
Binomial (decision)
2,842
5,059
0.562
8.79
0.124
Binomial (all)
11,008
21,337
0.516
4.65
0.032
Receiver 531 produced an overall significant score (i.e. Z = 5.2, p ≤1 x 10-7, 8 = 0.52). This receiver is
experienced at computer tasks and the result is consistent with his historical performance. A raw hit
rate of 0.516 is what is usually seen,12 and the effect size of 0.032 is consistent with other forced choice
AC experiments.
Although only one receiver of three produced significant evidence of AC, the result is illustrative of the
technique, and because of 531's previous performance, we consider that this result is not likely to be
spurious. While a 16-fold enhancement of effect size was realized by the SA method, it is particularly
inefficient; to obtain 100 decisions, 531 pressed the mouse button 21,333 times for an efficiency of
0.47%. It is possible that the efficiency could be improved if the basic SA method could include some
adaptive method. That is, the parameters of the analysis could be modified on the basis of the recent
scoring rate. If sufficient improvement could be realized, this method might be incorporated as an aid
in decision making in practical applications.
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VI. MAGNETOENCEPHALOGRAPH
This section comprises the final report for SOW item 6.2.1.
1. Introduction
In a series of electroencephalograph (EEG) experiments conducted at SRI International beginning in
1974, the central nervous system (CNS) of individuals was found to respond to remote and isolated visu-
al stimuli (i.e., a flashing light).15,16,17 In the first experiment, during randomly interleaved 10-second
epochs (i.e., trials), either a flashing light (16 Hz) or no light was present in a sensorially and physically
isolated room. Significant decreases of occipital alpha power of isolated receivers were observed by
Rebert and Turner.15 Two replications were conducted in collaboration with Galin and Ornstein at the
Langley Porter Neuropsychiatric Institute. As reported by May et al., the results were inconclusive; the
first replication confirmed the Rebert and Turner finding, a decrease of alpha power concomitant with
the flashing light, but the second replication attempt found an increase in alpha power.17
Under another program in FY 1988, SRI International and a biophysics group at a national laboratory
conducted an experiment using the magnetoencephalograph (MEG) technique. This experiment was
designed as a conceptual extension of the May et al. EEG experiment, although there were significant
differences in the protocol. Two types of stimuli were randomly presented to an isolated sender while
MEG data were collected from a receiver. The experimental stimulus (i.e., remote stimulus) was a 5-cm
square, linear, vertical sinusoidal grating lasting 100 milliseconds. The second stimulus, a control stimu-
lus (i.e., pseudostimulus), was simply a time marker corresponding to a blank screen in the data stream,
and was also presented to the sender. There was no change in the alpha power, as reported by May et
al., but a post hoc analysis revealed a root-mean-square average phase shift of the dominant alpha fre-
quency.18 A key result of that experiment was that similar "anomalous" phase shifts were obtained for
the remote stimuli and the pseudostimuli. Three candidate explanations for these results were sug-
gested. The observed phase shifts might have been:
· Spurious (i.e., statistical deviations within chance expectations)
· Electromagnetic artifacts
· Evidence of anomalous cognition
In order to determine which of these three candidate explanations was correct, we replicated the study at
the national laboratory as part of this current effort.
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2. Approach
In this section, we provide details of the replication of the 1988 MEG experiment.
2.1 Replication Protocol
2.1.1 Number of Trials
We assumed that the observed trial effect sizes that were reported for the previous MEG study resulted
from a putative AC effect.18 Under the remote stimulus condition (i.e., approximately 1,100 trials) we
found that the trial-level effect size was 0.060 ± 0.030. In statistical terms, this did not exceed mean
chance expectation.
To determine the number of trials necessary to provide a confident replication of the previous experi-
ment, we conservatively used the observed effect size minus one standard deviation (i.e., 0.030). Using
traditional statistical power analysis, we found that the probability of observing a significant AC effect
in 1,100 trials was 0.258. Conversely, if we require 95% confidence, a significant AC effect could be
observed in 12,026 trials, or approximately 120 blocks of 100 trials each.
Twelve individuals were initially identified as receivers for the formal replication; however, because of
scheduling difficulties only eight participated in the study. Seven receivers contributed ten blocks each,
and one receiver contributed five blocks. The statistical power for 7,500 trials was 0.83, which is the
probability of a significant replication over the total of 75 blocks. In this case, a given receiver had a 60%
chance of demonstrating an independently significant result if the AC hypothesis is true.
2.1.2 Receiver Selection
Eight experienced receivers, who either participated in the earlier MEG study or were known to be
"good" receivers from other investigations, participated in the study.
2.1.3 Sender Selection
An SAIC experimenter acted as sender throughout the study. While it is assumed that a sender is not
necessary for AC, it may have a vital psychological function.
2.1.4 Stimuli
The following two types of stimuli were generated by a PC, and consisted of an internal image that could
be sent to a standard TV monitor for display:
· Remote stimuli (RS). A low spatial-frequency sinusoidal grating lasting 100 milliseconds was used as
a remote stimulus.
· Pseudo Stimuli (PS). All data bytes corresponding to the pseudo stimuli were zero. Thus, the entire
video image was a blank screen corresponding to a "time marker" in the data.
An HP workstation controlled the collection of data and the presentation of the stimuli. Using a multi-
ple congruent pseudo random algorithm (i.e., Rn+1 = a0 × Rn + bo, where ag and bo are constants, and
0 ≤ R < 1.0), the nth + 1 stimulus was generated 3.0 + 4.5 x Rn+1 seconds after the nth stimulus. The
algorithm was seeded from the system clock. The HP notified the PC of the type and time for a stimulus.
The PC waited until the next vertical retrace signal from its hardware-video-output board; switched
pointers within the retrace cycle from the blank inter-stimulus (IS) frame buffer to one which contains
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either the RS or PS; and reset the buffer pointers after 100 ms (i.e., the stimulus duration = 100 ms).
Figure 16 shows this sequence in graphical form.
Main HP
IBM PC
Monitor
.... .
Buffer Pointers
Stimulus
Type RS/PS
Stimulus Initiation
Standard 30 Hz
Interleaved
RS Buffer
IS Buffer
Output Buffer
PS Buffer
Figure 16. Sequence of Events for Stimuli Generation
2.1.5 Placement of the Seven-Sensor MEG Array
The placement of the seven-sensor MEG array was determined by an individual receiver's response to a
direct light stimulus. While being stimulated by randomly interleaved low and high spatial-frequency
gratings, sufficient stimuli (e.g., 30 to 50 of each type) were collected to produce good signal-to-noise
responses. The position of the sensor array, relative to head-based coordinates, was recorded manually
on a skull cap, so that the array could be repositioned accurately during subsequent experimental
blocks. The array positions that were used during the RS blocks were determined by the maximum re-
sponse to these direct stimuli. For this portion of the experiment, the stimuli were generated three to
four times faster (i.e., = 1 per second) than in the AC portion of the experiment.
2.1.6 Session Protocol
The session protocol was a follows:
(1) Using the marking on the skull cap, the MEG array was repositioned as close as possible to the
original calibration location.
(2) Its position was confirmed with direct stimuli, and adjustments were made, if they were necessary.
(3) The designated sender was positioned in front of the remote monitor, which was located approxi-
mately 40 m from the receiver.
(4) The video monitor, which presented the direct stimuli, was turned off.
(5) The receiver was instructed to relax with eyes closed. In addition, the receiver was given a few
possible strategies that included focusing attention on the display that the sender was observing,
on the sender, or on both.
(6) The receiver was notified, by intercom, that the run was about to begin.
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(7) The run began and seven channels of MEG data and one channel of stimulus data were collected for
two minutes. The raw data were saved to disk, and the appropriate parameters for the next run
were entered into the log book and the control program.
(8)
After five runs, an experimenter quietly entered the MEG room, checked the MEG position, and
readjusted it, if necessary. No communication about the status of the experiment was provided.
(9)
Five additional runs were collected.
(10) At the end of the block, the receiver entered the control room and was shown a computer display of
the results of the last run. The experimenter pointed out interesting portions of the display, but
cautioned that the final results required careful analysis of all the runs, not just the last one.
2.1.7 Controls
Two types of controls were used in this experiment to assure the validity of the experimental results:
. Within-block. The data in the inter-stimulus times (IS) were used as a within-block control.
· Between-block. Using a counterbalanced random protocol, either immediately before or immediate-
ly after each 20-minute experiment block, an additional block of ten runs was taken under the same
conditions as the experiment block, but without the receiver under the MEG. The sender, however,
was "sending" as before.
2.1.8 Data Recording
Along with the experimental parameters, eight channels of 200 per second data were digitally recorded
for later analysis (i.e., seven channels of MEG data and one channel of stimulus data).
2.1.9 Analysis
2.1.9.1 Overview
A block of data was ten, 2-minute runs. Each block contained approximately 100 RS and 100 PS
stimuli, respectively, from each of the seven sensors. The following was computed for each stimulus
type and for each sensor:
· Time averages for 0.5 second prestimulus to 0.5 second poststimulus.
· Separate average power spectra for the prestimulus and poststimulus periods.
. Averages of the phase shift observed at the dominant a-frequency, which was determined from the
centroid of the peak with the largest area above "background" for experiment blocks; 10.0 Hz was
used for the between-block controls. The relative phase shift for a single stimulus is defined in Figure
17. The RMS average was computed over the total number of stimuli in the block.
The RMS average phase was the dependent variable for the block. A Monte Carlo calculation was used to
determine whether the observed phase shifts deviated from those observed at random times throughout the
rest of the block-data record. Each Monte Carlo pass computed the RMS phase over random entry points,
which were determined by the same timing algorithm described above, into the same 20-minute data set.
The timing algorithm was the same one used during the data collection; however, a new seed started the
process on each pass.
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Prestimulus: x(t)
Poststimulus: y(t)
x(t)
Linear Process
y(t)
X(v) = FFT [x(()]
Let:
Then:
Y(v) = FFT [y()]
Gain = \H(v)|
(Im H(v)'
Phase = 4(v) - tan -1 (RE H(G)
Figure 17. Phase Calculation for a Single Stimulus
Statistics (e.g., p-values, z-scores) were computed from the distribution of RMS phases derived from
the Monte-Carlo-pass distribution.
Conceptually, a 2-tailed z-score was calculated from a Monte Carlo distribution of phase shifts in the
following way: Let py and ow be the mean and standard deviation of the Monte Carlo phase shift dis-
tribution, and Yo be the observed RMS phase shift. Since the distribution of averages is approximately
normal, compute:
z =
40 - My
and P - Tm je-0
Z
e-0.5c dc.
Since we did not specify a direction for a change in phase, the p-value for the block was given by:
p = 2 x P,
and the two-tailed z-score was computed from the inverse normal distribution for P. In the experiment, the
empirical value of P was used. That is, the number of Monte Carlo-derived RMS phases that were greater
than or equal to the observed RMS phase was divided by the total number of Monte Carlo passes. There-
fore, the 1-o error estimate in P were computed from the binomial distribution for proportions. Or
1-o error in P =
V
P (1 - P)
M
where M is the number of Monte Carlo passes.
For this replication, the analyst was "blind" to the identity of the receiver, the date, the experiment
condition (i.e., experimental or control run), and the stimulus type.
2.1.9.2 Details of the Analysis
Consider N blocks of experimental data. Let nir be the number of remote stimulir for blockj, and njp be
the number of pseudo stimuli p in block j. Similarly, define &jr and &jp as the corresponding effect sizes
for block j. We define the weighted effect size for each stimulus type, k, as
VE
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where
WIR =
j=1
Hjk
N
,
and
k = r,p.
Tests Against the Null Hypothesis: The Average Effect Size E = 0. Since the experimental effect sizes,
Ejk, are derived from normally distributed data (i.e., Monte Carlo calculations of the RMS phase shift),
then we know the standard error for each Ejk is
sd(E) = THE .
(1)
Thus, the variance of the weighted average effect size is
Var(Ex) =
N
Σωζάνας(εικ) =
1
Ensk
N
.
The z-score associated with @ is
ZŁ =
Ex
Var(Ex)
.
(2)
Equation 2 is used to test the average effect sizes of the RS and PS for the experimental and control
conditions against the null hypothesis of € = 0 for the experimental and control conditions.
Tests Against the the Null Hypothesis: E(RS) - E(PS) = 0. Within a given condition we cannot assume
that the phase shifts from an RS are independent from those associated with a PS. Thus, hypotheses
tests that do not account for potential correlations between the RS and PS are inappropriate. Because
of the simplicity of the individual ajk, we can compute the exact variance for the differences as follows.
Let the difference between the effect sizes for RS and PS be
dj = &jr - Ejp.
Since there usually are a different number of stimuli for RS and PS, we define a weighting factor for the d; as
0, = "1,
j=1
where
n, x njp
nj - nj, + njp
Then the weighted mean difference is given by
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א
a = Lod,
The variance of a is given by:
Var(d) = >2;Var(d),
j=1
but
Var(d) = Var(€),) + Var(€)p) - 2 Cov(Ejn€jp),
but
Cov(Ejn€jp) = Qrp \Var(Ej+) . Var(Ejp) .
Combining these equations with the definition for the variance of the effect size, gives the Var(d) as
Var(a)= > [+) - 2 0ml
- 2 erp Var(Ej,) . Var(E)p) ,
L
and
Z =
Var(a)
(3)
Tests Against the Null Hypothesis: E(Experiment)-E(Control) = 0. To compare each stimulus type in
the experimental and control conditions, we assume that the data are independent. Thus, the z-score
for the difference is given by
- c)= Varende
a
Var(Ex(e)) + Var(E)(c))
P
(4)
=
,
- ++
1
RWD
KWI
where e and c represent the experiment and after-block control conditions, respectively, d is the
weighted difference for the stimulus type in the experiment and control conditions.
Equation 4 is used to test the difference between experimental blocks and their corresponding control
blocks.
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Table 9 summarizes these results.
Table 9.
Hypothesis Testing for Each Receiver
Hypothesis
Test Quantity
1. RS(e) have no effect.
En,(e) E,(e)
2. PS(e) have no effect.
En,(e) E,(e)
3. RS(c) have no effect.
Eni,(c) E,(c)
2. PS(c) have no effect.
Σ'ip(c) ε,(c)
a(RS - PS)
5. No RS(e)-PS(e) difference.
VER;[+++ -2 erp Var(,) . Var(;p)
Ep(e) - Ep (c)
7. No PS(e)-PS(c) difference.
+
3. Results
In the experimental condition the effect sizes we measured for the RS and the PS were all well within
mean chance expectation for all receivers individually and for the data, which were summed across re-
ceivers. This was also true for both stimulus types for the data that were collected during the between-
block controls .* All difference statistics shown in Table 9 were also at mean chance expectation.
Formally, therefore, we say that the 1988 study did not replicate, and that those earlier results appear to
be spurious.
During the analysis, however, a subtle but major problem was discovered that may render this conclu-
sion, at least, premature. The measurement of instantaneous phase was confounded by noise, so event-
related phase shifts might not have been seen with the current analytical technique.
4. Discussion
Using the same analytical techniques that were used in the 1988 study, we did not observe significant alpha
activity concomitant with RS; however, we realized, after the fact, that the 1988 analytical technique con-
tained a subtle flaw. We were attempting to measure instantaneous phase shifts of the dominant alpha
rhythm in the presence of considerable noise (i.e., the signal-to-noise ratio was approximately 0 decibels).
Under this circumstance, the variance of the phase is primarily determined by the noise (i.e., the Crammer-
* Unfortunately, some preliminary results, which were described in an earlier interim technical report, were incorrect. Because
of an inadvertent error in the timing parameters, the Monte Carlo calculations were only using the first 10% of the data. Cor-
recting this mistake caused the reported significances to vanish.
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Rao relationship19). One representation of the Crammer-Rao relationship for the variance of the instanta-
neous phase, ø, is given by
Var(+) ≥ AT xRSN
1
where 47 is the analysis time (i.e., 0.5 s in our case) and Rsw is the signal-to-noise ratio. For our typical
brain-wave records, the lower bound for Var(+) was approximately 2.67 rad,2 or the expected error was
1.63 rad or 93.6 degrees. This estimate is a lower bound, but a more realistic estimate might be higher
because of the nonstationary nature of brain-wave data. Thus, if there were phase shifts related to the
RS, they likely would have been masked by the noise, and we would not have seen them.
Fortunately, we have saved all the raw data and are able to use an appropriate analysis to determine
whether a phase shift occurred concomitant with the RS. We are unable to manipulate Rsw; however,
we are able, in principle, to extend the analysis time, 47, arbitrarily. There are confounding factors that
will limit the size of 47, so other techniques may have to be employed. In a recent article, Boashash has
outlined a number of promising techniques that are specifically developed to address this problem in
nonstationary data.19
It is important to look carefully at this data because a phase shift, or amplitude shift, should be there,
given that the alpha rhythm appears to respond to a variety of non-AC tasks. One such example is
event-related desynchronization (ERD). Spontaneous EEG reveals short-lasting, task- or event-re-
lated amplitude changes in rhythmic activity within the alpha band. This amplitude change, or desynch-
ronization, is one of the elementary phenomena in EEG. It was first described in 1930 by Berger20 in
scalp EEG as alpha blocking, and was later termed ERD by Pfurtscheller and Aranibar.21 ERDs can be
quantified as a function of time and can then be used to study cortical activation patterns during the
planning of motor behavior,22 sensory stimulation, and cognitive processes.23,24,25 Kaufman et al. pro-
vide a more recent example of cognitive-process-related ERDs.26 They found a significantly shorter
ERD when subjects simply responded to a target stimulus, compared with the ERD that occurred when a
subject had to search visual memory to determine whether the target matched one previously presented.
If we take the historical behavioral AC data as evidence of an anomaly, it would be surprising not to find
some form ERD, given we can provide the proper stimulus.
5. Suggested Research
Aside from the technical difficulties associated with the Crammer-Rao relationship, all of our earlier
attempts to identify CNS correlates to AC did not contain any concomitant behavioral measure of AC;
therefore, we have no independent measures that AC functioning occurred in these experiments. Also,
the conditions under which experiments were conducted were not similar to those known to be condu-
cive to the production of AC data. For example, there is no evidence that a flashing light constitutes a
valid AC target. It is also likely that when a receiver is asked to recline face down in a MEG laboratory,
that the conditions for the receiver are not optimal.
Il
We suggest that new experiments be designed to measure CNS responses to AC stimuli. Since we will not be
initially concerned about source localization, we will not immediately require the special properties of a
MEG.
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Specifically, we suggest the following as remedies to the problems that were described above. In series of
EEG experiments:
. Use stimuli that are identical to those in standard AC experiments.
. Demonstrate CNS correlates to these stimuli when they are directly presented to receivers.
· Provide a potential for independent, but concomitant, behavioral evidence for AC.
In addition, we suggest that the experiments should use EEG measures that more closely resemble
those that are used in more traditional psychophysiological experiments. In this way, conditions are
optimized to observe ERDs that may be related to AC stimuli.
.
..
.
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VII. ENHANCING DETECTION OF AC WITH
BINARY ENCODING
This section comprises the final report for SOW item 6.2.3.3.
1. Objective
The objective of this pilot study was to use a two-by-five error correcting block code to improve the
detection of AC.
2. Background
AC responses usually are narrative descriptions, which have been difficult to quantitatively assess. A
number of analysis techniques have been developed to deal with this problem. In one of the earliest
techniques, an analyst visited potential target sites and ranked them from best to worst match for each
AC response. The analyst had to determine subjectively the boundaries of the target and the elements
that were to be included in the analysis.6
During the next phase of the development, the target and the response were reduced to their individual
conceptual attributes. The analyst then had to compare lists of discrete attributes; one defining the re-
sponse and one each for the potential targets. This all-or-nothing binary determination proved to be
inappropriate for an inherently imprecise situation.27,28
Fuzzy sets were then used to allow a gradation of judgment in defining specific elements of content with-
in both the target and the response. This method, however, proved to be labor intensive and did not
significantly improve the stability and reliability of AC analysis.7
This pilot experiment was designed to explore the potential for maximizing the reliability of AC re-
sponses through objective and rapid analysis. We have reverted to using a dichotomous binary proce-
dure as opposed to a fuzzy set technique. By carefully selecting the dichotomous elements and by using
standard block coding techniques to incorporate all single and a few double error corrections, the earli-
er problem of all-or-nothing binary determinism might be reduced. A message sending motif was used
as a test-bed for this kind of analysis.
3. Approach
This pilot experiment was similar to a traditional AC experiment: a target was selected randomly; a re-
ceiver was asked to describe information that was not available to currently known sensorial channels;
and a quantitative assessment of the match between the target and the AC response was made. It differs
only in the construction of the target pool and in the quantitative analysis.
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3.1 Targets
The targets were all photographs from the National Geographic magazine. A special target pool was
constructed consisting of 10 packs, each of which contained four targets. Each target was described in
terms of permutations of five fixed attributes. Each target pack had its own individual set of five attrib-
utes, and each photograph was represented by a binary encoded number indicating the presence (i.e.,
binary one) or absence (i.e., binary zero) of each of the five attributes.
Table 10 shows the assigned attributes for each of the 10 target packs:
Table 10.
Attributes for Ten Target Packs
Bit Position
Pack
0
1
2
3
4
1
Repeat
Motif
Action
Mountains/Cliffs
Vehicle
Manmade
Structure
2
Towers
Vehicles
Mountains/Cliffs
Water
Buildings
3
Vehicle
Arch/Dome
Stepped
Buildings
Vegetation
4
Building
Circle
Rectangle
Triangles
Repeat Motif
5
Square/
Rectangle
Mountains/
Cliffs
Action
Natural
Arch/Dome
6
Mountain/
Hill
Water
Action
Building
Natural
7
Action
Water
Industrial
Vehicle
People
8
People
Natural
Vehicle
Vegetation
Buildings
9
Water
Mountains/
Hills
Buildings
Rural
Road/Bridge
10
People
Industrial
Mountains/Hills
Tower
Vehicle
For example, to construct the binary number 10101 from pack one, we found a photograph that contained a
repeat motif, mountains/cliffs, and manmade structures, but did not contain action or vehicles. The error-
correcting code that we are using required us to construct the following four binary numbers: 00000, 01110,
10101, and 11011 (see Figure 18, on page 52), that is, two "message" bits (i.e., first two from the left) and
three "check" bits. Using the attributes shown in Table 10, we identified four photographs for each pack
that satisfied these restrictions. Each of the four binary numbers were then represented by a single
photograph within each target pack.
3.2 Target Selection
For each trial in this experiment, a pseudo random number generator was used to select a pack and one
of four possible photographs within the pack to serve as a target.
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3.3 Receiver Selection
Five receivers were selected to participate in this experiment on the basis of their significant results
from previous AC experiments.
3.4 Protocol
3.4.1 Number of Trials
The five receivers contributed eight trials each.
3.4.2 Trial Protocol
Before the experiment began each receiver was provided with instructions and a list of dates on which
targets were to be at a prearranged location in the Menlo Park laboratory. The following steps were
performed for each trial:
(1) The PI used a pseudo random number generator to select a photograph (i.e., a binary number) from
the target pool and placed the photograph in a previously agreed upon location. This target re-
mained in the designated location for one week for the convenience of the receiver. Receivers had
access to the target, by AC methods only, at any point during this time period, since no senders or
session monitors were involved in this study.
(2) Receivers were to find a quiet place in their homes to work with pen and paper. For a period lasting
no longer than 15 minutes, each receiver was to write and draw his/her impressions of the target.
(3) The responses were sent by facsimile to the PI.
(4) The PI sent back a sheet of five questions about the target, which could be answered by "yes" or
"no." These questions pertained to the five target attributes for the target pack from which the
designated target was chosen (e.g., Does the target contain triangles?).
(5) The answers were sent back to the PI for analysis. Upon receipt, the PI provided a copy of the target
photograph as feedback.
(6) This procedure was repeated until eight trials were obtained from each receiver.
3.4.3 Analysis
At the end of the experiment, the PI removed the name, date, and time from each response; randomized the
order of the responses; and provided an analyst with the responses and associated target packs. The in-
tended target was not disclosed. Three different methods of analysis were used in this experiment:
· Rank ordering
· Number decoding (analyst)
· Number decoding (receiver)
3.4.3.1 Rank-Ordering
Traditional rank-ordering was the first method of analysis. When a target was chosen from one of the
target sets, the remaining three targets were considered "decoy" targets for an analyst. For each trial,
an analyst was given the AC response and the target pack (i.e., four targets) from which the actual target
was chosen. The analyst was required to rank order the targets within the designated pack from best to
least match to the response, regardless of the quality of the matches. The rank that was assigned to the
intended target represented the value of the dependent variable for the trial. A sum-of-ranks was then
computed for all trials for each receiver. Effect sizes and p-values were determined from the known
sum-of-ranks distribution. This method was used to determine the level of AC functioning for each
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receiver in the study. In addition, the number of direct hits (i.e., first place ranks) was computed for
each receiver and the binomial distribution was used to compute p-values and effect sizes from this per-
spective.
3.4.3.2 Number Decoding (Analyst)
For each response, an analyst, who was blind to the binary number for each trial, answered the same set
of questions that were sent to each receiver. In this way, the AC response was converted into a 5-bit
binary number. Figure 18 shows the decoding matrix, which is specified by the block coding.
00000
01110
10101
11011
}
Targets
00001
01111
10100
11010
00010
01100
10111
11001
00100
01010
10001
11111
Single Error
Correction
01000
00110
11101
10011
10000
11110
00101
01011
-
00011
01101
10110
11000
01001
00111
11100
10010
Double Error
Correction
Figure 18. A Two-by-Five Bit, Error Correcting Block Code
The PI then used the answers provided by the analyst to locate the 5-bit binary number from the decod-
ing matrix. The actual target binary number is the one represented by the 5-bit code that tops the col-
umn in which the encoded AC response is found. This matrix allows for correction for all single bit er-
rors and a number of two bit errors within the AC response.
3.4.3.3 Number Decoding (Receiver)
It has been observed anecdotally that receivers, when asked to perform analytical tasks on their own data,
are not accurate. To test this hypothesis, the five questions answered by the receivers for each trial were
translated into their own 5-bit assessment of the target. This was used to access the decoding matrix.
4. Results
4.1 Rank-Ordering
The rank-order method of analysis was used to determine the level of AC functioning for each receiver in
this study. The results can be seen in Table 11 below. Because the target was the same for all receivers in a
single trial, we did not compute statistics across receivers. In this way, we avoided a stacking problem.
Sum-of-ranks and mean-of-ranks statistics were computed for the eight trials for each receiver. We calcu-
lated the p-values and examined the magnitude of the effect sizes on a receiver-by-receiver basis. No receiv-
er produced a significant p-value, while only one receiver (454) had an effect size larger than 0.20.
In Table 11, ER is the sum-of-ranks, R is the average rank, and the p-value is computed from the sum-of-
ranks distribution. The effect size is shown for comparison.
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Table 11.
Statistics for the Sum-of-Ranks
Receiver ID
ER
R
p-value
Effect Size
009
21
2.625
0.6797
-0.1118
083
25
3.125
0.9597
-0.5590
372
20
2.500
0.5617
0
389
19
2.375
0.4383
0.1118
454
18
2.250
0.3203
0.2236
In addition, the number of direct hits (i.e., first place ranks) were computed for each receiver and the
binomial distribution was used to compute p-values and effect sizes from this perspective.
In Table 12, h is the number of first place ranks computed for each receiver.
Table 12.
Statistics for First Place Ranks
Receiver ID
h
p-value
009
1
0.900
083
0
1.000
372
2
0.633
389
1
0.900
454
2
0.633
4.2 Number Decoding
The number decoding method of analysis was used to test two hypotheses:
. A two-by-five, error correcting block code can be used to improve the detection of AC.
. Receivers who are asked to perform analytical tasks on their own data are not as accurate as an inde-
pendent analyst.
The results of decoding by the receiver are shown in Table 13. The number of direct hits (i.e., event
probability of 0.25) is shown as h. The p-value is computed from the exact binomial distribution.
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Table 13.
Receiver First Place Ranks
Receiver ID
h
p-value
009
2
0.633
083
3
0.322
372
3
0.322
389
2
0.633
454
3
0.322
The results of decoding by the analyst are shown in Table 14. The number of direct hits (i.e., event prob-
ability of 0.25) is also shown as h. The p-value is computed from the exact binomial distribution.
Table 14.
Analyst First Place Ranks
Receiver ID
h
p-value
009
1
0.900
083
1
0.900
372
2
0.633
389
2
0.633
454
3
0.322
Z-scores were computed for each of the p-values in Tables 13 and 14 using an inverse normal distribu-
tion, and they were combined in each table by Stouffer's-z (i.e., -0.317 and -1.243, respectively). The z
of the difference is 1.10, which corresponds to an effect size of 0.493. While neither receiver nor analyst
produced significant matches in the block coding analysis, the receivers appeared to be better at asses-
sing their internal responses than were third-party analysts. The number of trials is small and, as we
note below, the study had difficulties; therefore, we urge caution in interpreting the results.
5. Discussions and Conclusions
The primary consideration in this pilot study was to determine if binary coding could enhance the detec-
tion of AC. Only one receiver, however, demonstrated an effect size larger than 0.20 (i.e., 0.22) for
evidence of an AC phenomena and no evidence of enhanced detection of AC was seen.
The following difficulties may have rendered the results inconclusive:
. Although the question sets were different for each target pack, the receivers reported that they attempted
to guess what the questions would be while producing individual AC responses. This may have reduced a
free-response AC trial to a forced-choice one, which is known to be significantly less robust.
. In an attempt to make the targets dichotomous within packs and at the same time interesting to view,
targets within the pool ranged in scale from a panoramic scene of a cityscape to a photograph of three
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chairs to an image of three geometric shapes, and thus possessed a large target-pool bandwidth.
Since receivers were told in advance that the targets could contain absolutely any material, they were
unable to censor their internal experiences, which may have resulted in enhanced intrinsic receiver
noise (see Section IV.5.3).
. Each encoding bit was linked to only one percept (e.g., the single target element of water). This exag-
gerated the importance of the chosen dichotomous elements. For example, if a receiver failed to
sense water in the target but managed to sense most other aspects of the target that were not part of
the bit structure, then the block coding was not particularly applicable.
. In an AC application, a fundamental imbalance exists in the bit structure. The block coding assumes
that binary zero is "assertive." That is, in AC when water is not indicated in the response, it is equiva-
lent to indicating the water is definitely not in the target. In AC experiments, however, unless a re-
ceiver specifies explicitly that water is not present, then the presence or absence is indeterminate.
Maybe water exists in the target but was not noticed or was unreported by the receiver. Similarly,
water may not exist in the target and a non-response is equivalent to an assertive no. These two cases
are, of course, indistinguishable. The net effect is to render the block coding invalid.
Because of these difficulties, we recommend that the experiment be repeated with the following im-
provements:
. Reduce the target-pool bandwidth by using the National Geographic static target pool, which has been
successful for many AC experiments.
. Reduce the sensitivity to single block encoding bits by incorporating a number of fuzzy-set elements
for each bit. Thus, each bit will not rely upon a single percept, but rather represent classes of different
percepts.
We anticipate that these improvements will allow for much stronger AC, and provide a more sensitive
test of whether binary error-correcting can be successfully applied to AC detection.
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VIII. SUBCONTRACTS
Under this current effort we let three subcontracts to address specific items in the SOW.
1. Edinburgh University
This section constitutes part of the final report for SOW item 6.2.3.2.
We subcontracted to the Psychology Department of Edinburgh University to construct an isolation
room, which was designed specifically for Ganzfeld studies. The room is now complete and pilot Ganz-
feld trials are being conducted.
As part of their statement of work, we specified that the sound attenuation characteristics of the Ganz-
feld isolation room must be measured. The Department of Building Engineering and Surveying of Her-
iot-Watt University was asked to conduct the appropriate measurements.
We find that the room is sufficiently physically isolated from the sender's location and the sound attenu-
ations is reasonable for Ganzfeld studies.
2. Psychophysical Research Laboratories (PRL)
This section constitutes the final report for SOW item 6.2.2.4, the remainder of item 6.2.3.2, and
item 6.3.2.2.
To assist in our ongoing effort to determine what variables might be important in AC experiments, we
subcontracted with Mr. Charles Honorton, the director of PRL, to improve an earlier meta-analysis of
the literature pertaining to characteristics of persons who might perform well in AC tasks. Specifically,
he found that good novice Ganzfeld performers reported personal experience with natural AC, partici-
pated in earlier AMP experiments, were involved with mental disciplines such as meditation, and ten-
ded toward the Intuition side of the Sensing/Intuition scale of Myers-Briggs Type Indicator. Honor-
ton's complete report can be found in Appendix B.
As part of our effort to understand the role of the sender in AC experiments, we asked Mr. Honorton to
conduct a meta-analysis of the Ganzfeld literature to determine if there were meaningful differences
between Ganzfeld studies with and without a sender. Unfortunately, there were insufficient numbers
of Ganzfeld experiments conducted in the clairvoyant mode (i.e., without a sender) to be able to ascer-
tain, from the published literature, the sender's role. Appendix C contains Mr. Honorton's detailed
meta-analysis of the available literature.
Because the results of the meta-analysis proved to be inconclusive, PRL was tasked to design a protocol
for a definitive Ganzfeld study to understand the role of the sender in such experiments. That protocol,
detailed in Appendix D, superimposes on the standard auto-Ganzfeld procedure an additional 4-state
sender condition. That is, the sender is either:
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(1) Blind to all aspects of the target material
(2) Shown only the audio content of the target material
(3) Shown only the video content of the target material
(4) Shown the audio and visual content of the target material
During a Ganzfeld trial, the experimenter and receiver will be blind to which of these conditions is
operative.
3. The Lucidity Institute
This section constitutes the final report for SOW item 6.2.4.1. The Lucidity Institute's final report,
which can be found in Appendix E, contains the complete details of the results of the study. We provide
our perspective on the experiment in this section.
3.1 Objective
The objective of this investigation was to determine if anomalous cognition can be observed during
a lucid dream.
3.2 Background
Dreams involving putative AC have been part of every human culture from the times of ancient Greece
to the present. The first serious attempt, however, to examine AC in dreams under controlled condi-
tions began under the direction of Montague Ullman, MD, in 1962 at the Community Mental Health
Center of the Maimonides Medical Center in Brooklyn, New York. The research of AC in dreams con-
tinued until 1972, when the dream protocol was abandoned in favor of a simpler and more rapid ap-
proach to the study of AC. Child has summarized and critiqued this body of research in the American
Psychologist.29
In these studies, individuals were asked to sleep in a laboratory and be monitored for brain activity and
eye movement. From these records, it was possible to tell when they were dreaming. Upon the onset of
rapid eye movement (REM), an experimenter notified a sender, who was isolated in a remote laborato-
ry, to begin attending to a randomly selected target. At the end of the REM period, the dreamer was
awakened and asked to report the dream content. This procedure was repeated throughout the night
using the same target material for each separate dream (e.g., up to ten). The assessment of the AC
content was accomplished through independent judges. As described by Child, significant evidence for
AC was observed under a variety of conditions.
The dreamers in these studies, however, were not necessarily focused upon the AC task. They slept as
usual and, when asked, reported their dream content. In our pilot study we focused the dreamer explic-
itly on the AC task using the methods of lucid dreaming.
A lucid dream is one during which the sleeper becomes consciously aware that the experience is a dream
as opposed to the waking state. LaBerge et al. (1981) have found that it is possible for dreamers to know
when they are dreaming and to signal the waking world through predetermined eye movements indicat-
ing their awareness.30 Using this ability, LaBerge et al. (1986 and 1988) conducted psychophysiological
studies to determine the differences between waking and dreaming from that perspective.31,32 They
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found that dreaming is similar to the waking state. Motor action is mostly inhibited from the brain stem
downward; however, the cerebral cortex appears not to "know" this.
In this preliminary pilot study, we used the skills developed by LaBerge to teach individuals to lucid
dream. Differing from the earlier AC dream studies, our dreamers were instructed to adopt a proactive
attitude to seek out and remember the AC target. In this way, we tried to determine the degree to which
lucid dreaming can facilitate the reception of AC material.
3.3 Approach
3.3.1 Receiver Selection
We used two specialized populations from which we drew receivers for this pilot experiment:
(1) Experienced dreamers from LaBerg's research subjects (three receivers)
(2) Receivers who have demonstrated significant ability in other AC studies (four receivers)
3.3.2 Target Selection
Targets were chosen randomly from the standard set of 100 National Geographic magazine photographs.
3.3.3 Trial Definition
A trial was defined as a successful lucid dream during which the target material was examined and later
transcribed in the waking state.
3.3.4 Lucid Dream Protocol
All receivers undertook two forms of training in lucid dreaming: (1) They completed a lucid dreaming
home-study course developed by the Lucidity Institute, and (2) they attended two weekend seminars,
one at the beginning and one at the end of a three-month pilot study. The first seminar, which was held
in December, 1991, introduced receivers to lucid dreaming skills and the use of the DreamLight™, a
lucid dream induction device. In previous studies, the DreamLight™ has been shown to enhance the
frequency of lucid dreaming. The DreamLight™ consists of a sleep mask equipped with lights and eye
movement sensors, which are attached to a small battery-operated computer. When the computer de-
tects the eye movements of dreaming (i.e., REM) sleep, it causes the lights in the mask to flash briefly
(i.e., either one or two flashes per second). The dreamer frequently incorporates the flashes into the
ongoing dream, and thus experiences a cue to indicate that he or she is dreaming. Receivers had access
to DreamLights™ during the duration of the study.
3.3.5 AC Baseline Measures
The three inexperienced receivers from the Lucidity Institute were asked to contribute eight AC trials in a
waking state in the Cognitive Sciences Laboratory as an AC baseline series. The targets for these series
were chosen at random from the standardized target set. Each trial was conducted as follows: After the
receiver and a monitor entered the AC laboratory (i.e., an office with a single desk and two chairs), an assis-
tant used a computer random number generator to select a target from the baseline target pool. Both the
receiver and the monitor were blind to this specific choice. At a pre-arranged time, the monitor encouraged
the receiver to draw and write impressions of the target material, which was located approximately 30 m
away. After approximately 15 minutes of casual questioning, the trial ended; the data were copied; the orig-
inals were secured; and the actual target was presented as feedback to the receiver.
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3.3.6 Protocol for a Lucid-Dream Trial
During this study, a lucid-dream trial for each receiver was conducted as follows:
(1) The receiver was given a sealed opaque envelope containing a target photograph chosen randomly
from a predetermined set of 100. The receiver placed the target envelope in the room in which he
or she was going to sleep.
(2) Using the DreamLight™, the receiver attempted, while dreaming, to open the envelope, memo-
rize its content, and awaken as soon as possible.
(3) In the waking state, the receiver wrote and drew his or her impressions in detail.
(4) During the next day, the unopened envelope and the response was mailed to the PI for analysis.
Upon receipt, the PI sent back a copy of the target photograph as feedback and an additional
sealed envelope for the next trial.
Traditional rank-ordering was the method of analysis. In addition, each trial was assessed using the post
hoc scoring method, which is shown in Table 3 on page 21.
3.4 Results and Discussion
A total of 21 trials were collected in this pilot study. Summed across receivers, we observed significant
evidence for AC (i.e., z = 1.69, p ≤ 0.046, effect size = 0.368). During the calibration series, one of
Lucidity Institute's receivers obtained evidence for AC (i.e., effect size = 0.265); however, the other two
receivers showed little overall evidence of AC. As is common in novice receivers, who may have innate
AC ability, the quality is highly variable. On those rare cases when a first place rank was assigned, the
quality scores were quite good. Because of the limited number of lucid dream trials, we were not able to
ascertain the degree to which the lucid dream state improves the quality of AC; however, we are able to
say that it does not inhibit AC.
We are encouraged by these results for so few trials and suggest that the experiment be repeated with
the following improvements:
. Conduct the lucid dreaming AC trials in the laboratory. During the pilot study, the receivers could
not reliably produce lucid dreams. This hit-and-miss approach can be markedly improved in the labo-
ratory. Receivers can be awakened at the end of a dream, which has been observed to be lucid by eye
signals, and queried about their experience. In addition, the setting of the laboratory is likely to be
more conducive for lucid dreaming.
. Provide immediate feedback at the end of the overnight session.
· Monitor various psychophysiological variables so that the lucid dream state can be more accurately
defined.
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IX. OTHER ACTIVITY
1. Correlations between AC and Geomagnetic Activity
This section comprises the final report for SOW item 6.2.2.3.
1.1 Background
Persinger, Tart, Krippner, and others have reported an association between AC performance and in-
dices of geomagnetic field (GMF) fluctuations. This work has shown that both anecdotal reports of
spontaneous AC, as well as higher-scoring laboratory AC trials, tend to occur at times of relatively low
GMF activity. The published evidence is not entirely compelling. The anecdotal AC data are contami-
nated to an unknown extent with confounding factors of reporting bias, timing errors, and the difficulty
of establishing the veracity of such reports post hoc. The retrospective studies of laboratory AC data,
while largely free of these problems, have demonstrated only small correlations to GMF indices. There
is, however, increasing interest in the possibility of biological effects of small amplitude magnetic field
variations. Recent work has shown that melatonin and serotinin levels are modulated by GMF activity
both in vivo and in vitro. Other research is exploring the physics of possible mechanisms whereby low-
amplitude magnetic field variations could interact with cells.
1.2 Anomalous Cognition
To investigate the relationship between scores in laboratory AC experiments and GMF fluctuations, we are
combining various experimental databases. Currently, we have assembled a database of approximately
1,000 free-response AC trials from several laboratories. There is a very small (i.e., Q = - 0.05, p ≤ 0.09)
correlation between trial scores and GMF fluctuations in the expected direction in this database. The cor-
relation, however, is much larger (i.e., Q = - 0.40) in those experiments where significant AC was
demonstrated.
1.3 Epilepsy
We may discover more about the impact of GMF fluctuations on AC performance by research on other
behaviors that are modulated by very low frequency magnetic fields. Some literature suggests a connec-
tion between idopathic and epileptic seizures and GMF fluctuations. Currently, we have assembled a
database of approximately 4,000 seizures and seizure-related mortalities. Preliminary analysis of a sub-
set of this database suggests that both seizures and mortalities associated with seizures are weakly cor-
related with elevated GMF noise levels. GMF noise might be depressing the melatonin level, resulting
in an increased probability of seizure. We have submitted a paper, which describes the results of the
GMF/epilepsy investigation, for publication in the British medical journal, The Lancet. This paper may
be found in Appendix F.
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2. Assessment of Theoretical Constructs
This section comprises the final report for SOW item 6.2.3.1.
One senior research physicist has been identified who is anxious to explore thermodynamic and general
relativistic models to formulate hypotheses for the mechanism of AC.
The data from AMP experiments have begun to suggest theoretical approaches toward understanding
the underlying principles for the phenomena. Most of the previous modeling has been quantum me-
chanical,33,34 metaphoric,35 or behavioral36 and generally has not led to testable hypotheses. One heu-
ristic model does suggest experiments, but it does not provide fundamental insight into the mechanisms
of AC.37 We suggest a variety of different theoretical approaches that are either dictated by the
strength of the AC data or are strongly suggested by fundamental concepts.
Specifically, we suggest that theoretical approaches from among the following should be examined to
determine those that are most likely to provide testable hypotheses (i.e., new protocols or experiments)
and lead us toward a theoretical understanding of the physics of AC.
The Einstein, Poldasky, Rosen (EPR) Paradox. The paradox suggests possible information transport dur-
ing the collapse of a wave function. The paradox arises naturally when considering two-particle correlations
and the effect of measuring the state of one particle, which gives rise to unambiguous knowledge of the state
of the correlated particle. While no one any longer questions the validity of the predictions of quantum
mechanics for correlated systems, the fact of that validity has caused a philosophical revolution. There is no
underlying reality no absolute reality. There is only reality as defined by measurements made by an ob-
server.
This approach is suggested because AC experiments appear to show "correlation" of separated
events. While it is doubtful that AC is quantum mechanical, nonetheless the EPR formalism might provide
conceptual insight into possible AC mechanisms.
Thermodynamic Entropy. For nearly two hundred years, scientists have taken the position that the en-
tropy of a closed system can never decrease with time and that, on the scale of the universe, entropy
always increases with increasing time. Recently, Steven Hawking has raised the possibility that macro-
scopic time or psychological time, the time that we perceive, is actually determined by the change of
entropy.38 The study of classical thermodynamic entropy appears likely to be the most productive
based upon the results of a recent Shannon entropy experiment39 and on the extensive evidence for
so-called precognition-AC of targets before they have been determined.40
General Relativity. Matt Visser's paper on traversable wormholes suggests that it is physically possible
to transport energy (and, therefore, information) between remote space-time points without traversing
the classical distance between the space-time events.41 General relativity, therefore, is a candidate for a
theoretical basis for AC.
Tachyons. It is possible to describe mathematically a fully consistent universe in which everything
moves faster than the speed of light. The particles inhabiting such a universe are named tachyons while,
in contrast, the particles with which we are familiar are named tardyons. The important fact is that nei-
ther particle can ever travel at the speed of light. Photons, of course, are common to both universes.
Moreover, this is a non-quantum mechanical description. Theoretical understanding of tachyons may
assist in defining an energy transfer mechanism for AC.
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Fuzzy Set Attributes and Levels
Attribute
Description
Level
1
Fort
10
2
Castle
10
3
Palace
10
4
Church, Religious
10
5
Mosque
10
6
Pagoda
10
7
Coliseum, Stadium, Arena
10
8
Bridge
9
9
Dam, Lock, Spillway
9
10
Boats, Barges
9
11
Pier, Jetty
12
Motorized Vehicles
13
Column
9
14
Spire, Minaret, Tower
9
15
Fountain
9
16
Fence
17
Arch
18
Wall
19
Monument
20
Roads
21
Port, Harbor
22
Oasis
7
23
Agricultural Fields
£
7
24
Industrial
7
25
Recreational
7
26
Religious
7
27
Mechanical
7
28
Technical
7
29
Agricultural
7
30
Commercial
7
31
Wilderness
7
32
Urban
7
33
Rural, Pastoral
7
131
Historical/Archaeological
7
34
Ruins, Incomplete Buildings
6
aaaaor
9
9
9
8
7
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Fuzzy Set Attributes and Levels (continued)
Attribute
Description
Level
35
Mesa, Plateau
6
36
Waterfall
6
37
Glacier
6
38
Canal, Manmade Waterway
6
39
Desert
6
40
Forest
6
41
Jungle
6
42
Marsh, Swamp
6
43
Isolated Settlement
5
44
Town, Village
5
45
City
5
46
Single Peak
5
47
Hills, Slopes, Bumps, Mounds
5
48
Mountains
5
49
Cliffs
5
50
Plain, Delta
5
51
Valley, Gully, Cleft
5
52
Canyon
5
53
Crater, Regular Depression
5
54
Unbounded Large Expanse Water
5
55
Completely Bounded Water
5
56
Partially Bounded Water
5
57
Island
5
58
River, Stream, Creek
5
59
Coastline
5
60
Vegetation, Trees
5
61
Yellow
4
62
Orange
4
63
Red
4
64
Blue
4
65
Green
4
66
Purple, Pink
4
67
Brown, Beige
4
68
Black
4
69
White
4
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Fuzzy Set Attributes and Levels (continued)
Attribute
Description
Level
70
Grey
4
71
Shiny, Reflective
4
72
Gold
4
73
Silver
4
74
Chrome
4
75
Copper
4
76
Obscured, Fuzzy, Dim, Smoky
4
77
Cloudy, Foggy, Misty
4
78
Old
4
79
Weathered, Eroded, Incomplete
4
80
Smooth
4
81
Fuzzy
4
82
Grainy, Sandy, Crumbly
4
83
Rocky, Ragged, Rubbled, Rough
4
84
Striated
4
85
Hot
4
86
Cold, Snow, Ice
4
87
Humid
4
88
Dry, Arid
4
89
Flowing
4
90
Other Implied Movement
4
91
Congested, Cluttered, Busy
4
92
Serene, Peaceful, Unhurried
4
93
Closed In, Claustrophobic
4
94
Open, Spacious, Vast
4
95
Ordered, aligned
4
96
Disordered, Jumbled, Unaligned
4
97
Buildings, Structures
3
98
Rise, Vertical Rise, Slope
3
99
Flat
3
100
Light/Dark Areas
3
101
Boundaries
3
102
Land/Water Interface
3
103
Land/Sky Interface
3
104
Single Predominant Feature
3
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Fuzzy Set Attributes and Levels (continued)
Attribute
Description
Level
105
Odd Juxtaposition, Surprising
3
106
Manmade, Altered
3
107
Natural
3
108
Rectangle, Square, Box
2
109
Triangle, Pyramid, Trapezoid
2
110
Other Polygonal, Hexagon
2
111
Cross-Hatch, Grid
2
112
Circle, Oval, Sphere
2
113
Torus
2
114
Cylinder
2
115
Cone
2
116
Semicircle, Dome, Hemisphere
2
117
Irregular Forms
2
118
Repeat Motif
2
119
Stepped
1
120
Parallel Lines
1
121
Vertical Lines
1
122
Horizontal Lines
1
123
Diagonal Lines
1
124
V-Shape
1
125
Inverted V-Shape
1
126
Other Angles
1
127
Arc, Curve
1
128
Wave Form
1
129
Spiral
1
130
Meandering Curve
1
.
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Physical Interpretation of Potentials. Classical mechanics and, for the most part, quantum mechanics
have treated potentials as convenient mathematical descriptions for which there are no physical counter-
part. Recent experiments have shown, however, that a potential can affect a particle even when there is no
corresponding force present. If potentials could be made to propagate, then they could be candidates for an
energy transfer mechanism for AC.
3. Anomalous Perturbation
This section constitutes the final report on SOW item 6.2.5.
At the sponsor's request, we provided two receivers to participate in an informal and exploratory anom-
alous perturbation experiment. The target system was a special E&M wave device; there was no partic-
ular protocol; and we report, in the form of a laboratory anecdote, that a sufficiently large number of
unexpected events occurred to suggest that additional and more formal data must be collected.
4. Fuzzy Set Analysis
This section constitutes the final report on SOW item 6.3.2.1.
4.1 Background
The elements in our fuzzy set representation of our target pool are structured in levels, ranging from the
relatively abstract, information poor (such as vertical lines-level 1), to the relatively complex, informa-
tion rich (such as churches-level 10). The current system is structured into seven primary and three
secondary levels of descriptors; the main intent of this structure is to serve as a heuristic device for guid-
ing the analyst into making judicious concrete descriptor assignments based on rather abstract com-
mentary. The determination as to which descriptors belonged on which level was made after considera-
tion of two primary factors: (1) the apparent ability of receivers' to resolve certain features, coupled
with (2) the amount of pure information thought to be contained in any given descriptor. Some of these
"factor one" determinations were based on observations of analysts and monitors in the course of either
analyzing or conducting numerous AC experiments and on subjective lore; some were determined em-
pirically from post hoc analyses of receivers' abilities to perceive various descriptor elements in previous
experiments.
The "factor two" determinations were made primarily by arranging the descriptors such that a descrip-
tor at any given level represents the sum of constituent descriptors at lower levels. The world is not a
very crisp place and not all of its elements are amenable to hierarchical structuring. Certain violations
of the "factor two" rule appear, therefore, throughout the proposed levels. Some of the more glaring
violations were largely driven by the "factor one" determinations (i.e., the receivers' abilities to discern
certain elements) enumerated above.
Thus, the visual information content as described by our fuzzy-set encoding ranges from the specific and
detailed for level 10 to the unspecific and abstract for level 1. Please see Appendix A for a complete list
of fuzzy set elements and their associated levels.
4.2 Analysis
Using the data from the static target set in the target-dependency experiment (see Section IV), we cor-
related the post hoc scores and the blind ranks with the content in each of the fuzzy set levels. Figure 19
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shows this correlation only for those trials that demonstrated clear evidence for AC (i.e., scores ≥ 4 on
the post hoc scale shown in Table 3 on page 21). The blind ranking appeared to be most sensitive to the
elements in level 5. This is expected since level 5 contains complete visual elements, which are likely to
be those that allow differentiation among targets. For example, town, island, river, coastline, are repre-
sentative of the elements in this level. Most of the other positive correlations levels appear in the ab-
stract levels, which contain elements of texture, color, and ambience.
:
0.50
Correlation Coefficient (df = 26)
Blind Ranking
Post Hoc Scores
0.25
0.00
-0.25
-0.5
10
9
8
7
6
5
4
3
2
1
Fuzzy Set Coding Levels
---
Figure 19. Correlation: Levels of Visual Complexity with Post Hoc Ratings
and Blind Rankings for Post Hoc Scores Greater than Three
(i.e., evidence for AC)
1
The interpretation of the correlations for the post hoc scores is less clear. The single strong positive
correlation occurs with simple geometric elements in level 1. Since many AC responses consist of sim-
ple drawings, perhaps an analyst is drawn to these elements in the target while assigning scores. The
negative correlations for levels 2-4 imply that most of the incorrect aspects of the response appeared in
these levels. The elements in levels 2-4 include more complex geometries than in level 1 and more of
those elements allowed discrimination in blind ranking.
We also computed the correlation for all 100 trials regardless of post hoc rating. The results are shown in
Figure 20. One striking feature is the complete opposite correlation between blind ranks and post hoc
scores. For example, level 10, the most specific and detailed, showed strong positive correlation for post
hoc scores but a strong negative correlation for blind ranking. Thus, it appears that analysts were most
sensitive to detailed visual elements in assigning post hoc scores, but were more likely to find these ele-
ments in decoy targets in blind ranking. This is precisely what is expected since a positive correlation
with post hoc scores would include low scores for specifics that don't match.
Another striking feature in Figure 20 is that level 5 contains the elements that are best for discrimina-
tion in blind ranking. This same correlation was seen using only the data that indicated strong post hoc
evidence for AC.
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0.50
Correlation Coefficient (df = 98)
Blind Ranking
Post Hoc Scores
0.25
0.00
1-0.25
-0.5
10
9
8
7 6 5
4 3 2 1
Fuzzy Set Coding Levels
Figure 20. Correlation: Levels of Visual Complexity with Post Hoc Ratings
and Blind Rankings for all Post Hoc Scores
4.3 Conclusion
Generally, elements that assist in a post hoc analysis are not the same elements that assist in blind rank-
ing. Fuzzy set elements, which are generally image specific, are most sensitive in blind rank analysis, but
specific visual elements are best for post hoc. These conclusions are based upon on set of 100 AC trials.
It is currently unknown the degree to which they will generalize.
5. Empirical Training Overview
This section constitutes the final report on SOW item 6.3.3.1. The following discussion has been pri-
marily provided by Professor D. Bem of the Psychology department of Cornell University.
5.1 Overview
We have examined a stimulus-response training method, which has been in use for a number of years. 42
Generally, this method assumes that internal visual imagery is a strong source of noise, at least for be-
ginning receivers. The training method is highly focused on the structure of the response as an attempt
to limit imagery. Not unlike a word association test, a receiver is asked to respond, as quickly as pos-
sible, to a stimulus such as the word "target." By refraining from a long introspection time, it is hoped
that internal imagery does not have time to interfere with the AC "signal."
The training method requires that the structure of the response change as a student advances through a
series of discrete stages. The stages represent access to increasing information about the target material.
For example, Stage I consists primarily of large scale generalities about a site, such as mountains and cities,
whereas Stage VI consists of specific analytic details involving relationships among the response elements.
5.2 Analysis
Most of the concepts outlined in this training method have not been individually tested under laboratory
conditions. The method, however, has been used "successfully" in that individuals who have been trained by
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it produce stable and robust evidence of an AC ability (i.e., effect sizes of the order of 0.4). At this time, it is
difficult to ascertain what elements, if any, are responsible for this observation.
Successful AC involves two basic steps:
(1) Obtaining the information
(2) "Transducing" or communicating the information so that it can be evaluated or acted upon
Only the first step involves AC, and we know very little about its intrinsic properties. In contrast, we
have a number of reasonable hypotheses about what facilitates or hinders the second step. In fact, virtu-
ally all the specific procedures in this training method are directed toward facilitating this second step.
This training method has naturally evolved over the years so that the method has been optimized by the
performance of a particular set of "star" receivers. This group, however, is highly selected, quite small,
and may well be unrepresentative of a larger population of potentially successful receivers. As a result,
this method is probably too narrow in the sense that it may be excluding many potential receivers who
would be successful at obtaining AC information (i.e., step 1) but who cannot overcome a number of
arbitrary and unnecessary obstacles to their transducing it accurately (i.e., step 2).
For example, the "star" receivers may do better at transducing visually, by drawing, than individuals
who can communicate better verbally. The successes that have led us to give more weight to the draw-
ings than to the verbal material might be an artifact of the transducing styles of the "stars" and not an
inherent property of an AC ability.
The research on individual differences also appears to tap differences in transducing skills. For exam-
ple, meta-analysis shows that extroverts typically outperform introverts on specific AC tasks; however,
these tasks involved considerable interaction with an experimenter or a sender. Yet, in other AC tasks,
the opposite has been observed. Likely what is being observed is a preference style for a particular pro-
tocol that supports an individual's transducing proclivity. An ideal training method would recognize
these types of individual differences in reporting.
For training purposes, providing intermediate feedback is certainly problematical. The training meth-
odology calls for prescribed responses by a training monitor to various aspects of the student's response.
There is substantial evidence to suggest that this is counterproductive. In reviewing 345 studies, Rosen-
thal and Rubin have shown that interpersonal expectancy effects, under certain circumstances, are ex-
tremely robust in behavioral research. That is, we communicate our expectations and other informa-
tion to one another by non-verbal means, and, occasionally, this can be the primary mode of
communication.43 If the trainer is knowledgeable about the target material while in the training ses-
sion, the implication is that the student may be recognizing non-verbal clues rather than aspects of AC.
Minimally, what exactly the student has learned is indeterminate.
5.3 Suggested Modifications
In this section we describe a possible way to expand this training methodology, while still retaining most
of the current procedure. In particular, we emphasize the stimulus-response format to avoid noise. The
following is an outline of the suggested modification.
(1) Use the word "target" as a prompt, and let the receiver sketch anything that comes to mind. The
receiver should have the opportunity to "pass" or draw nothing. In addition he or she should be
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0.50
Correlation Coefficient (df = 98)
Blind Ranking
Post Hoc Scores
0.25
0.00
9-0.25
-0.5
10
9 8 7
6
5
4
3
2
1
Fuzzy Set Coding Levels
Figure 20. Correlation: Levels of Visual Complexity with Post Hoc Ratings
and Blind Rankings for all Post Hoc Scores
4.3 Conclusion
Generally, elements that assist in a post hoc analysis are not the same elements that assist in blind rank-
ing. Fuzzy set elements, which are generally image specific, are most sensitive in blind rank analysis, but
specific visual elements are best for post hoc. These conclusions are based upon on set of 100 AC trials.
It is currently unknown the degree to which they will generalize.
5. Empirical Training Overview
This section constitutes the final report on SOW item 6.3.3.1. The following discussion has been pri-
marily provided by Professor D. Bem of the Psychology department of Cornell University.
5.1 Overview
We have examined a stimulus-response training method, which has been in use for a number of years. 42
Generally, this method assumes that internal visual imagery is a strong source of noise, at least for be-
ginning receivers. The training method is highly focused on the structure of the response as an attempt
to limit imagery. Not unlike a word association test, a receiver is asked to respond, as quickly as pos-
sible, to a stimulus such as the word "target." By refraining from a long introspection time, it is hoped
that internal imagery does not have time to interfere with the AC "signal."
The training method requires that the structure of the response change as a student advances through a
series of discrete stages. The stages represent access to increasing information about the target material.
For example, Stage I consists primarily of large scale generalities about a site, such as mountains and cities,
whereas Stage VI consists of specific analytic details involving relationships among the response elements.
5.2 Analysis
Most of the concepts outlined in this training method have not been individually tested under laboratory
conditions. The method, however, has been used "successfully" in that individuals who have been trained by
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it produce stable and robust evidence of an AC ability (i.e., effect sizes of the order of 0.4). At this time, it is
difficult to ascertain what elements, if any, are responsible for this observation.
Successful AC involves two basic steps:
(1) Obtaining the information
(2) "Transducing" or communicating the information so that it can be evaluated or acted upon
Only the first step involves AC, and we know very little about its intrinsic properties. In contrast, we
have a number of reasonable hypotheses about what facilitates or hinders the second step. In fact, virtu-
ally all the specific procedures in this training method are directed toward facilitating this second step.
This training method has naturally evolved over the years so that the method has been optimized by the
performance of a particular set of "star" receivers. This group, however, is highly selected, quite small,
and may well be unrepresentative of a larger population of potentially successful receivers. As a result,
this method is probably too narrow in the sense that it may be excluding many potential receivers who
would be successful at obtaining AC information (i.e., step 1) but who cannot overcome a number of
arbitrary and unnecessary obstacles to their transducing it accurately (i.e., step 2).
1
V
For example, the "star" receivers may do better at transducing visually, by drawing, than individuals
who can communicate better verbally. The successes that have led us to give more weight to the draw-
ings than to the verbal material might be an artifact of the transducing styles of the "stars" and not an
inherent property of an AC ability.
The research on individual differences also appears to tap differences in transducing skills. For exam-
ple, meta-analysis shows that extroverts typically outperform introverts on specific AC tasks; however,
these tasks involved considerable interaction with an experimenter or a sender. Yet, in other AC tasks,
the opposite has been observed. Likely what is being observed is a preference style for a particular pro-
tocol that supports an individual's transducing proclivity. An ideal training method would recognize
these types of individual differences in reporting.
For training purposes, providing intermediate feedback is certainly problematical. The training meth-
odology calls for prescribed responses by a training monitor to various aspects of the student's response.
There is substantial evidence to suggest that this is counterproductive. In reviewing 345 studies, Rosen-
thal and Rubin have shown that interpersonal expectancy effects, under certain circumstances, are ex-
tremely robust in behavioral research. That is, we communicate our expectations and other informa-
tion to one another by non-verbal means, and, occasionally, this can be the primary mode of
communication.43 If the trainer is knowledgeable about the target material while in the training ses-
sion, the implication is that the student may be recognizing non-verbal clues rather than aspects of AC.
Minimally, what exactly the student has learned is indeterminate.
5.3 Suggested Modifications
In this section we describe a possible way to expand this training methodology, while still retaining most
of the current procedure. In particular, we emphasize the stimulus-response format to avoid noise. The
following is an outline of the suggested modification.
(1) Use the word "target" as a prompt, and let the receiver sketch anything that comes to mind. The
receiver should have the opportunity to "pass" or draw nothing. In addition he or she should be
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explicitly told that it is not considered undesirable to pass, but it simply reflects a stylistic prefer-
ence for ways of communicating.
(2) The receiver now generates any adjectives or terms that occur spontaneously. Passes are also allowed.
(3) The receiver is now prompted with a set of Semantic Differential Scales-bipolar dimensions-
and asked to respond verbally in a stimulus-response fashion. For example, the trainer might say
"hot-cold" and the viewer might respond with "warm, cold, stiff, sauna, or pass." In other words,
the trainer gives the dimension and the receiver gives any response at all.
(4) The receiver may now supply any additional dimension and/or terms that occur to him or her. This
is essentially a repeat of step 1, recognizing that step 3 may have promoted new material.
(5) The session ends after a number of repeats of steps 1-4 and with a final integration of drawn (and)
verbal material.
5.4 Discussion
Note that this sequence goes from unstructured to structured responses, with no pressure to use any proce-
dure that seems uncomfortable. For example, if the receiver feels distracted by having to use pen and paper,
he or she should have the option not to do so; the monitor could tape-record the session, for example.
Step 3 is modeled on word association techniques. There are several possibilities for the scales. We could:
· Use our visual fuzzy set elements.
· Select dimensions from previous work on the Semantic Differential.
· Conduct a preliminary study on a subset of targets that are displayed to receivers, and allow the re-
ceivers to generate dimensions that are tailored specifically by them for those targets.
. Let each receiver construct his or her own impressionistic vocabulary by serving in a session described
above. Then present these individualized dimensions as stimuli in the subsequent AC sessions.
The dimension of the presented stimuli should not be confined to physical/visual features of targets but
should range widely over affective and impressionistic dimensions as well (e.g., kind-cruel, soft-hard, good-
bad). The Semantic Differential was originally developed to tap affective or connotative meaning, and factor
analyses uncovered three orthoginal dimensions that appear to have cross-cultural universality:
(1) An evaluative dimension (e.g., good-bad)
(2) An activity dimension (e.g., active-passive)
(3) A potency dimension (e.g., strong-weak)
An effective procedure should use scales from all three factors.
It is possible to use prompts other than those of bipolar dimension. For example, the prompt could be
the name of a sensory modality like smell or odor to which a receiver could respond "dank, bakery, acid-
ic, or pass." Or the prompt could be mood or emotion and the response could be "sad, tranquil, agitated,
or pass." Cross-cultural research reveals that six dimensions of affect appear to be universal: happy,
sad, anger, fear, disgust, and surprise. These might be pertinent for some target pools.
-
We have stressed cross-cultural dimensions here to approach AC from the viewpoint of evolution. If
some kind of AC is functionally adaptive for the species, what would its properties be? Affectively rele-
vant information is the most likely to be accessed in AC-related ways, and universal categories of affec-
tive description have the best chance for transducing such information. In contrast, we speculate that
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L
the vocabulary for describing visually descriptive features of locations is much more derivative and fur-
ther removed from primordial experience.
Once a descriptive set of dimensions has been decided upon for a particular target set, preliminary sessions
with student receivers can be used to train them in the use of the dimensions. This can be accomplished by
using practice targets on which there is consensus on the applicability of the dimensions to each photograph.
If dimensions are ats tailored to each individual, then these preliminary sessions are those in which the
student receiver constructs his or her dimensions rather than learning a universal set.
5.5 Conclusion
We have analyzed one existing AC training methodology and have provided a schematic outline of mod-
ifications that might improve the method by generalizing it. We emphasize that this suggestion is in our
5-year research plan, which was developed under this program. It is important to realize that many dif-
ferent approaches should be explored. The one presented here represents only a modest modification
of the existing method.
6. A Potential New Training Method
This section constitutes the final report on SOW item 6.3.3.2.
We have designed a potential new training methodology that is based upon subliminal perception.
6.1 Background
Preconscious processing of sensory information may be responsible for much of the perceptual in-
formation that reaches conscious awareness. A trivial example is the processing of the left and right
two-dimensional retinal images into a single three-dimensional cyclopean percept. Because the eyes
view the world from different viewpoints, the two retinal images are not superimposable, and frequent-
ly contain different information about the external environment. In those abnormal instances where
both retinal images reach conscious awareness, the receiver perceives diplopic images of the external
environment, that is, he has double vision. The observations that the cyclopean image is not retinotopic
for either eye and that the cyclopean image is created without conscious effort are strong support for
preconscious processing of sensory information.
A more significant example is provided by the Poetzl effect,44 in which an unperceived stimulus is capa-
ble of evoking subsequent memories of having perceived the stimulus. Very often, the memories are
distorted, but contain spatial, chromatic, textural, temporal, and contextual elements of the previously
unperceived stimulus. This effect provides evidence of preconscious processing of not only the unper-
ceived stimulus, but of its primitives in several domains, such as color.
The most compelling evidence for preconscious processing is provided by a body of research commonly
known as blindsight.45 Blindsight can occur when anatomical brain structures that are crucial to visual
perception, such as the striatal cortex, have been destroyed, but the remainder of the visual system is
intact. Under these conditions, any visual stimulus that falls on an area of the retina that projects to the
destroyed area of the striate cortex cannot reach perceptual awareness. A person with this condition is
blind in this area of the visual field. A large body of evidence, however, demonstrates that persons with
this condition can respond to visual stimuli, even though they cannot see them. Furthermore, persons
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with blindsight can make visual discriminations, for example, of form and color, without perceiving the
form or color of the stimuli. Blindsight, then, is a compelling example of preconscious, or perhaps extra-
conscious processing.
Other evidence of preconscious processing can be found by comparing the sensory and perceptual
thresholds. The sensory threshold can be determined physiologically by measuring the amplitude of a
stimulus that elicits an identifiable signal in a receptor system, for example, a change in the firing rate of
a sensory neuron. The perceptual threshold can be defined as that amplitude of the same stimulus that
elicits a response indicating that the stimulus has been detected. It is a well-known phenomenon that
the sensory and perceptual threshold can differ markedly.46,47 Thus, between the sensory and per-
ceptual thresholds, the receiver is processing information that is below the perceptual threshold, that is,
preconscious processing.
The question of interest here is whether the perceptual threshold can be reduced so that it is closer to
the physiological threshold. Several studies suggest conditions under which the perceptual threshold
can be lowered to more closely approximate the sensory threshold. For example, changing the emotion-
al content of the stimuli or the emotional state of the receiver has been shown to affect the perceptual
thresholds for subliminal stimuli.48,49
Essentially, reducing the emotional state of the receiver or ele-
vating the emotional content of the stimulus reduces the perceptual threshold.
The question can now be refined to ask whether the perceptual threshold can be reduced through training.
Couched in terms of signal detection theory, the question can be posed: Can the receiver's threshold be
changed through training so that the receiver can detect a signal at a lower signal-to-noise ratio?
-
---
-
Here, again, the answer is yes. Detection thresholds have been found to respond to training protocols
that use feedback on repeated trials to elevate sensitivity to previously unperceived visual cues.50,51,52
We suggest that the detection threshold be changed through a program of repeated feedback.
6.2 A Suggested Experiment
This suggested experiment has a two-fold purpose. The first is to assess the effects of training protocols
on the detection thresholds for subliminal visual stimuli. The second is to examine whether those re-
ceivers whose thresholds were lowered by training perform better on AC tasks than receivers who have
not been through the training. By using threshold-lowering training protocols, we will attempt to in-
crease the sensitivity of receivers to subliminal visual stimuli so that following training, stimuli that had
been subliminal will be supraliminal. We will then determine whether there is a parallel increase in sen-
sitivity to AC stimuli.
1
Specifically, we suggest that receivers first be randomly assigned to a subliminal-training group and a
sham-training group. No receiver will be informed of his or her status until both the training and re-
mote-viewing portions of the study have been completed.
Each receiver in both groups will be shown a series of target images that are presented tachistoscopically for
approximately 10 milliseconds, alternating with a 5-second presentation of a masking stimulus. All target
images will be below the receiver's detection threshold, that is, they will be subliminal. Interspersed ran-
domly among the subliminal stimuli will be an equal number of blank trials in which no target image is pres-
ented during the 10-millisecond presentation.
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Immediately following each presentation of either the blank or target stimulus, the receiver will re-
spond by pressing a button indicating either that he was aware that a target was presented or that he was
unaware. Essentially, the receiver's task will be to report whether a target was presented. After each
response, the receiver will receive feedback about whether his response was correct or incorrect. The
experimental paradigm is shown in Figure 21.
Stimulus
subliminal
stimulus
Internals
awareness
no
awareness
Response
yes
no
no
yes
1
Feedback
correct
incorrect
Figure 21. Experimental Paradigm for Training.
Receivers in the subliminal-training group will receive truthful feedback about their performance, whereas
receivers in the sham-training group will receive random feedback. Because all stimuli will be subliminal,
sham-training receivers should not be able to detect that the feedback is uncorrelated with the stimuli.
Feedback to the subliminal-training receivers is expected to reinforce the pathways identified by bold
arrows in Figure 21. The proportion of "yes" responses under blank-trials conditions (i.e., sham-train-
ing) will be used to estimate the guessing rate.
Several hundred trials will be run, and cumulative performance measures, in terms of percentage of
correct responses, will be calculated for each of the sham-trained and subliminally-trained receivers.
Receivers from both groups will participate in a blind study of remote-viewing performance.
!
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X. GLOSSARY
Not all the terms defined below are germane to this report, but they are included here for completeness.
In a typical anomalous mental phenomena (AMP) task, we define:
· Anomalous Cognition (AC)-A form of information transfer in which all known sensorial stimuli
are absent.
· Agent-An individual who attempts to influence a target system.
· Analyst-An individual who provides a quantitative measure of AC.
· Anomalous Perturbation (AP)-A form of interaction with matter in which all known physical mech-
anisms are absent.
· Feedback-After a response has been secured, information about the intended target is displayed to
the receiver.
· Monitor-An individual who monitors an AC session to facilitate data collection.
· Protocol-A template for conducting a structured data collection session.
· Receiver-An individual who attempts to perceive and report information about a target.
. Response-Material that is produced during an AC session in response to the intended target.
· Sender/Beacon-An individual who, while receiving direct sensorial stimuli from an intended target,
acts as a putative transmitter to the receiver.
. Session-A time period during which AC data are collected.
. Specialty-A given receiver's ability to be particularly successful with a given class of targets (e.g.,
people as opposed to buildings).
. Target-An item that is the focus of an AMP task (e.g., person, place, thing, event).
. Target Designation-A method by which a specific target, against the backdrop of all other possible
targets, is identified to the receiver (e.g., geographical coordinates).
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REFERENCES
M
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17. E. C. May, R. Targ, and H. E. Puthoff, "Possible EEG Correlates to Remote Stimuli Under
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27. R. Targ, H. E. Puthoff, and E. C. May, "State of the Art in Remote Viewing Studies at SRI," 1977
Proceedings of the International Conference of Cybernetics and Society, pp. 519-529 (1977).
28. E. C. May, B. S. Humphrey, and C. Mathews, "A Figure of Merit Analysis for Free1-Response
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New Directions for Methodology of Social and Behavioral Sciences: Quantitative Assessment of
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1
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APPENDIX A
Target Elements for the Fuzzy Set Representation of AC Targets
-
=
?
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APPENDIX B
The Ganzfeld Novice: Four Predictors of Initial ESP Performance
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The Ganzfeld Novice:
Four Predictors of Initial ESP Performance
Charles Honorton
University of Edinburgh
Abstract: This report updates earlier studies examining characteristics of successful
novice ganzfeld participants. A new study comprising Novice Series 103-105 in the PRL
automated ganzfeld study (Honorton, Berger, Varvoglis, Quant, Derr, Schechter, &
Ferrari, 1990) is compared with a previous PRL study (Honorton & Schechter, 1987)
and an independent study reported by the FRNM research team (Broughton,
Kanthamani, & Khilji, in press). ESP ganzfeld performance is examined in relation to
four predictors: reported personal psi experiences, Myers-Briggs Feeling/Perception,
prior (nonganzfeld) psi testing, and involvement with mental disciplines such as
meditiation.
CPYRGHT
One of the goals of the PRL automated ganzfeld
research was to identify characteristics associated
with successful ESP ganzfeld performance by
previously inexperienced participants (novices).
Two hundred and six participants each contributed
to one of five novice series in the PRL automated
ganzfeld project. (See Honorton, Berger,
Varvoglis, Quant, Derr, Schechter, & Ferrari
[1990] for details of experimental procedures and
overall results.) Most participants completed Form
F of the Myers-Briggs Type Indicator (MBTI;
Briggs & Myers, 1957) and a 55-item demo-
graphic survey (Participant Information Form,
PIF).
Three previous reports have already described
aspects of the PRL-novice research. The relation-
ship between novice ESP ganzfeld performance
and extraversion was presented by Honorton,
Ferrari, & Bem (in press). Schlitz & Honorton
(1992) described a subset of the PRL novice data
involving performing artists from The Juilliard
School. At the 1986 PA Convention, Honorton and
Schechter (1987) presented an exploratory analysis
of performance correlates for the first two PRL
novice series (Series 101-102; hereafter designated
PRL-1), suggesting that initial ganzfeld ESP
performance was positively and significantly
related to self-reports of personal psi experiences,
Feeling/Perception (FP) preferences on the MBTI,
and prior participation in nonganzfeld psi
experiments. A positive but nonsignificant
tendency for better performance among partici-
pants reporting involvement with mental
disciplines such as meditation was also found.
Broughton, Kanthamani, & Khilji (in press)
successfully replicated the ESP/FP finding in an
independent study at FRNM. In this paper, the
PRL-1 findings will be compared with those in the
later PRL novices series (Series 103-105; hereafter
designated PRL-2) and the FRNM series to
estimate the overall magnitude and consistency of
the four predictors.
Following presentation of the Honorton &
Schechter report, an effort was made to obtain
Myers-Briggs data from PRL-1 participants who
had not originally taken the MBTI, and ten
participants kindly cooperated. Their data are
included in the PRL-1 totals in this report. The
PRL-1 findings summarized in this paper also
reflect corrections for a number of data entry
errors in the Honorton & Schechter (1987) report
that were discovered during a data audit of the
entire PRL automated ganzfeld database prior to
publication of Honorton, et al., (1990).
The PRL novices included 121 women and 85
men (total N = 206). PIF data was available for
195 and MBTI data was available for 190 subjects.
As can be seen from Table 1, these participants
1
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CPYRGHT
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2
Ganzfeld Novices
Table 1. Descriptive Statistics for PRL Novices
Age
Formal
Education.
(years)
.. ..
EI
SN
TF
JP
Belief in
Psi (1-7)
Reported Psi Prior Psi Testing
Experiences (Not Ganzfeld)
(0-4)
Mean
36.63
15.42
101.51
127.92
103.78
110.67
6.22
2.16
N= 32
SD
12.29
2.02
25.15
17.64
22.75
26.41
0.99
1.16
Median
36
16
99
132
106
113
7
2
Table note: Scores on MBTI scales increase in the direction of the second letter (e.g., EI scores below 100 signify extraversion while those above 100 signify
introversion).
tended to be mature, moderately well educated,
and, perhaps most prominently, strong believers in
psi. Of the MBTI scales, only the SN
(Sensing/Intuition) MBTI Scale was unusual: PRL
novices tended strongly toward the Intuition side
of the scale. A recent reevaluation of the MBTI
scales in terms of the five-factor model of per-
sonality indicates that the SN scale is highly
correlated with openness to experience (McRae &
Costa, 1989). The two PRL studies differed
significantly on responses to four PIF items: PRL-
2 subjects were younger, reported fewer personal
psi experiences, a lower frequency of coincidences,
and, curiously, stronger belief in luck than those in
PRL-1. These differences, with the exception of
luck, are due to the Juilliard students in PRL-2.
The Juilliard students were much younger and
rated themselves significantly lower on belief in
psi and personal psi experiences than the PRL
population (Schlitz & Honorton, 1992, p. 91).
Differences Between PRL and FRNM Novices
PIF data were available for 108 of the 120
FRNM novices. The PRL and FRNM novices also
differed significantly in four areas. PRL novices
were significantly older (t = 7.15, 303 df, p < 10-6,
r = . 38) and had a significantly higher mean on
the MBTI SN Scale than their FRNM counterparts
(t = 2.09, 290 df, p = . 037, two-tailed). The
incidence of reported personal psi experiences was
significantly lower for the FRNM novices than for
their PRL counterparts (Overall-adjusted Fisher
exact p = . 0163, phi = . 12 [Overall, Rhoades, &
Starbuck, 1987]) as was involvement in mental
disciplines (Overall-adjusted Fisher exact p =
.00018, phi = . 20).
Psi Performance
Table 2 summarizes novice psi performance in
the three studies. (In this report, all p-values are
one-tailed unless otherwise noted. ESP hit rates
are tested using exact binomial probabilities with p
= . 25 and q = . 75. Z-scores, calculated from the
inverse normal function, are provided to facilitate
meta-analytic comparisons.)
Thirty percent of the PRL-1 novices correctly
identified their targets (N = 100, p = . 15, z = 1.04).
The effect size (Cohen's h; Cohen, 1977) was .11,
with a 95% confidence interval (CI) from 22% to
38%. In PRL-2, 35% of the novices were
successful (N = 106, p = . 015, z = 2.18, h = . 22,
95% CI from 27% to 43%). Hits were obtained by
28% of the FRNM novices (N = 120, p = . 23, z =
Table 2. Ganzfeld Novice ESP Performance in Two Laboratories
95% CI
N
% Hits
From
To
Effect
size (h)
Z
p
PRL-1
100
30
22
38
.11
1.04
.150
PRL-2
106
35
27
43
.22
2.18
.015
FRNM
120
28
21
36
.08
0.75
.23
Combined
326
31
26
36
.13
2.25
.012
Homogeneity of effect sizes: x2 = 2.39, 2 df, p = . 30
Table notes. Percent hits and confidence estimates are rounded to nearest percentage point. Combined effect size and Stouffer z are
weighted by study sample size.
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Honorton
3
CPYRGHT
Figure 1. Ganzfeld Performance in Relation to Reported Psi Experiences
29
0.7
0.6
0.5
48
0.4
47
0.2
57
0.1
0
-0.1
-0.2
-0.3
-0.4
-0.5
0
1
2
3
4
Number of Types of Psi Experiences Reported
0.75, h = . 08, 95% CI from 21% to 36%). The
three studies combined yield a success rate of 31%
(N = 326, p = . 012, z = 2.25, h = . 13, 95% CI
from 26% to 36%). The effect sizes of the three
studies are quite consistent (x2 = 2.39, 2 df, p =
.30)
psi types, PIF item 14 asks "If you have had
experiences which you thought involved psi,
which of the following do you feel you have expe-
rienced (please check)." One point was given for
each of the checked items (telepathy, clairvoyance,
precognition, psychokinesis) and their sum
constituted the psi experiences predictor.
Honorton and Schechter (1987) found a sig-
nificant positive correlation between the number of
types of psi experiences and psi ganzfeld
Table 3. Ganzfeld Psi Performance in Relation to An Alternate Measure of Reported Psi Experiences
95% CI
Personal
Psi
Study
N
Trials
% Hits
From
To
Effect Size
(h)
N
P
Experiences?
PRL-1
7
14
1
55
-. 27
-1.11
.867
"None"
PRL-2
7
29
5
66
.08
-0.14
.555
FRNM
17
29
12
54
.10
0.19
.426
Combined
31
26
11
41
.01
-0.28
.61
PRL-1
84
33
24
43
.18
1.61
.054
"Some"
PRL-2
97
36
27
45
.24
2.33
.010
FRNM
91
31
22
40
.13
1.14
.126
Combined
272
33
28
39
.19
2.96
.0015
Difference in proportions ("None" vs. "Some")
0.85
.197
.
Table notes. Percent hits and confidence estimates are rounded to nearest percentage point. Combined effect sizes and Stouffer's zs are weighted by study
sample sizes. Confidence intervals for subsets with N ≤ 30 are based on Blyth & Still (1983). None/Some difference is based on a z-test for binomial
proportions using the combined (sample size weighted) estimates for each group.
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Reported Personal Psi Experiences
Following standard definitions of the four basic
0.3
Effect Size (d)

CPYRGHT
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4
Ganzfeld Novices
performance (session z-scores but not direct hits)
for participants in PRL-1. Recast as a one-way
ANOVA using linear contrasts (Rosenthal &
Rosnow, 1985), F = 7.41, 1/86 df, p = . 0039 (r =
.28). This relationship was replicated in PRL-2 (F
= 2.86, 1/99 df, p = . 047, r = . 17). As described
earlier, the Juilliard students, who contributed to
the later study, reported significantly fewer types
of personal psi experiences. When they are ex-
cluded from the PRL-2 analysis, the relationship
between psi performance and psi experiences is
nearly identical to that obtained in PRL-1 (F =
6.29, 1/79 df, p = . 007, r = . 27).
Combining the two PRL studies gives F = 9.37,
1/190 df, p = . 0015, r = . 24. Figure 1 shows the
relationship between number of types of psi
experiences reported and ganzfeld effect size
(Cohen's d; Cohen, 1977).
Due to their rewording of the relevant PIF
question in the FRNM study, Broughton, et al.,
could not perform the same analysis on their data.
Instead, they reported a modified analysis between
self-reports of psi experiences (coded as "none" or
"some") and direct hits. FRNM novices reporting
"some"!
personal psi experiences
were
nonsignificantly more successful than those re-
porting "none." Since the FRNM report does not
provide z-scores, Table 3 summarizes all three
studies using the FRNM psi experience definition
as the predictor and direct hits as the outcome
measure. The combined difference between
participants who did and did not report personal
psi experiences is not significant in this analysis,
but significant ESP performance was only obtained
by those who reported psi experiences (N = 272,
33% hits, p = . 0015, z = 2.96, h = . 19).
The stronger association in the PRL data
between number of types of personal psi
experiences and session z-scores (rather than
direct hits) indicates that persons who believe they
have had a variety of psi experiences are more
adept at identifying partial correspondences
between their ganzfeld experience and targets in
the judging pool. Further research is needed to
determine whether this is better explained by
motivational or cognitive factors. Perhaps those
who report an abundance of psi experiences,
motivated by a need to validate their personal
experiences, expend more effort to find
correspondences when judging their ganzfeld
mentation against the target pool. If so, there
should be a positive relationship between
abundance of types of personal psi experiences and
the amount of time taken for judging. This could
be tested by measuring judging time in future
studies. An alternative cognitive model might
suggest that abundance of reported psi experiences
correlates with general pattern recognition ability,
which could be tested by giving participants a
variety on nonpsi pattern recognition tasks.
Prior Psi Testing
PIF item 19 asks, "Have you ever participated in
formal laboratory testing of psi phenomena
[Yes/No]?" By definition, none of the novices had
previous psi ganzfeld experience. While most of
Table 4. Summary of Prior Testing
95% CI
Prior Psi Testing?
Study
Trials
Hits
Effect
Size (h)
Z
P
PRL-1
72
26
16
36
.03
0.16
.437
No Prior Psi Testing
PRL-2
92
32
23
40
.15
1.31
.0948
FRNM
94
31
22
40
.13
1.18
.1182
Combined
258
30
25
35
.11
1.62
.053
PRL-1
20
50
29
71
.52
2.20
.0139
Prior Psi Testing
PRL-2
12
67
34
83
.86
2.77
.0028
FRNM
14
29
10
58
.05
0.05
.4787
Combined
46
48
35
60
.47
2.87
.0021
Difference in proportions (Prior vs. No Prior Testing):
2.35
.0094
N
%
From
To
Table notes. Percent hits and confidence estimates are rounded to nearest percentage point. Combined effect sizes and Stouffer's zs are weighted by study
sample sizes. Confidence intervals for subsets with N $ 30 are based on Blyth & Still (1983). Prior/No Prior Testing difference is based on a z-test for
binomial proportions using the combined (sample size weighted) estimates for each group.
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CPYRGHT
Honorton
5
them had not been previously involved in formal
psi research of any kind, approximately 16% of the
PRL novices and 13% of FRNM novices had
participated in other types of psi research. In PRL-
1 a hit rate of 50% was achieved by novices who
had previously participated in other, nonganzfeld,
psi experiments (N = 20, p = . 014, z = 2.20, h =
.52), while only 26% of those with no prior psi
testing experience had hits (N = 72, 19 hits and 53
misses, p = . 437, z = 0.16, h = . 03). The distribu-
tion of hits and misses in relation to prior testing
was significant: Overall-adjusted Fisher exact test
(p = . 024, phi = . 21). In PRL-2, 67% of those with
previous testing experience had hits (N = 12, p =
.0028, z = 2.77, h = . 86) as did 32% of subjects
with no prior testing history (N = 92, p = . 095, z =
1.31, h = . 15). The Overall-adjusted Fisher test of
the distribution of hits and misses was significant
(p = . 02, phi = . 23).
This effect was not replicated in the FRNM
study, which showed a slight reversal of the trend:
hits were obtained by 29% of subjects with prior
testing (N = 14, p = . 479, z = 1.05, h = . 08) and by
31% of those with no prior testing (N = 94, p =
.118, z = 1.18, h = . 13); Overall-adjusted Fisher p
= . 543 (phi = -. 01). The overall effect of prior
testing is significant, though clearly further
research will be needed to assess the cross-labora-
tory generality of this finding. (See Table 4.) The
mean weighted phi is .14 (95% CI from .02 to
.25).
Myers-Briggs Feeling-Perception
Following MBTI convention, participants were
classified as FP if their continuous scores on the
TF and JP Scales were both above 100. A recent
reevaluation of the MBTI in terms of the five-
factor model of personality (McCrae & Costa,
1989) indicates that the MBTI TF Scale correlates
positively with Agreeableness. JP correlates
negatively with Conscientiousness (i.e., orderli-
ness) and positively with Openness to Experience.
In PRL-1, 50% of the MBTI FP participants
obtained hits (p = . 00057, z = 3.25, h = . 52) com-
pared to 18% of those classified non-FP (N = 44,
p = . 892, z = - 1.24, h = -. 17). The Overall-adjusted
Fisher exact p = . 001 (phi = . 34). In PRL-2, the FP
success rate was 36% (N = 44, p = . 075, z = 1.44,
h = . 23) and 35% of the nonFP subjects were
successful (N = 60, p = . 054, z = 1.61, h = . 22).
The Overall-adjusted Fisher exact p = . 472 (phi =
.01).
In the FRNM series, 40% of the FP subjects had
hits (N = 42, p = . 02, z = 2.06, h = . 33), compared
to 25% for the nonFP subjects (N = 60, p = . 5, z =
0.00, h = . 00). The Overall-adjusted Fisher exact p
= . 0499 (phi = . 16).
Table 5 summarizes the results across all three
studies. The FP subjects show significant
performance (N = 127, p = . 000064, z = 3.83, h =
.38). The 95% confidence interval for the mean
success rate of 42% is from 34% to 49%. NonFP
show nonsignificant overall performance, with a
hit rate of 27% (N = 164, p = . 33, z = 0.44, h =
.035); the 95% CI is from 20% to 34%. The differ-
ence in overall success rates between FP and
nonFP subjects is also significant (z = 2.69, p =
.0036). Using meta-analytic techniques for com-
bining correlations (Hedges and Olkin, 1985), the
Table 5. MBTI Feeling/Perception (FP)
95% CI
FP?
Study
N
% hits
From
To
Effect size
(h)
Z
p
PRL-1
40
50
37
64
.52
3.25
.00057
Yes
PRL-2
45
36
23
48
.23
1.44
.075
FRNM
42
40
27
54
.33
2.06
.02
Combined
127
42
34
49
.38
3.83
.000064
PRL-1
44
18
5
31
-. 17
-1.24
.892
No
PRL-2
60
35
24
46
.22
1.61
.054
FRNM
60
25
14
36
.00
0.00
.500
Combined
164
27
20
34
.035
0.44
.33
Difference in proportions (Combined FP vs No FP)
2.69
.0036
Table notes. Percent hits and confidence estimates are rounded to nearest percentage point. Combined effect sizes and Stouffer's zs are weighted by study
sample sizes. FP/no FP difference is based on a z-test for binomial proportions using the combined (sample size weighted) estimates for each group.
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Ganzfeld Novices
mean weighted phi is .16 (95% CI from .05 to
.27).
Mental Disciplines
PIF item 28 asks, "Have you ever practiced any
form of mental discipline, e.g., meditation,
biofeedback, hypnosis, relaxation
exercises
[Yes/No]." In PRL-1, hits were obtained by 36%
of those reporting some experience involving
mental disciplines (N = 72, p = . 024, z = 1.98, h =
.24) and by 16% of those with no involvement
with mental disciplines (N = 19, p = . 89, z = - 1.22,
h= -. 23). In PRL-2, hits were obtained by 33% of
participants with mental disciplines experience (N
= 83, p = . 075, z = 1.44, h = . 17) and by 48% of
the nonpractitioners (N = 21, p = . 021, z = 2.04, h
= . 48); the latter outcome is largely due to the Juil-
liard nonpractitioners who had a success rate of
71% (N = 7, p = . 0129, z = 2.23, h = . 97). The
distribution of hits in relation to mental disciplines
for the Juilliard students shows a nearly significant
reversal of the PRL-1 pattern (Overall-adjusted
Fisher exact p = . 091, phi = -. 30).
In the FRNM study, practitioners had a 34% hit
rate (N = 65, p = . 07, z = 1.48, h = . 19), compared
to 26% for the nonpractitioners (N = 43, p = . 477,
z = . 06, h = . 01).
Table 6 summarize the three studies. Thirty-four
percent of the practitioners were successful overall
(N = 220, p = . 0025, z = 2.81, h = 20, 95% CI
from 28% to 40%), compared to 28% of the
nonpractitioners (N = 83, p = . 37, z = 0.33, h =
.07, 95% CI from 20% to 38%). The difference
between practitioners and nonpractitioners is
nonsignificant (z = 0.96, p =. 168, phi = . 06).
When the Juilliard students are excluded, the
overall difference increases to z = 1.45, p = . 086,
phi =. 09.
Combined-Predictor Models
In this section we examine the combined effects
of the predictors. There are significant
intercorrelations among three of the predictors in
the combined PRL data: reported psi experiences,
FP, and mental disciplines. The strongest
correlation is between FP and psi experiences (r =
.226, 185 df, p = . 002). The correlation between
FP and involvement with mental disciplines is
.184 (p = . 012). Mental disciplines and psi
experiences show a correlation of .179 (193 df,
p = . 012). The fourth predictor, prior psi testing,
correlates positively but nonsignificantly with psi
experiences (r = . 106, 193 df, p = . 139) and with
mental disciplines (r = . 088, 193 df, p = . 222).
Prior testing is negatively but nonsignificantly
correlated with reported psi experiences (r = -. 101,
185 df, p = . 169). Since no prior predictions were
made concerning the direction of relationships
among the predictors, the cited p-values are two-
tailed.
The Four-Predictor Model
Due to the small number of participants with
Table 6. Ganzfeld Psi Performance in Relation to Mental Disciplines
95% CI
Mental
Data Set
Effect
disciplines?
N
% Hits
From
To
Size (h)
Z
p
PRL-1
19
16
4
39
-. 23
-1.22
.89
Nonpractioners
PRL-2
21
48
28
70
.48
2.04
.021
FRNM
43
26
13
38
.01
0.06
.48
Combined
83
28
20
38
.07
0.33
.37
PRL-1
72
36
26
46
.24
1.98
.024
Practitioners
PRL-2
83
33
23
42
.17
1.44
.075
FRNM
65
34
23
44
.19
1.48
.07
Combined
220
34
28
40
.20
2.81
.0025
Difference (Combined Yes vs. No)
0.96
.168
Table notes. Percent hits and confidence estimates are rounded to nearest percentage point. Combined effect sizes and Stouffer's zs are weighted by study
sample sizes. Confidence intervals for subsets with N ≤ 30 are based on Blyth & Still (1983). Yes/No difference is based on a z-test for binomial
proportions using the combined (sample size weighted) estimates for each group.
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7
CPYRGHT
Table 7. The Three Factor Model
95% CI
Psi+FP+Mental
Study
N
% Hits
From
To
Effect
Size (h)
Z
P
Disciplines?
PRL-1
49
18
6
31
-. 16
-1.26
.895
No
PRL-2
67
37
27
48
.27
2.12
.017
FRNM
74
27
17
37
.05
0.29
.386
Combined
190
28
20
38
.07
0.92
.179
PRL-1
34
56
41
70
.64
3.67
.00012
Yes
PRL-2
37
32
19
46
.17
0.86
.194
FRNM
28
43
26
62
.38
1.89
.029
Combined
99
43
35
52
.39
3.64
.00014
Difference (Combined Yes vs. No)
2.64
.0041
Table notes. Percent hits and confidence estimates are rounded to nearest percentage point. Combined effect sizes and Stouffer's zs are weighted by study
sample sizes. Confidence intervals for subsets with N ≤ 30 are based on Blyth & Still (1983). Yes/No difference is based on a z-test for binomial
proportions using the combined (sample size weighted) estimates for each group.
prior psi testing experience, only 15 participants
satisfied the four-predictor model (reported psi
experiences, FP, mental disciplines, and prior
testing) in the three studies. Nevertheless, the
results are rather striking. In PRL-1 hits were
obtained by six of the seven participants satisfying
all four factors (p= . 0013, z = 3.00, h = 1.32).
Three out of four were successful in PRL-2 (p
=. 0508, z = 1.64, h = 1.05). In the FRNM series,
hits were obtained by two of the four participants
satisfying all four factors. Combining across the
three studies, 11 of the 15 participants correctly
identified their targets (73% hits, weighted z =
3.35, p = . 00041). The overall effect size (h
weighted by sample size) is = 1.03.
The Three-Predictor Model
Due to the extremely small number of cases
satisfying the four-predictor model, Honorton &
Schechter (1987) and Broughton, et al., (in press)
focused on a three-factor model, excluding prior
psi testing. Combining the three studies, 99
participants satisfied the three-predictor model
(reported psi experiences, FP, and involvement
with mental disciplines). In PRL-1, 34 participants
satisfied the three-factor model. They achieved a
success rate of 56% (p = . 00012, z = 3.67, h = . 64)
and the 95% CI is from 41% to 70%. An 18%
success rate was obtained by the 49 PRL-1
participants not satisfying the three-factor model,
but for whom data on all three factors is available
(p = . 895, z = - 1.26, h = -. 16, 95% CI from 6% to
31%). This pattern was slightly reversed in PRL-2
with a success rate of 32% for those satisfying the
model (N = 37, p = . 194, z = 0.86, 95% CI from
19% to 46%) and a 37% success rate for those who
did not satisfy it (N = 67, p = . 017, z = 2.12, h =
.27, 95% CI from 27% to 48%). In the FRNM
study, 28 participants satisfied the model with a
success rate of 43% (p = . 029, z = 1.89, h = . 38,
95% CI from 26% to 62%). A success rate of 27%
was obtained by the 74 FRNM participants who
did not satisfy the model (p = . 386, z = 0.29, h =
.07, 95% CI from 17% to 37%).
Table 7 summarizes the results of all three
studies. Overall, the three-factor model appears to
show some promise. Altogether 99 novice
participants in three studies satisfied the three-
predictor model, with an overall success rate of
43% (z = 3.64, p = . 00014, h = . 39, 95% CI from
35% to 52%). The 191 participants not satisfying
the model obtained a success rate of 28% (z =
0.92, p = . 179, h = . 07, 95% CI from 20% to
38%). The difference between the two groups is
significant (z = 2.64, p = . 0041) and the phi
coefficient is .15.
Discussion
While none of the predictors individually
differentiated successful versus unsuccessful
performance in each of the three studies,
significant hitting across all three studies was
limited to participants meeting the criteria for each
of the individual predictors. From a purely
pragmatic point of view, if we were advising new
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Ganzfeld Novices
ganzfeld investigators how to maximize the
likelihood of successful psi ganzfeld performance
in their studies, we would recommend that they
recruit participants who conform to as many of
these factors plus extraversion (Honorton,
Ferrari, & Bem, in press) -as possible.
More detailed and systematic refinement of the
four predictors used in these studies would
probably be more useful at this stage than further
direct
replications
involving
the current
implementation. The PRL results using number of
types of reported psi experiences as a predictor, for
example, suggest that a more refined measure of
participants' putative psi experiences might well
be more effective. Such a measure might include
items to assess the predominant mode, as well as
type and frequency of the participants' reported psi
experiences. This would enable investigators to
test whether or not the modality of participants'
personal psi experiences is systematically (and
perhaps differentially) related to performance in
different types of experimental task: for instance,
whether those whose experiences are primarily
imagery-driven are better ganzfeld performers
than those whose experiences involve noncognitive
impressions and vice versa for unconscious psi
tasks such as remote physiological influences (e.g.,
Braud & Schlitz, 1992).
References
Blyth, C.R., & Still, H.A. (1983). Binomial confi-
dence intervals. Journal of the American
Statistical Association, 78, Number 386, 108-
116.
Braud,
W.G.,
&
Schlitz,
M.J. (1992).
Consciousness
interactions
with
remote
biological systems: anomalous intentionality
effects. Subtle Energies, 2, 1-46.
Briggs, K. C., & Myers, I. B. (1957). Myers-
Briggs Type Indicator Form F. Palo Alto, CA:
Consulting Psychologists Press, Inc.
Broughton, R. S., Kanthamani, H., & Khilji, A.
(in press). Assessing the PRL success model on
an independent ganzfeld database. In Research
in Parapsychology 1989.
Metuchen, NJ:
Scarecrow Press.
Cohen, J. (1977). Statistical power analysis for the
behavioral sciences. NY: Academic Press.
Hedges, L.V., & Olkin, I. (1985). Statistical
methods for meta-analysis. NY: Academic
Press.
Honorton, C., Berger, R.E., Varvoglis, M. P.,
Quant, M, Derr, P., Schechter, E.I., & Ferrari,
D.C. (1990). Psi communication in the gan-
zfeld: Experiments with an automated testing
system and a comparison with a meta-analysis
of earlier studies. Journal of Parapsychology,
54, 99-139.
Honorton, C., Ferrari, D. C., & Bem, D. J. (in
press). Extraversion and ESP performance: A
meta-analysis and a new confirmation. In
Research in Parapsychology, 1990. Metuchen,
NJ: Scarecrow Press.
Honorton, C., & Schechter, S. (1987).Ganzfeld
target retrieval with an automated testing sys-
tem: A model for initial ganzfeld success. In D.
H. Weiner & R. D. Nelson (Eds.) Research in
Parapsychology 1986. (pp. 36-39). Metuchen,
NJ: Scarecrow Press.
McRae, R.R., & Costa, P.T., Jr. (1987). Validation
of the five-factor model of personality across
instruments and observers. Journal of
Personality and Social Psychology, 52, 81-90.
McRae, R.R., & Costa, P.T., Jr. (1989). Rein-
terpreting the Myers-Briggs Type Indicator
from the perspective of the five-factor model of
personality. Journal of Personality, 57:1, 17-
40.
Overall, J.E., Rhoades, H.M., & Starbuck, R.R.
(1987). Small sample tests for homogeneity of
response probabilities in 2 x 2 contingency ta-
bles. Psychological Bulletin, 102, 307-314.
Rosenthal, R., & Rosnow, R.L. (1985). Contrast
analysis: Focused comparisons in the analysis
of variance. NY: Cambridge University Press.
Schlitz, M.J., & Honorton, C. (1992). Ganzfeld psi
performance within an artistically gifted popu-
lation. Journal of the American Society for
Psychical Research, 86, 83-98.
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AnBERMEal Final Report
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APPENDIX C
Impact of the Sender In Ganzfeld Communication:
Meta-Analysis and Power Estimates
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.
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Impact of the Sender in Ganzfeld Communication:
Meta-Analysis and Power Estimates
Charles Honorton
Psychophysical Research Laboratories and The University of Edinburgh
Abstract: This report provides a quantitative review of all available studies
of information retrieval via real-time ganzfeld imaging techniques reported
in the English-language parapsychological literature between 1974-1991.
The review estimates the magnitude of the effect overall and as a function of
target presentation conditions (presence or absence of a target observer or
sender). The resulting estimates are used in a statistical power analysis to
determine optimal sample sizes for maximising successful detection of
ganzfeld communication in new studies.
Keywords: Ganzfeld, meta-analysis, parapsychology, power analysis.
CPYRGHT
Description of the Domain
In the early 1970s a number of investigators were led independently to explore the
effects of a perceptual isolation technique (ganzfeld stimulation) on performance in
anomalous communication tasks (Braud, Wood, & Braud, 1975; Honorton & Harper,
1974; Parker, 1975). The impetus for this research involved converging evidence that
anomalous communication effects were frequently associated with internal attention
states characterised by reduced perceptual processing (see Honorton, 1977). A
homogeneous visual field (ganzfeld) is produced through diffusion of a bright light
source over translucent hemispheres covering the receiver's eyes. Homogeneous
auditory stimulation is produced by white noise through headphones. The receiver
usually undergoes relaxation exercises at the beginning of the session, then free-as-
sociates to describe a randomly selected and remotely located target. The target usually
is viewed by a sender who attempts to communicate salient features of its content or
meaning to the receiver; in studies without a sender, the target is enclosed in an opaque
container. Assessment typically involves blind-ranking or rating similarities between the
receiver's ganzfeld-produced imagery and a pool including the target and several
decoys.
The Standard Analysis Method
In the prototypical ganzfeld imaging study, receivers attempt to identify the target by
ranking perceived similarities between their ganzfeld generated imagery and a judging
pool consisting of the target and several decoys. This judging task is "double-blind,"
such that neither receiver nor experimenter knows the identity of the correct target.
Success is defined in terms of the binomial probability associated with the proportion of
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"direct hits," i.e., correctly-assigned ranks of 1, compared to the null chance expectation
of 1/N, where N is the number of candidates in the judging pool (usually four); in the
modal case-accounting for approximately three-quarters of the studies-the null
hypothesis (of no communication) predicts that the proportion of "direct hits" will not
differ reliably from .25.
Variations in Method
Several variations in analysis method also have been reported. A few early studies
defined performance in terms of 'binary' or partial hits, a crude weighting scheme that
gives credit when the target rank is in the lower half of the rank distribution, such that
the chance probability of a hit is .5. Others have used a sum-of-ranks technique that
utilises all of the rank data (Solfvin, Kelly, & Burdick, 1978), or standardized ratings of
the target and decoys (Stanford & Sargent, 1983). A more radical variation used in a
small cluster of studies employed a special set of 210 targets characterised by the
presence or absence of 10 binary features (Honorton, 1975); the receivers' ganzfeld
impressions were also feature-coded and matched against the 10-bit target code,
producing 10 independent binary trials/session. None of these methods account for
more than 10% of the studies.
Method
Study Retrieval
The meta-analysis includes all (real-time) ganzfeld imaging studies published in the
English-language parapsychology literature between 1974 and 1991. Besides published
reports, the meta-analysis also includes doctoral theses and abstracts of otherwise
unpublished studies.
Meta-Analysis of Ganzfeld Effect Sizes
To maintain compatibility with previous estimates, the direct hits measure was used
whenever possible. The effect size index Cohen's h (Cohen, 1977) was employed. The h
index is the (arcsine transformed) difference between the observed proportion of hits
and the proportion expected by chance. For studies not amenable to direct hits analysis,
approximations to Cohen's h were obtained by dividing the z score by VN, where z is
the standard normal deviate associated with the reported significance level and N is the
total number of trials. In a few cases involving multiple analyses of the same data set, z,
N, and effect size were estimated by averaging across the reported measures. Studies
reporting only 'nonsignificance' were assumed to have effect size = 0.00.
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bact of the Sender in Ganzfeld Communication 3
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Table 1. Overall Results
95% confidence
interval
N
studies
N
investi-
gators
Median
sample
size
Mean
effect
size
From
To
Z
p
Fail-
Safe
Ratio
All studies
73
21
32
0.16
.06
.26
5.74
4.75×10-9
11 to 1
Direct hits
studies
53
16
30
0.23
.13
.33
6.75
7.43×10-12
16 to 1
Results
Overall Effect
A total of 73 studies were retrieved. These studies were conducted by 21
independent research teams and involve 4,155 trials contributed by 1,762 subjects.
Table 1 summarizes the overall ganzfeld study outcomes. The combined z-score is 5.74
(p = 4.75 x 10-9). Rosenthal's (1991) 'Fail-Safe N' estimate indicates that approximately
11 unreported studies averaging null outcomes would be required to reduce the overall
significance of the retrieved studies to p =. 05. The mean effect size is .16 (95% CI =
.06/.26). The mean effect size is equivalent to a success-rate of 32.2% in the standard 4-
choice situation. The last row of Table 1 gives the same breakdown for the largest
subset of studies involving analysis by direct hits. These studies were contributed by 16.
independent research teams and the combined z = 6.75 (p = 7.43 x 10-12). The 'Fail-
Safe' estimate indicates that approximately 16 unretrieved studies averaging null
outcomes would be required to jeopardise the significance of this subset. The mean
Table 2. Statistical Power Analysis for Overall Results
All Studies
Direct Hits
Studies
Power Estimate (using average ES & sample size)
0.23
0.35
Expected N Studies Significant at p = . 05, given power estimate
17
19
Observed N Studies significant
19
15
Z(Observed vs. Expected)
0.49
-1.17
p(Z)
.31
.88
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effect size of .23 is equivalent to an average success rate of 35.5% in the typical 4-
choice situation and the 95% CI = . 13/.33 (approx. 31%/40%).
Statistical Power Analysis for Overall Effect. Table 2 summarizes a statistical power
analysis based on the mean effect sizes and median sample sizes for the data in Table 1
(Cohen, 1977, pp. 460-461). For all studies, the power analysis indicates that an
average effect size of .16 (at the p≤.05 level) would be detected only about 21% of the
time, given the median sample size of 57 trials. The power estimate for direct hits
studies (mean ES = . 23, mean N = 31 trials) is 23%. As indicated by the last two rows
of Table 2, the actual number of significant (p≤ .05) studies is consistent with the
number expected from the power analysis. It is clear from the meta-analysis that the
various alternatives to direct hits assessment have not been effective.
A sample size of 420 trials would be necessary to detect (at p≤ .05) an effect size of
.16 (all studies) with 95% power. For an effect size of .23 (direct hits), 95% power can
be achieved with a sample size of 200 trials.
Impact of Sender vs. No Sender
Figure 1 presents a stem-and-leaf display of the distribution of effect sizes for studies
Figure 1. Stem and Leaf Plot of Effect Size Distribution
No Sender
Sender
N Studies:
12
N Studies
61
Minimum:
-. 582
Minimum:
-. 930
Lower Quartile:
-. 086
Lower Quartile:
-. 020
Median:
.105
Median:
.140
Upper Quartile:
.305
Upper Quartile:
.320
Maximum:
.730
Maximum:
1.440
-9
3
8
-5
-4
30
0
-3
7420
-2
70
-1
620
000
-0
54221
0
0
00477779
1
1111 3 4 5 5 7 8 8 8
971
2
234447
2
3
124 4 7 8 8
0
4
2224
5
8
3
7
2
8
1 7
9
5
13
3
14
4
Note: Outlying values are underscored.
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Impact of the Sender in Ganzfeld Communication 5
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Table 3. Studies with and without Senders
95% confidence
interval
N
studies
N
investi-
gators
Median
sample
size
Mean
effect
size
From
To
Z
P
Fail-
Safe
Ratio
Sender
61
20
30
0.17
.07
.27
5.70
6×10-9
11 to 1
No Sender
12
7
33.5
0.10
-. 10
.30
1.31
.095
-
Difference
1.49
.137
with and without senders (Tukey, 1977). A statistical summary is provided in Table 3.
Senders were employed in 61 studies (3,684 trials) by 20 independent investigators. The
combined z-score is 5.70 (p=7x10-9). Rosenthal's 'Fail-Safe N' estimate indicates that
approximately 11 unreported studies averaging null outcomes would be required to
reduce the overall significance of the retrieved studies to p =. 05. The mean effect size of
.17 is equivalent to a success rate of 32.5% in the typical 4-choice situation and the 95%
CI = . 07/.27, i.e., 28%/37%.
The remaining 12 studies (470 trials) did not employ senders. These studies,
contributed by seven independent investigators, have a combined z = 1.31 (p =. 095).
The mean effect size is .10 (95% CI = -. 10/.30). Thus, the studies without senders show
no overall evidence for anomalous communication.
Transforming the mean effect sizes for studies with and without senders back to
proportion of hits, the difference between the two conditions was tested using the z test
for differences between binomial proportions. The resulting z of 1.49 is nonsignificant
(p =. 1371, two-tailed). The effect size for the difference is .023. While this difference is
not significant, only the studies with senders show a significant overall ganzfeld
communication effect.
Since the sender/no sender comparison is between rather than within studies, i.e., not
based on systematic within study comparison of sender impact, the observed difference
could be due to factors other than the presence or absence of senders. Investigators tend
to implement experimental procedures in various ways, sample from different
populations (e.g., students, volunteers), employ various instructional sets, and use a
variety of different target stimuli. Such variations could conceivably account for the
observed differences.
-
To assess this possibility, an analysis was performed on the subset of five
investigators who contributed both studies with senders and without senders. This
subset comprises only about 20% of the investigator base, but 40% of the total number
of trials (N = 1,666). These investigators reported 25 studies with senders (N = 1,497,
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mean ES = . 301, SD = . 420, combined z = 5.84, p = 3.15 x 10-9). This is equivalent to a
hit rate of 38.96% in the typical 4-choice judging situation. Seven studies without.
senders yield a mean ES = . 017 (N = 169, SD = . 351, combined z = 0.31, p = 378), or
25.74% hits in the 4-choice situation. For this subset the difference in the proportion of
hits with and without senders is significant (z = 3.39, p = . 0007, two-tailed, 95% CI
from .06/.20). The effect size of the difference is .083. This analysis indicates that
sender/no sender differences in performance are not likely to be the result of differences
in laboratory or investigator style factors. Statistical power analysis indicates that
approximately 1600 trials would be needed to achieve a 95% likelihood of detecting a
difference of this magnitude.
Conclusions
This report has focused on two aspects of a larger meta-analytic study of anomalous
communication in the ganzfeld: estimates of the main effect (overall magnitude), and the
impact of one moderator variable (presence or absence of a target observer or sender).
Regarding the main effect, the meta-analysis suggests the following conclusions:
. The combined evidence across 73 studies and 21 independent investigators
provides strong evidence for anomalous communication in the ganzfeld: the null
hypothesis is highly implausible given the overall probability of 4.75 x 10-9.
. The fail-safe estimates render alternative explanations based on selective
reporting of positive results untenable. The overall observed outcome would
remain statistically significant even if there were 25,696 unretrieved ganzfeld
trials, averaging null outcomes (Fail-safe estimate x N studies x mean trials per
study).
· Statistical power analysis indicates that the observed number of statistically
significant (p≤ .05) studies is consistent with the overall effect size estimates for
all studies and direct hits studies.
. The meta-analysis fails to support the advantage of nondirect hits analysis
methods.
. The power analysis indicates that anomalous communication effects should be
detectable at conventional significance levels in 95% of ganzfeld studies
employing direct hits analysis and sample sizes ≥ 200 trials.
Due to the small number of studies without senders, the meta-analysis is less clear
concerning the moderating effect of the sender. The strongest evidence regarding sender
impact is based on an analysis of the subset of five investigators who each contributed
studies with and without senders, thus holding laboratory, sampling, and investigator
style factors constant. This analysis indicates that the presence of a sender results in
significantly superior anomalous communication effects, though the magnitude of the
difference is small. Moreover, since, with one exception (Raburn, 1975), the primary
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studies were not designed to systematically assess sender versus no sender conditions,
the meta-analysis cannot address the underlying source of this difference. New studies,
specifically designed to compare sender/no sender effects, will be needed to assess the
extent to which the sender's influence is instrumental (intrinsic to the communication
process) or peripheral (based on psychological or motivational factors).
References
/or determines dato
type "
Braud, W. G., Wood, R., & Braud, L. W. (1975). Free-response GESP performance
during an experimental hypnagogic state induced by visual and acoustic ganzfeld
techniques. A replication and extension. Journal of the American Society for
Psychical Research, 69, 105-113.
Cohen, J. (1977). Statistical power analysis for the behavioral sciences (rev. ed.). New
York: Academic Press.
Honorton, C. (1975). Objective determination of information rate in psi tasks with
pictorial stimuli. Journal of the American Society for Psychical Research, 69, 353-
359.
Honorton, C. (1977). Psi and internal attention states. In B. B. Wolman (Ed.),
Handbook of parapsychology. NY: Van Nostrand Reinhold. (pp. 435-472).
Honorton, C., & Harper, S. (1974). Psi-mediated imagery and ideation in an
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Society for Psychical Research, 68, 156-168.
Parker, A. (1975). Some findings relevant to the change in state hypothesis. In J. D.
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Tukey, J. W. (1977). Exploratory data analysis. Reading, MA: Addison-Wesley.
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Impact of the Sender in Ganzfeld Communication 8
Studies Used in the Meta-Analysis
Ashton, . T., Dear, P. R., Harley, T. A., & Sargent, C. L. (1981). A four-subject study
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Braud, W. G., Wood, R., & Braud, L. W. (1975). Free-response GESP performance
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Child, I. L., & Levi, A. (1979). Psi-missing in free-response settings. Journal of the
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Press, pp. 184-186.
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Impact of the Sender in Ganzfeld Communication 9
Honorton, C., Berger, R. E., Varvoglis, M. P., Quant, M., Derr, P., Schechter, E. I., &
Ferrari, D. C. (1990). Psi communication in the ganzfeld: Experiments with an
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Honorton, C., & Harper, S. (1974). Psi-mediated imagery and ideation in an
experimental procedure for regulating perceptual input. Journal of the American
Society for Psychical Research, 68, 156-168.
Houtkooper, J. M., Gissurarson, L. R., & Haraldsson, E. (1988-89). Why the ganzfeld
is conducive to ESP: a study of observational theory and the participant-order
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Kanthamani, H., Khilji, A., & Rustomji-Kerns, R. (1989). An experiment in ganzfeld
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Research in Parapsychology, 1988. Metuchen, NJ: Scarecrow Press. (pp. 84-88.)
Keane, P., & Wells, R. (1979). An examination of the menstrual cycle as a hormone
related physiological concomitant of psi performance. In W. G. Roll (Ed.), Research
in Parapsychology, 1978. Metuchen, NJ: Scarecrow Press. (pp. 72-74.)
Milton, J. (1986). Displacement effects, role of the agent, and mentation categories in
relation to ESP performance. Unpublished Ph.D. thesis, University of Edinburgh.
Munson, R. J., Kanthamani, H., Khilji, A., & Zingrone, N. L. (1988). FRNM ganzfeld:
an attempted replication. In L. A. Hinkel & R. E. Berger (Eds.), Research in
Parapsychology, 1987. Metuchen, NJ: Scarecrow Press (pp. 44-47.)
Murre, J. M., van Dalen, A. C., Dias, L. R., & Schouten, S. A. (1988). Ganzfeld psi
experiments with a control condition. Journal of Parapsychology, 52, 103-126.
Palmer, J., & Aued, I. (1975). An ESP test with psychometric objects and the ganzfeld:
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Parapsychology, 1974. Metuchen, NJ: Scarecrow Press (pp. 50-53).
Palmer, J., Bogart, D. N., Jones, S. M., & Tart, C. T. (1977). Scoring patterns in an
ESP ganzfeld experiment. Journal of the American Society for Psychical Research,
71, 121-145.
Palmer, J., & Kanthamani, H. (1990). A ganzfeld experiment with subliminal sending.
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Palmer, J., Khamashta, K., & Israelson, K. (1979). An ESP ganzfeld experiment with
Transcendental Meditators. Journal of the American Society for Psychical
Research, 73, 333-348.
Palmer, J. Whitson, T., & Bogart, D. N. (1980). Ganzfeld and remote viewing: a
systematic comparison. In W. G. Roll (Ed.), Research in Parapsychology, 1979.
Metuchen, NJ: Scarecrow Press. (pp. 169-171.)
Parker, A. (1975). Some findings relevant to the change in state hypothesis. In J. D.
Morris, W. G. Roll, & R. L. Morris (Eds.) Research in Parapsychology, 1974.
Metuchen, NJ: Scarecrow Press (pp. 40-42).
Parker, A., Millar, B., & Beloff, J. (1977). A three-experimenter ganzfeld: an attempt to
use the ganzfeld technique to study the experimenter effect. In J. D. Morris, W. G.
Roll, & R. L. Morris (Eds.) Research in Parapsychology, 1976. Metuchen, NJ:
Scarecrow Press (pp. 52-54.)
Raburn, L. (1975). Expectation and transmission factors in psychic functioning.
Unpublished honors thesis, Tulane University, New Orleans, LA.
Rogo, D. S. (1976). ESP in the ganzfeld: an exploration of parameters. In J. D. Morris,
W. G. Roll, & R. L. Morris (Eds.) Research in Parapsychology, 1975. Metuchen,
NJ: Scarecrow Press (pp. 174-176).
Rogo, D. S., Smith, M., & Terry, J. (1976). The use of short-term ganzfeld stimulation
to facilitate psi-mediated imagery. European Journal of Parapsychology, 1, 72-77.
Roney-Dougal, S. M. (1982). A comparison of psi and subliminal perception: a
confirmatory study. In W. G. Roll, R. L. Morris, & R. White (Eds.), Research in
Parapsychology, 1981. Metuchen, NJ: Scarecrow Press. (pp. 96-99.)
Sargent, C. L. (1980). Exploring psi in the ganzfeld. Parapsychological Monographs
(No. 17).
Sargent, C. L., Bartlett, H. J., & Moss, S. P. (1982). Response structure and temporal
incline in ganzfeld free-response GESP testing. In W. G. Roll, R. L. Morris, & R.
White (Eds.), Research in Parapsychology, 1981. Metuchen, NJ: Scarecrow Press
(pp. 79-81).
Sargent, C. L., Harley, T. A., Lane, J., & Radcliffe, K. (1981). Ganzfeld psi-
optimization in relation to session duration. In W. G. Roll & J. Beloff (Eds.)
Research in Parapsychology, 1980. Metuchen, NJ: Scarecrow Press (pp. 82-84).
Schmitt, M., & Stanford, R. G. (1978). Free-response ESP during ganzfeld stimulation:
the possible influence of menstrual cycle phase. Journal of the American Society for
Psychical Research, 72, 177-182.
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Smith, M., Tremmel, L., & Honorton, C. (1976). A comparison of psi and weak sensory
influences on ganzfeld mentation. In J. D. Morris, W. G. Roll, & R. L. Morris (Eds.)
Research in Parapsychology, 1975, Metuchen, NJ: Scarecrow Press (pp. 191-194.)
Sondow, N. (1979). Effects of associations and feedback on psi in the ganzfeld: is there
more than meets the judge's eye? Journal of the American Society for Psychical
Research, 73, 123-150.
Sondow, N. (1987). Exploring hypnotizability, creativity, and psi: conscious and
unconscious components to psi success in the ganzfeld. In D. H. Weiner & R. D.
Nelson (Eds.) Research in Parapsychology, 1986. Metuchen, NJ: Scarecrow Press.
(pp. 42-47.)
Sondow, N., Braud, L., & Barker, P. (1981). Target qualities and affect measures in an
exploratory psi ganzfeld. In W. G. Roll, R. L. Morris, & R. White (Eds.), Research
in Parapsychology, 1980. Metuchen, NJ: Scarecrow Press (pp. 82-85).
Stanford, R. G. (1979). The influence of auditory ganzfeld characteristics upon free-
response ESP performance. Journal of the American Society for Psychical
Research, 73, 253-272.
Stanford, R. G., & Angelini, R. (1984). Effects of noise and the trait of absorption on
ganzfeld ESP performance. Journal of Parapsychology, 48, 85-100.
Stanford, R. G., Frank, S., Kass, G., & Skell, S. (1989). Ganzfeld as an ESP-favorable
setting: part II. Journal of Parapsychology, 53, 95-124.
Stanford, R. G., & Neylon, A. (1975). Experiential factors related to free-response
clairvoyance performance in a sensory uniformity setting (ganzfeld). In J. D. Morris,
W. G. Roll, & R. L. Morris (Eds.) Research in Parapsychology, 1974, Metuchen,
NJ: Scarecrow Press (pp. 89-93.)
Terry, J. C. (1976). Comparison of stimulus duration in sensory and psi conditions. In J.
D. Morris, W. G. Roll, & R. L. Morris (Eds.) Research in Parapsychology, 1975,
Metuchen, NJ: Scarecrow Press (pp. 179-181).
Terry, J. C., Tremmel, L., Kelly, M., Harper, S., & Barker, P. (1976). Psi information
rate in guessing and receiver optimization. In J. D. Morris, W. G. Roll, & R. L.
Morris (Eds.) Research in Parapsychology, 1975, Metuchen, NJ: Scarecrow Press
(pp. 194-198.)
Terry, J. C., & Honorton, C. (1976). Psi information retrieval in the ganzfeld: two
confirmatory studies. Journal of the American Society for Psychical Research, 70,
207-217.
Wood, R., Kirk, J., & Braud, W. (1977). Free response GESP performance following
ganzfeld stimulation vs. induced relaxation, with verbalized vs. nonverbalized
mentation: a failure to replicate. European Journal of Parapsychology, 1, 80-93.
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Impact of the Sender in Ganzfeld Communication 12
York, M. (1977). The defense mechanism test (DMT) as indicator of psychic
performance as measured by a free-response clairvoyance test using a ganzfeld
technique. In W. G. Roll & R. L. Morris (Eds.), Research in Parapsychology, 1975.
Metuchen, NJ: Scarecrow Press (pp. 48-49).
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Technical Final Report
APPENDIX D
Effects of the Sender on Anomalous Communication In the Ganzfeld
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Effects of the Sender on Anomalous
Communication in the Ganzfeld
Research Protocol
Charles Honorton
Psychophysical Research Laboratories
and the University of Edinburgh
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Ganzfeld Protocol
Project Overview
The objective of this project was to develop a detailed protocol for experimental
assessment of the effects of a sender on anomalous communication in a ganzfeld setting. This
objective has been realized through the completion of three tasks:
A meta-analysis of existing ganzfeld communication research was performed and used
in a statistical power analysis to estimate the sample sizes needed to reliably detect (a)
an overall anomalous communication effect and (b) a difference between sender and no
sender conditions (Honorton, 1992). Given the effect size associated with the overall
ganzfeld effect, the power analysis indicated that 95% reliability should be achievable
in studies employing at least 200 trials. The small number of studies without senders,
while limiting the usefulness of meta-analysis of sender impact from the existing data,
nevertheless indicates that overall evidence for anomalous communication in the
ganzfeld is present only in the subset of studies using senders.
Meta-analysis of moderator variables in this domain indicates a reliable correlation
between performance in anomalous communication tasks and the psychological trait of
extraversion. Less certain but reasonably consistent evidence was also found
supporting the predictive utility of abundance of self-reported anomalous experiences,
history of prior testing, involvement with mental disciplines such as meditation, and
certain other personality dimensions (Honorton, in press).
Informed by the above meta-analytic studies, development of an automated, computer-
based testing system and protocol for new studies sender effects in anomalous
communication. The testing system and protocol are described in this document.
Study Design
The basic research methodology and design comply with the PRL design described by
Honorton, Berger, et al. (1990). A new video ganzfeld control system has been developed
with modifications to enable double-blind sender comparisons. (See Video Ganzfeld System.)
New target pools have been created and coded to enable quantitative characterization of
targets. (See Target Stimuli.)
The project involves two interrelated types of studies. Novice studies provide initial training
in ganzfeld communication tasks for previously inexperienced subjects. The novice studies
form the primary basis for selecting subjects for the sender comparison study. The novice
studies are conducted in four series. In each series 50 novice subjects or receivers complete
one ganzfeld session involving full target presentation to a sender. A secondary function of the
novice series is to test refinements in predictor measures. (See Predictors.)
Successful novices will be asked to participate in the sender comparison study. Rather than
simply comparing performance with and without a sender, we have opted for a more
informative comparison of sending modes in which a sender is always physically present.
Instpastofeet for Release 20001081& :of the RER96-00787 R090309230997 Target
information available to the sender. Since we are using dynamic video stimuli, each target has

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both visual and auditory components, enabling comparison of four conditions: Video+audio
("Full target") components presented to sender, Video only, Audio only, neither component
("Null sender" condition). The specific condition for a given session is randomly selected and
unknown to either experimenter or subject until the end of the session. (See Figure 1.)
Figure 1. Study Design
SENDER COMPARISON
STUDY
NOVICE SERIES
Previously inexperienced subjects
25 subject selected from best of
Novices
1 session each following complet-
ion of personality and demo-
graphic questionnaires
Each subject contributes 2
sessions in each condition:
Assess predictors
Sender exposed to full target
Serves as screening device for
sender comparison study
Sender exposed to video
Four series, 50 subjects each
Sender exposed to audio
Sender blind to target
(null sender condition)
Video Ganzfeld System
The video ganzfeld system is a second-generation hardware/software control system for the
study of anomalous communication in the ganzfeld. It is essentially an updated version of the
PRL automated ganzfeld system (Honorton, et al., 1990), providing automated computer
control of major aspects of the ganzfeld session, including:
· Random selection of the target in novice series
· Random selection of sender condition in sender comparison series
· Automated VCR control and presentation of the target (or target element) to the sender
during sending periods
· Presentation of judging pool (target and decoys) to receiver (subject) and experimenter
during the post-session blind-judging procedure
· Presentation of judging rating scales and registration of blind-judging responses
· Data recording and storage
· Automated presentation of subject feedback following blind-judging and data recording
The system also includes modules controlling series design and subject registration which
are described below.
Hardware System
The video ganzfeld system runs under Microsoft Windows 3.1/DOS 5 on a 33MHz 80386DX
BRO 360 2360
35BS
232 serial
ports, an 80387 numeric coprocessor, and a super VGA monitor. The video subsystem has onboard
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genlock capability to enable transfer of the VGA graphics screen to an NTSC composite monitor in the
receiver's room.
The target presentation subsystem is an NEC PC/VCR, a frame-accurate NTSC videocassette
recorder with an onboard RS 232 serial interface. All VCR functions are controlled via computer
software. Custom-designed video switchng circuitry enables the computer to route VCR video and
audio signals (as well as the computer graphics screen) to any combination of the three experimental
rooms (experimenter's monitoring room, receiver's room, sender's room). Each room is equipped with
a 14 in. Panasonic color monitor and headphones.
Two audio cassette decks are used. One deck enables two-way audio communication between
experimenter and receiver, and records the receiver's mentation report during the session as well as any
interaction between experimenter and receiver. The other audio cassette deck plays prerecorded
relaxation exercises, session instructions, and white noise during the session. One-way audio
communication from receiver to sender enables the sender to monitor the receiver's mentation report
during the session. Figure 2 provides a schematic diagram of the communication flow during the
experimental session.
Figure 1. Schematic Diagram of Video Ganzfeld Communication Flow
ROOM S17B
EXPERIMENTER'S
ROOM
Switcher routes VCR
audio/video to any combination of Sender.
Receiver and/or Experimenter's rooms under
software control
AUDIO/VIDEO
SWITCHER TO
RS-232 SERIAL
PORT
PC VCR
AUDIO OUTPUT
DECK
2-way audio between E & R:
Records Receiver's mentation
& Experi-menter/Receiver
interaction
. Background music
* Relaxation exercises
· Instructions
. White noise
AUDIO
INPUT DECK
ROOM S27
SENDER'S
ROOM
ROOM S17C
RECEIVER'S
ROOM
....
1-way audio from Receiver
to Sender
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Software System
The video ganzfeld software runs under Microsoft Windows 3.1. The initial startup
sequence requires the experimenter to enter a valid security password. (See Figure 3.) The
system automatically terminates if a valid password has not been entered.
Figure 3. System Startup Sequence
Startup
UNIVERS
THE
0
Department of Psychology
Koestler Chair of
Parapsychology
Login
Password
VIDEO GANZFELD SYSTEM
Enter your password
then click 'OK'.
OK
Series Manager
Upon entry of a valid password, the Series Manager is loaded. Series Manager is
the central control program. It enables the experimenter to design new experimental
series, register new subjects, run experimental sessions, and export data files to
database management packages. (See Figure 4.)
Figure 4. Video Ganzfeld Series Manager
Video Ganzfeld Series Manager
Series
Participants Procedures Analysis
Series
Session
Date
Receiver
Sender
Sender's Relationship to Receiver
Staff member
Friend
Relative
The Series Manager menu structure is shown in Figure 5. Each of the major menu
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Ganzfeld Protocol
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Figure 5. Series Manager Menu Structure
Video Ganzfeld Series Manager
Series
Participants Procedures Analysis
List Active Serles
Series Type
Pilot
Review Completed Series
Novice
Design New Series
Experienced
Sender Comparison
Other
Video Ganzfeld Series Manager
Series
Participants
Procedures Analysis
List Current Participants
Register New Participant
Video Ganzteld Series Manager
Series
Participants
l'rocedures
Analysis
Bun Session
Judging
Abort Current Session
Session Log
Check System ...
Audio Video System
Iest ANG
Video Ganzteld Series Manager
Series
Participants Procedures
Analysis
Series Update
Create Report ...
Screen
Print
Export to database
Series
The Series menu allows the experimenter to list currently active experimental
series, review completed series, and design a new series. The Series Design option
is the most important function in this menu. It provides the only means through
which a new experimental series can be created and requires advance specification
of the study sample size (number of trials and subjects), the series type, and the
target display (sender) mode:
. Full Target: The sender will be exposed to both the video and auditory
components of the target episode
· Sender Comparison: The system randomly determines whether the sender
is to be exposed to the full target, its video component, its auditory
component, or a blank screen (null sender mode)
Data input validation routines check for inappropriate or contradictory input
(e.g., that the product of the maximum number of participants and maximum
number of trials per participant does not exceed the total number of trials). The
Series Design parameters are stored in a series startup file. The file is read into
memory when the series is selected from the Series Manager and the system
checks to insure that the specified sample size and maximum trials per subject are
not exceeded in the series.
Participants
The Series Manager Participants menu allows the experimenter to list current
participants in the selected series and to register new participants. in soppsiments
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The Participant Registration option provides the only valid means by which
new participants can enter an experimental series. Upon selecting this option, the
experimenter is presented with a dialog box which prompts him to enter the
subject's name, a unique identification (PIF) number, the participant's sex, date of
birth, source of recruitment into the study (from a standardized list), and prior
testing history. As with the Series Design dialog, data input validation routines are
used to insure appropriate input and check for contradictions (e.g., checking “No
prior testing" and one of the other prior testing options). The Series Design and
Participant Registration dialogs are shown in Figure 6.
Figure 6. Dialogs for Series Design and Participant Registration
Design New Series
SERIES TYPE
Series Name [max = 8 char.]
Pilot
Total Number of Trials
Novice
Max Number of Participants
Experienced
Max Trials per Participant
Sender Comparison
Target Display Mode
Full Target
Create Series
Cancel
Register New Participant
PIF #
Last Name
First Name
Date of Birth
[DD-MM-YY]
Testing History
Sex
Male
Female
Ganzfeld
Source of Recruitment
Other Free-Response
Volunteer
Forced-Choice
No Prior Testing
Flegister More
Cancel
OK
Procedures
The primary options available on the Procedures menu enable the experimenter
to run a session and to initiate the blind-judging procedure at the end of the
session.
When the experimenter selects "Run Session" from this menu, Series Manager
opens a Session Controller window (Figure 7).
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Figure 7. Video Ganzfeld Session Controller
Video Ganzfeld Series Manager
Series
Participants Procedures Analysis
Series
Pilot- 0.PIL
Session
Date
07-14-1992
Receiver
Sender
Session Controller
Status
Remaining Time
PC-VCR Control Panel
REW
FF
PLAY
RECORD
VER Controls
PAUSE
STOP
EJECT
Resel
POWER
lewe PC/VCR Command
Flush
The experimenter turns on the PC-VCR by clicking the "POWER" button. The
session is begun when the experimenter clicks "RUN." After randomly selecting a
target for the session, the Session controller reads a file containing the digital
addresses of each target in the pool. The program verifies that the proper
videocassette target pool has been inserted into the PC-VCR, then searches for
the target on the videocassette and places the PC-VCR into pause mode. The
system clock is used to time the onset of each of the six sending periods in the
session. Fifteen seconds prior to each sending period, the program uses the PC-
VCR character generator to display a message on the sender's monitor,
announcing that a sending period is about to begin, then displays the target on the
sender's monitor. In sender comparison studies, the system performs another
randomization to determine whether the sender will be shown the complete target,
the target video component, audio component, or a blank screen, then routes the
appropriate target element to the sender's monitor. At the end of the sending
period, the program rewinds the videocassette to the beginning of the target and
the PC-VCR is placed in pause mode. This procedure is repeated for each of the
six sending periods
The Session Controller provides the experimenter with a count down of the
number of minutes remaining in the session.
At the end of the session, experimenter and receiver, communicating via
intercom link, review the receiver's mentation. The experimenter then selects
"Judging" from the Series Manager Procedures menu and the program displays
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monitors. The four elements in the judging pool are presented in one of four
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random sequences. The receiver is prompted to identify
whatever
correspondences they perceive between their ganzfeld mentation and each of the
four potential targets. The receiver is given the option to view any or all of the
elements in the judging pool as many times as desired, then procedes to perform
the blind judging task. The program displays a judging scale (Figure 8) on the
receiver's monitor for each of the four possible targets in the judging pool. The
judging scale shows a brief descriptive name for each target, a thermometer-style
rating scale, and three buttons. Using a mini-joystick, the receiver rates the degree
of perceived similarity between each potential target and their mentation. The
scale ranges from 0% to 100% and the current value of the scale is displayed both
numerically and graphically as the receiver clicks either the left or right arrow
buttons.
Figure 8. Video Ganzfeld Judging Scale
Judging Scale
RATE TARGET:
Target Name
Press ~~ of => to rate this target.
OK
When the receiver is satisfied with the rating assigned, she or he presses the
"OK" button. The judging procedure is repeated for each of the four potential
targets in the judging pool. The program checks for tied ratings and prompts the
receiver to re-rate in the event of a tie. Once the receiver has rated all of the
elements in the judging pool, the program converts the ratings to ranks and stores
the ratings and ranks as fields in the session database record. The program
calculates a standardized rating (z-score) based on the difference between the
rating assigned to the correct target and the mean of the three decoy ratings
divided by the standard deviation of of all four ratings (Stanford & Sargent,
1983).
The program times the duration of the judging procedure from initial
presentation of the four judging pool elements to completion and adds it to the
session database record.
current session," "Session log," and "Check System." The abort session option is

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used to terminate an ongoing session prior to completion. Premature termination
of a session may only occur in the event of a protocol violation (e.g., sender or
receiver leaving their respective rooms after the beginning of the session),
equipment failure, or an emergency situation. When "Abort session" is selected,
the system displays a dialog box prompting the experimenter to enter his or her
security password and indicate the specific reason for terminating the session. This
information, along with the the participant's ID, and the date and time are written
to a series abort file. Abort session is not available after the blind judging
procedure has been completed.
Session log enables the experimenter to register comments concerning the
current session and "Check System" performs diagnostics on the audiovisual and
randomization functions of the system.
Target Stimuli
Target Pool
Following Honorton, et al., (1990), target stimuli consist of brief (35-80 sec.) video
excerpts from a variety of films and documentaries. Two target pools, each containing 40
targets (10 judging pools of four targets each), have been prepared. Each target pool is stored
on one 90-min. . 5 in. VHS videocassette tape. Digital addresses on each videocassette enable
frame-accurate access of targets via the video ganzfeld/PC-VCR computer link. A unique
digital header is recorded on each videocassette and is read by the computer at the onset of
each experimental session. Accidental insertion of a videocassette other than that containing
the designated target pool is automatically detected and results in termination of the session.
Based on an analysis of target success-rates in the PRL experiments, approximately half of
the targets were taken from among the most successful PRL dynamic targets. The remainder
of the targets are new. Pool A will be exclusively used for the Novice Screening Series and
Pool B will be used for the Sender Comparison Series. Since the latter series will include
sessions in which the sender will be exposed only to the audio soundtrack portion of the
target, the elements in Pool B include a high proportion of targets with descriptive narration.
Measurement of Target Attributes
The quantification of complex target material has long eluded investigators of anomalous
communication. The quantitative characterization of target attributes is important for a
number of reasons, for example:
· Development of more statistically powerful methods for assessing target/description
correspondences,
· Detection and elimination of targets associated with strong response bias (i.e., targets
that tend to be selected or rejected because of their intrinsic characteristics),
· Detection and elimination of targets that activate perceptual defense,
. Identification of targets that are exce
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· Identification of elements of target environments that may be especially amenable to
retrieval via anomalous communication.
Recently, major advances have been made with regard to certain aspects of this problem as
it specifically applies to remote viewing studies (May, et al., 1985; 1990). While aspects of
May's conceptual schema can also be applied to ganzfeld research, there are two aspects of
the latter that call for a somewhat different approach: (1) The standard ganzfeld mentation
protocol focuses upon the elicitation of unconstrained spontaneous imagery rather than an
explicit focus upon describing the target. (2) The video targets are themselves quite different
from those typically used in remote viewing research: They include auditory components (e.g.,
music, dialogue, narration, sound effects), occasionally major transitions in perspective, highly
evocative dramatic and comedic scenes, etc.
For these reasons, we have adopted a somewhat different approach, consisting of two
distinct aspects: (1) Specific descriptors tailored to the content of the target pools, and (2)
generic characteristics derived from environmental psychology.
Content-based Descriptors
Each target has been coded with respect to Theme, Tone, and Content. Each item is coded
Table 1. Content-based Descriptors
Nature/wildlife
Fantasy/religion/mythology
THEMES
Aggression/battles/warfare/conflict
Social interactions
Sports/athletics/acrobatics
Art/dance/music
Places/travel/exploration
Cartoons/animation
Humor
Documentary
Action
Drama
Wonderment/awe
Light entertainment
CONTENT
People
Animals
Fantasy/mythical characters
Water
Rocks/hills/mountains
Trees/flowers/foliage
Land vehicles/scenes
Terrestrial flight scenes
Underwater vehicles/scenes
Architecture/urban scenes
Technology/objects/devices/tools
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Space/planets galaxies
Music
TONE

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on a four-point scale, where 0 = absent, 1= present, 2= prominent, and 3=dominant. (See
Table 2). The content-based descriptors are used (a) in construction of orthoginal judging
pools and (b) in exploratory analysis of target attribute correlates of anomalous
communication.
Generic Characterization of Targets based on
Environmental Psychology Approaches
The above approach represents what Mehrabian and Russell (1974) describe as "the most
common, but least parsimonious, approach ... the use of the everyday language of specific
events and entities" (p. 6). They point out that this approach does not permit comparison
across environments, " ... and it is impossible to analyze behavioral changes as functions of
changes in environments so described" (p. 6). Mehrabian and Russell survey a wide array of
evidence pointing to the advantage of generic characterization of environments in terms of the
primary emotional responses they elicit and a (psychologically-based) measure of information
rate. Their general framework is illustrated below in Figure 9.
Figure 9. Mehrabian & Russell Framework for Characterizing Environments
THE ENVIRONMENT
Sense modality variables
(e.g., color and temperature)
BEHAVIORAL
RESPONSES
Information rate
(characterizing the spatial and
temporal relationships among
the stimulus components of
an environment)
PRIMARY
EMOTIONAL
RESPONSES
Approach-avoidance
Pleasure
Arousal
Dominance
(which includes physical
approach, exploration,
affiliation, performance,
or other verbal and non-
verbal communications
of preference)
Characteristic emotions
associated with
PERSONALITY
After Figure 1.1 of Mehrabian & Russell (1974).
Within this framework, environments are coded using semantic differential scales measuring
the three primary emotional responses (pleasure or evaluation, arousal or activity, dominance
or potency) and information rate. The scales are reproduced in the appendix. Each of the
targets has been coded on these four scales. We believe that this approach may provide a basis
for broader comparison across laboratories and target sets than more traditional methods. It of
course remains to be seen how useful it will be as a predictor of success in anomalous
communication.
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Predictor Measures
Extraversion and Openness to Experience
Performance in anomalous communication tasks has been found to correlate with the
psychological trait of extraversion in a recent meta-analysis of 15 studies by five independent
investigators (Honorton, Ferrari, & Bem, 1990). The mean correlation is small (r = . 20) but
consistent across investigators, studies, and personality measures.
While the meta-analysis provides strong evidence that a relationship exists between
anomalous communication and extraversion, it is silent as to the nature of the relationship.
Extraversion is commonly associated with sociability (gregariousness), but it is now known
that there are at least five other components of extraversion. For this reason, we have chosen
the NEO Personality Inventory (Costa & McRae, 1985), an instrument that measues six facets
of extraversion. Recent research implicates sensation seeking as an instrumental factor in the
ganzfeld experience (Glicksohn, 1991) and we are especially interested in the possibility that it
also correlates with performance in anomalous communication tasks. We also will use the
NEO PI Openness scale, and its six facets, because a number of studies have indicated a
relationship between anomalous communication and various measures of openness to
experience. Table 21ists the six facets of extraversion and openness.
Table 2. Facets of Extraversion and Openness
Scale
Facet
1.
Warmth
2.
Gregariousness
3.
Assertiveness
EXTRA VERSION
4.
Activity
5.
Excitement Seeking
6.
Positive Emotions
1.
Fantasy
2.
Aesthetics
3.
Feelings
OPENNESS
4.
Actions
5.
Ideas
6.
Values
A computer program scores the questionnaire and presents graphic profiles for each of the
six facets of extraversion and openness. Statistical power analysis (Cohen, 1977) indicates that
a sample size of 200 subjects will achieve a 90% likelihood of detecting a correlation of .2 at
p <. 05. With N≥200, the critical value of r (p≤.05) is within the 95% CI of the meta-analysis.
Other Moderators
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Meta-analysis of three novice experiments in two independent laboratories indicates that
initial anomalous communication performance in the ganzfeld is related to four other factors
(Honorton, in press):
· The number of types of personal "psychic" experiences subjects believe they have had,
Experience with mental disciplines such as meditation,
· Classification as Feeling/Perception on the Myers-Briggs Type Indicator, and
.
Prior formal testing involving anomalous communication tasks.
Across the three studies, only 15 subjects (about 5%) satisfied all four predictors, but 11 of
them successfully identified their targets (effect size = 1.03). When the least frequently
satisfied condition (prior testing) was eliminated, 99 subjects in the three studies satisfied the
remaining three predictors, with an effect size of .39. Subjects who did not satisfy the three-
predictor model (N = 190) produced a nonsignificant effect size of .07.
Myers-Briggs Feeling/Perception is highly correlated with the NEO Openness Scale used in
this study. We have developed more refined items regarding reported personal anomalous
experiences, prior laboratory testing, and mental disciplines. Prior to contributing to the novice
series (total N = 200), subjects will complete the NEO-PI Extraversion and Openness scales
and a demographic survey incorporating measures of personal experiences and prior testing. If
the predictive utility of these factors is confirmed in the new novice series, a composite
predictor measure will be used in addition to novice target acquisition to select subjects for the
sender comparison study.
Subjects
Previous research also indicates that artists and musicians are particularly successful in
anomalous communication tasks (Schlitz & Honorton, 1992). For this reason, we will recruit
as many subjects as possible from University music and arts departments and local creative and
performing arts groups.
References
Cohen, J. (1977). Statistical power analysis for the behavioral sciences (rev. ed.). New York:
Academic Press.
Costa, P. T., & McRae, R. R. (1985). The NEO Personality Inventory manual. Psychological
Assessment Resources, Inc.
Glicksohn, J. (1991). The induction of an altered state of consciousness as a function of
sensory environment and experience seeking. Personality and Individual Differences, 12,
1057-1066.
Honorton, C. (1992). Impact of the sender in ganzfeld communication: meta-analysis and
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power estimates. Report to
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Ganzjela Protocol
Honorton, C. (in press). The ganzfeld novice: Four predictors of initial ESP performance.
Proceedings of the 35th Annual Convention of the Parapsychological Association.
Research Triangle Park, NC: Parapsychological Association.
Honorton, C., Berger, R. E., Varvoglis, M. P., Quant, M., Derr, P., Schechter, E. I., &
Ferrari, D. C. (1990). Psi communication in the ganzfeld: Experiments with an automated
testing system and a comparison with a meta-analysis of earlier studies. Journal of
Parapsychology, 54, 99-139.
Honorton, C., Ferrari, D. C., & Bem, D. J. (1990). Extraversion and ESP performance: A
meta-analysis and a new confirmation. Proceedings of the 33rd Annual Convention of the
Parapsychological Association. Research Triangle Park, NC: Parapsychological
Association, 113-125.
May, E. C., Humphrey, B. S., & Mathews, C. (1985). A figure of merit analysis for free-
response material. Proceedings of the 28th Annual Convention of the Parapsychological
Association. Research Triangle Park, NC: Parapsychological Association, 343-354.
May, E. C., Utts, J. M., Humphrey, B. S., Luke, W. L. W., Frivold, T. J., & Trask, V. V.
(1990). Advances in remote-viewing analysis. Journal of Parapsychology, 54, 193-228.
Mehrabian, A., & Russell, J. A. (1974). An approach to environmental psychology.
Cambridge: MIT Press.
Schlitz, M. J., & Honorton, C. (1992). Ganzfeld psi performance within an artistically gifted
population. Journal of the American Society for Psychical Research, 86, 83-98.
Stanford, R. G., & Sargent, C. L. (1983). Z scores in free-response methodology: Comments
on their utility and correction of an error. Journal of the American Society for Psychical
Research, 77, 319-326.
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Appendix
Semantic Differential Scales Used for Generic Target Characterization
(Mehrabian & Russell, 1974)
I. Primary Emotional Responses
Instructions: Take a few moments to really get into the mood of the situation depicted
in the target episode; then rate your feelings in the situation with the adjective pairs below.
Some of the pairs might seem unusual, but you'll probably feel more one way than the
other. So, for each pair, put a check moark close to the adjective which you believe to de-
scribe your feelings better. The more appropriate the adjective seems, the closer you put
your check mark to it.
TARGET NAME
TAPE
TAPE ADDR. (START : END)
RATER
EVALUATION
Happy
Unhappy
Pleased
Annoyed
Satisfied
Unsatisfied
Contented
Melancholic
Hopeful
Despairing
Relaxed
Bored
ACTIVITY
Stimulated
Relaxed
Excited
Calm
Frenzied
Sluggish
Jittery
Dull
Wide-awake
Sleepy
Aroused
Unaroused
POTENCY
Controlling
Controlled
Influential
Influenced
In control
Cared-for
Important
Awed
Dominant
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Il. Information Rate
Instructions: Please use the following adjective pairs to describe the situation depicted
in the target episode. Each of the following adjective pairs helps define the situation or the
relation among the various parts of the situation. Put a check mark in one of the boxes to
indicate what you think is an appropriate description.
Varied
Redundant
Simple
Complex
Novel
Familiar
Small-scale
Large-scale
Similar
Contrasting
Dense
Sparse
Intermittent
Continuous
Usual
Surprising
Heterogeneous
Homogeneous
Uncrowded
Crowded
Asymmetrical
Symmetrical
Immediate
Distant
Common
Rare
Patterned
Random
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Technical Final Report
APPENDIX E
A Preliminary Study of Anomalous Perception During Lucid Dreaming
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A PRELIMINARY STUDY OF ANOMALOUS PERCEPTION DURING LUCID DREAMING1
Stephen LaBerge, Ph.D.
The Lucidity Institute, Inc.
Several studies (reviewed in Child, 1985) have found evidence supportive of the existence of
anomalous perception in dreams. The protocols for attempting to elicit anomalous perception in
dreams fall into three main categories.
The first type, which has accumulated the larget amount of data, referred to by Child as
"general ESP," is known in the popular literature as "dream telepathy." This entails the use of two
research subjects, a "sender" and a "receiver." The sender subject concentrates on target
information while the receiver subject is in REM sleep, presumably dreaming. The subject's
dream content report is later analyzed for correspondence with the target information.
The second category is "precogntion," anomalous perception of future events. In these
studies, the sender subject does not select or concentrate on the target until the receiver subject
has already attempted to dream about and report on it.
The third type of dream anomalous perception, of most relevance to the present
investigation, is called "clairvoyance," referring to the information acquired without a human
"sender" intermediate. The protocol requires that the information in the target is not known to
the experimenters, so that none could inadvertently act as a "sender."
The use of lucid dreaming to study "clairvoyant" type anomalous perception in dreams may
enhance the subjects' ability to acquire accurate information about a remote target. Lucid
dreaming is dreaming with awareness that one is dreaming (LaBerge, 1985). In the lucid dream
state, one can deliberately alter the course of the dream according to one's intentions. Thus, a
subject attempting to "see" a target photograph could decide in a lucid dream to seek out a dream
image of the target, rather than relying on the possibility of the target spontaneously appearing in
the dream. Lucid dreaming anomalous perception trials might be more similar to waking
anomalous perception trials in that in both the subject makes a deliberate attempt to concentrate
on and describe a remote stimulus.
This pilot experiment was designed to explore the potential for using the REM lucid
dreaming state (dreaming while knowing that one is dreaming) for anomalous perception.
Procedure
Training in Lucid Dreaming
The general strategy of this pilot study called for subjects to induce lucid dreams in which they
dream about Remote Viewing (RV) targets (National Geographic scenes sealed in opaque
envelopes). Thus, training in lucid dreaming was the first step.
The subjects were selected from 1) subjects in previous RV studies who had demonstrated
above normal RV capability (source: SAIC), and 2) subjects who had in prior studies shown
above normal ability to induce lucid dreams (LD) (source: LI). The previous RV subjects were
1FINAL REPORT: SAIC SUBCONTRACT NO. 29-92-0085-71
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compensated according to existing contracts with SAIC. The LD subjects participated as
volunteers.
All subjects received two forms of training in lucid dreaming: 1) They were provided with a
home-study course in lucid dreaming developed by the Lucidity Institute. 2) They attended two
weekend seminars. The first seminar introduced subjects to lucid dreaming skills and the use of
the DreamLight lucid dream induction device, which has been shown to effectively enhance the
frequency of lucid dreaming in previous studies.
Lucid dreaming RV trials
While practicing lucid dream induction techniques and using DreamLights, subjects attempted to
show RV in lucid dreams using the following procedure. At the first seminar each subject received
a sealed opaque envelope containing a target photo, which had been selected from sets of five
orthogonal National Geographic scenes. Subjects were asked place the target envelope in the
bedroom in which they were sleeping, to induce lucid dreams using the DreamLight, and to
attempt to locate the target envelope in a lucid dream. In the lucid dream they were to try to
open the envelope and examine its contents. Upon awakening they were to describe in detail
(with words and pictures) what they had seen. The target description and the target envelope
(unopened) were then sent to Dr. Edwin C. May at SAIC for analysis. Upon receipt, Dr. May sent
back the target photograph (for feedback) along with another sealed target envelope. The
procedure was repeated for as many trials as the subjects could complete during the six month
pilot study period.
!
The coded lucid dream target viewing reports were given to a judge blind to which who rank
ordered each set of five orthogonal scenes including the target for degree of correspondence with
the lucid dream report. Another judge rated each set of five targets for quality of correspondence
of the description given in the report, using an 8 point scale (see Table. 1).
Table 1. Quality Scale
0
No correspondence.
1
Little correspondence.
2
Some correct elements, but not sufficient to suggest results
beyond chance expectation.
3
Mixture of correct and incorrect elements, but enough of the
former to indicate viewer has made contact with the site.
4
Good correspondence with several matchable elements
intermixed with incorrect information.
5
Good correspondence with unambiguous unique matchable
elements, but some incorrect information.
6
Good correspondence with good analytical information and
relatively little incorrect information.
7
Excellent correspondence, including good analytical detail, with
essentially no incorrect information.
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Results
Seven subjects successfully completed at least one trial, visiting, viewing and reporting on the
appearance of the target in a lucid dream. Four subjects were from the RV group and three were
from the LD group. Three subjects were female, four male. Data was collected from 21 trials.
Individual subjects contributed 1-7 trials each (mean=3).
Rank order
See Table 2 and Figure 1 for the distributions of rank orders for Targets and Non-targets.
Examination of Figure 1 suggests that Non-target ranks were randomly distributed, while Targets
showed higher ranks than expected by chance. Sum of ranks statistics were computed for the
combined trials (N=21) and also for individual subjects. For individual subject statistics, see
Table 3. For the combined trials (N=21), a moderate effect size was obtained: ES=0.368 (z=1.685,
p =. 046).
Table 2. Distribution of rank orders for targets and non-targets.
Rank
Target N
% Targets
Non-target N
% Non-targets
1
7
33%
14
17%
2
5
24%
16
19%
3
3
14%
18
21%
4
4
19%
17
20%
5
2
10%
19
23%
50
45 -
Targets
40
Non-targets
35
30-
Percent
25
20
15.
10-
5-
1
2
3
4
5
Rank
Figure 1. Rank orders for Targets vs. Non-targets. Dotted line represents theoretical (20%).
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Table 3. Rank statistics by subject.
Subject
Number
of Trials
Mean
Rank
Effect
Size
₱
Z
1
7
3.00
0.000
0.552
0.000
2
1
2.00
0.707
0.400
0.707
3
2
1.00
1.414
0.040
2.000
4
2
3.00
0.000
0.600
0.000
5
3
1.67
0.943
0.080
1.633
6
1
1.00
1.414
0.200
1.414
7
5
3.00
0.000
0.561
0.000
Quality scores
Table 4 shows the distribution of quality (correspondence with report ) scores for the Target and
Non-target groups. The median values of quality scores were higher for Targets (median=2) than
for Non-targets (median=1).
The distributions of Target and Non-target quality scores (see Figure 2) significantly differed
(Kolmogorov-Smirnov test, p <. 05; Mann-Whitney U-test, z=2.14, p <. 03). Compared to Non-
targets, Targets were 3.4 times more likely to be rated 3 (" ... contact with the site.") or above
(Targets: 10/21=48%; Non-targets: 12/84=14%; Fisher's Exact Test, p =. 0019).
Table 4. Distribution of Quality Scores for targets and non-targets.
Quality
Target N
% Targets
Non-target N
% Non-targets
0
5
24%
30
36%
1
4
19%
21
25%
2
2
10%
21
25%
3
6
29%
6
7%
4
1
5%
5
6%
5
1
5%
0
0%
6
1
5%
1
1%
7
1
5%
0
0%
:
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40-
C
Targets
Non-targets
30-
Percent
20-
10-
[
0-
T
0
1
2
3
4
5
6
7
Quality
Figure 2. Quality Scores: Targets vs. Non-targets.
Three of the four RV subjects produced target viewing reports scoring 3 or better on quality,
as did all three of the LD subjects. The sample size is too small to allow comparisons between the
two groups.
Discussion
This study of the ability of people to report details of an unknown visual target examined
remotely during the lucid dream state has shown promising results. The correspondence between
the images of targets viewed in dreams and the actual target photographs was frequently enough
greater than expected by chance to suggest a genuine transmission of information. The moderate
to large effect sizes obtained in this preliminary study compare favorably to those acquired in
other investigations demonstrating the remote viewing phenomenon (E. May & W. Luke,
personal communication, 1992).
The sample size for this experiment was too small to be the basis for conclusions about the
effectiveness of RV attempts in waking versus lucid dreaming. It can be said, however, that the
lucid dream state allows access to this type of anomalous cognition. An example of a top ranking,
high quality target "hit" will serve to demonstrate the nature of information acquired through AC
in a lucid dream.
This trial was by a skilled lucid dreamer (S5) with no prior experience as a remote viewing
subject. He slept with the target envelope in his bedroom. His report states,
"I realized I was dreaming [because X and Y were there; actually they are in Alaska]. The
dream began to fade. I spun [technique for prolonging a dream] and arrived in my
bedroom. The envelope was there, thick with much tape. I tore it open and dumped the
contents on the bed. There were lots of odds and ends, which I decided to ignore, looking
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PRELIMINARY STUDY OF ANOMALOUS PERCEPTION IN LUCID DREAMS
6
only for the picture. I found the black paper [included in each envelope to prevent seeing
target through envelope] and a slip of paper with the picture below."
SANDY, PATCHY, DARK, LIGHT
Figure 3. Report picture for target shown in Fig. 4 (S5, Trial 2).
The actual target photograph was of a high sandy dune desert with extremely contrasting
patches of dark and light. The ("SANDY, PATCHY, DARK, LIGHT") pattern in the subject's
drawing matches that of the target. A reproduction of the target appears in Figure 4 below.
CPYRGHT
Figure 4. Reproduction of target photo [10(4)] for report shown in Fig. 3 (S5, Trial 2).
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PRELIMINARY STUDY OF ANOMALOUS PERCEPTION IN LUCID DREAMS
Several indications that certain features of lucid dream RV attempts tended to accompany
successful trials appeared in the content of the lucid dream reports. Among these were: veridical
dream representations of the subject's bedroom and the target envelope, the augmentation of
pictorial information with written words or phrases and the assistance of dream characters
helping the subjects to focus on the important elements of the dream imagery. To determine if
these or other aspects of lucid dreaming trials are truly important for success, future experiments
will direct and organize the subject's post trial reports with standardized questionnaires.
One reason for the small sample size in this study is the difficulty of training people to have
lucid dreams at home. Subjects would be likely to produce more lucid dreams when sleeping the
laboratory with stimuli applied while the subjects are in REM sleep to cue them to become lucid.
Furthermore, the sleep laboratory situation would enable the experimenters to awaken subjects
immediately after their lucid dream trials to collect the best possible reports of the dream target
viewing. Therefore, it is recommended that subsequent studies of RV in the lucid dream state be
conducted in a sleep laboratory with physiological monitoring of the parameters necessary for
determining sleep states. This would also permit analysis of the EEG and other physiological
measures that may correlate with successful RV.
References
Child, I.L. (1985). Psychology and anomalous observations: The question of ESP in dreams.
American Psychologist, 40, 1219-1230.
LaBerge, S. (1985). Lucid dreaming. Los Angeles: J.P. Tarcher.
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APPENDIX F
.
Possible Effect of Geomagnetic Fluctuations on the
Timing of Epileptic Seizures
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Methods
Patients
Seizure data consisting of dates, and in some cases times and dates, of seizures were
obtained for a total of 22 patients. Data for patients 1 through 17 were collected from a study
of the statistics of seizure timings.1 This data, referred to as TLG, comprised diaries of
patients on a stable regimen of antiepileptic medication who recorded the daily number of
seizures along with details of unusual activities, stress and alcohol consumption. In the TLG
study, data from three patients was split into subsets due to medication changes, loss of data
recording for a period, or intervening surgery. In this study these patients' data was treated as
a unit, identically to the other patients' data, since there was no a priori reason to expect that
the data subsets used would show a differentiation of response to GMF variations. The
remaining five patient's data was collected for this study and was more heterogeneous.
Patient RR1 had all seizures recorded by her parents during a 4 month period under medical
supervision but prior to medication being prescribed. After being administered sodium
valproate her seizures stopped. Patients NE1 to NE3 had their seizures recorded partly as
in-patients and partly at home. The completeness of these recordings is not known. Finally
patient WO1's seizures were recorded by a family member during two periods and are
thought to constitute a complete and accurate recording. All seizures submitted were included
in the analysis, except those which occurred after September 30th 1991 when ap index data
was not available. The clinical data is summarized in table I.
Insert table 1 about here
Geomagnetic Field Data
The 3 hour geomagnetic ap index16 was used as the primary measure of GMF activity.
This index provides an estimate of the range of variation of the intensity of the GMF, in nT,
during a 3 hour interval of universal time (UTC). The index is also a spatial average across
the globe; the actual range of field strength variation observed at any location may be greater
than the ap range at high latitudes and smaller at low latitudes. The ap index is an integer
value in the range [0, 400] with the variance of the index increasing during magnetic storms.
Since this behavior can violate assumptions of homogeneity of variance needed for t test used
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here, the ap index data was log transformed before the analysis. Owing to the persistence of
the interplanetary particle storms responsible for the larger GMF disturbances, 3 hour and
daily geomagnetic indices are auto-correlated. For instance the Ap daily index, consisting of
the mean of the eight ap values for the day, has a Pearson correlation of r = 0.48 for data for
1980 though 1990 at one day's lag. This auto-correlation may ameliorate the effect of the
lack of time of day information for some of the seizures.
Analysis
Since the majority of the seizures (3307 out of 4101) lacked time of day information,
the temporal unit for the analysis was taken as a day and an index of geomagnetic activity for
the day preceding the seizures was developed. The seizures for which a time of day had not
been recorded were assigned to have occurred at 12 noon local time. This procedure results
in a maximum error in the seizure time of 12 hours. All seizure times and dates were adjusted
to UTC allowing for time zones and summer time where necessary. The average ap for the 24
hour period preceding the seizure was calculated by computing the mean of the (log
transformed) ap values for the 3 hour UTC interval during which the seizure occurred and for
the 7 preceding 3 hour intervals. The average daily indices for the previous days were
computed similarly. The mean daily Ap index on the seizure day was compared with that for
preceding two days with paired t tests of the log transformed indices. All statistical tests were
calculated using SPSS-X software.
-.
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Results
GMF activity on the seizure days was compared with the activity of preceding days
for the group of patients as a whole and for each patient separately. Grouping the data, the Ap
index on the seizure day, 16.41 ± 20.2 nT, was slightly greater than for the preceding day,
16.01 ± 20.3 nT, (t [4100] = 1.84, p = 0.03). The index for the day prior to this, 16.09 ±
19.9 nT, was not significantly different from the seizure day (t [4100] = 0.55, p = 0.3).
Neither was the index for the 10 days preceding the seizure, 16.43 ± 11.2 nT, significantly
different from the seizure day index (t [4100] = 0.78, p = 0.2). The seizure diaries were
recorded during intervals spanning the years 1977 to 1991 and covering more than one 11
year cycle of solar activity. Thus some diaries were recorded at periods of higher average
GMF activity than others. For instance the mean Ap index for the 10 days prior to the seizure
days for patient NE1 was 35.7 ± 16.9 nT, while that for TLG12 was 7.93 ± 2.1 nT. With the
data combined into a single data set, GMF index changes between days will be masked by
the large differences between the mean indices for the diaries. To avoid this, the differences
in GMF index data between seizure and earlier days were analyzed for each patient separately.
The results are shown in table II. The overall deviation from chance expectation for the group
of patients can also be calculated from the individual patient's statistics by converting the t
values to 1-tailed p values and then to z - scores which were combined by Stouffer's method.
By this method, the Ap index for the seizure day was significantly greater than on the
preceding day, (z = 2.48, p = 0.007) and greater, but not significantly so, than for the second
day prior to the seizures (z = 1.21, p = 0.1), and for the mean daily index for the preceding 10
days (z = 1.08, p = 0.1). There is a wide range of patient t values (-2.59 ≤ t ≤2.89) present in
the data. To analyze inter-patient differences, a measure of the difference in Ap index
between the seizure days and the preceding days for each patient was defined which is
independent of the number of seizures. The effect size r = z / \n is such a measure, where z is
the equivalent z - score for each patient's t value as computed above and n is the number of
seizures recorded in the patient's diary. The overall effect size for the set of patients can be
estimated as the weighted mean of the effect sizes and was found to be ur = 0.029 ± 0.016.
This sample of 22 effect sizes was found to be inhomogeneous (x 2 [21] = 33.3, p = 0.04)
suggesting that the types of seizure or treatments represented in this data may exhibit
intrinsically different responses to geomagnetic variations.
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Insert table 2 about here
To investigate whether seizure type, sex and age of patients, or seizure frequency were
significant moderating variables for the difference between Ap values on the seizure day, a
linear regression was calculated between these variables and the patient effect size r. Using
dummy variables for sex and seizure type, the regressions revealed no significant loadings for
any of the variables. Given the small number of patients in the study the power of this
analysis to uncover any real effects, if they exist, is small. It is perhaps worth noting that the
two patients who were unmedicated for at least part of the time of seizure data collection had
relatively large effect sizes (RR1, r = 0.24 and WO1, r = 0.17, ur = 0.029 ± 0.016).
.
.
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Discussion
The hypothesized association between epileptic seizure occurrence and increased
GMF activity on the seizure day was confirmed in this data. However the observed effect size
for the interaction was very small (r = 0.03). For comparison Cohen17 classifies effect sizes
of less than 0.2 as small. Although this result has confirmed the earlier studies as regards the
existence and direction of the GMF - seizure effect, the very small effect size observed and
the absence of an established theoretical background for very low frequency EM fields as
seizure promoters suggest that the present result should be treated cautiously. However the
inhomogeneity of the sample of effect sizes suggests that there are uncontrolled factors
effecting the interaction between GMF fluctuation and seizure occurrence. Whether these
factors are characteristics of the patients or possibly of other environmental stimuli could not
be determined in this study.
Research in neurobiology in general and epileptology in particular involves the almost
impossible task of differentiating direct from indirect effects. Such unusual phenomena as
seizures induced by tooth brushing or the smell of perfume but not foul odors exemplify the
specificity of triggers in particular patients. Moreover, more general phenomena such as
stress itself have been noted to increase the risk of seizures in many. These non-specific
triggers may play only indirect roles by pathophysiologic cascades influencing
neurotransmitter systems or electrical firing. Such phenomena18 are even more difficult to
determine because they may effect only a small proportion of epileptics.
These comments clearly have relevance with regard to geomagnetic influence. This
could conceivably correlate with weather patterns. Cloudiness has been regarded as a
possible correlate with depression. Heat intolerance can cause irritability. Indirect
geomagnetic influences may turn out impossible to differentiate from direct ones but may
lessen the power of tests to quantify statistically as other influences may also be confounding
issues. Moreover, we know that certain patients may have their seizures triggered by events
which do not influence others. Consequently, geomagnetism may play a role in a small
proportion of patients and such actors as anticonvulsants may prevent this role powerfully.
Thus, the profound results with the limited medicated patients may not be coincidental and
serves as an excellent group for further research.
The decision not to control for anticonvulsant blood levels in our subjects merits
further comment. Although serum concentrations of agents known to be pharmacologically
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active against seizures might appear to be the single most important variable affecting seizure
frequency, there are several reasons for believing that this is probably not the case. In the
majority of patients, anticonvulsant levels remain stable over time, especially when
medications are administered chronically. Furthermore, except in cases of rapid medication
withdrawal or extreme toxicity, there is little evidence for a one-for-one relationship between
serum level and seizure frequency. Lastly, it is well known that patients respond differently at
similar serum concentrations, and thus for any given concentration, some patients will seize
and others will not. Furthermore patients TLG1 to TLG17 had their antiepileptic drug levels
measured at least once during the study with serum concentrations within the therapeutic
range. Multiple blood samples were drawn from patients TLG1, TLG4 and TLG6 and no
significant changes in the serum concentrations were observed and no relation to seizure
frequency could be demonstrated. We therefore could not justify the added time and expense
associated with frequent serum anticonvulsant determinations in all patients.
Many avenues of further investigation exist. If the seizure promoting effect of GMF
fluctuations is really due to very low frequency EM, a relationship between magnetic latitude
and effect size might be expected, since the amplitude of geomagnetic disturbances generally
increase at higher latitudes. Recently Randall19 reported just such a latitude dependence in
correlations between GMF disturbance and conception rate. Unfortunately the seizure data
studied here come from only four locations, with 17 of the 22 patients at just one latitude.
Thus the question of latitude dependence cannot be tested with this data. Another promising
approach would involve studying epileptic seizures in a medical facility, where precise
timings of seizures and EEG monitoring and seizure detection was possible. Such
observations combined with broad spectrum measurements of low frequency EM field
excursions might answer the question of electromagnetic stimulation of epileptic seizures.
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Acknowledgments: We thank Drs. Ed May and Jessica Utts for assistance with the statistical
design and Ms. Sarah Ryer for providing the original stimulus for this research.
1
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REFERENCES
1
Taubøll E, Lundervold A, Gjerstad L. Temporal distribution of seizures in epilepsy. Epilepsy
Res 1991; 8: 153-65.
2
Milton JG, Gotman J, Remillard GM, Andermann F. Timing of seizure recurrence in adult
epileptic patients: a statistical analysis. Epilepsia 1987; 28(Pt 5): 471-8.
3
Binnie CD. Are biological rhythms of importance in epilepsy. In: Martins da Silva A, Binnie
CD, Meinardi H, editors. Biorhythms and Epilepsy. New York: Raven Press, 1985: 1-11.
4 Matsushita S, Campbell WH, editors. Physics of geomagnetic phenomena, International
Geophysics Series Vol. 11, Academic Press, 1967.
5
Adey WR. Tissue interactions with nonionizing electromagnetic fields. Physiol Rev 1981;
61: 435-514.
6
Marino AA, Becker RO. Biological effects of extremely low frequency electric and magnetic
fields. Physiol Chem Phys 1977; 9: 131-47.
7
Venkatraman K. Epilepsy and solar activity - an hypothesis. Neurol India 1976; 24: 1-5.
8
Rajaram M, Mitra S. Correlation between convulsive seizure and geomagnetic activity.
Neurosci Lett 1981; 24: 187-91.
9
Keshavan MS, Gangadhar BN, Gautam RU, Ajit VB, Kapur RL. Convulsive threshold in
humans and rats and magnetic field changes: observations during total solar eclipse.
Neurosci Lett 1981; 22: 205-8.
10 Persinger MA. Increased geomagnetic activity and the occurrence of bereavement
hallucinations: evidence for melatonin mediated microseizuring in the temporal lobe?
Neurosci Lett 1988; 88: 271-4.
11 Ruhenstroth-Bauer G, Baumer H, Kugler J, Spatz R, Sonning W, Filipiak B. Epilepsy and
weather: a significant correlation between the onset of epileptic seizures and specific
atmospherics - a pilot study. Int J Biometeorol 1984; 28: 333-40.
12 Juutilainen J, Bjork E, Saali K. Epilepsy and electromagnetic fields: effects of simulated
atmospherics and 100 Hz magnetic fields on audiogenic seizure in rats. Int J Biometeorol
1988; 32: 17-20.
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13 Ossenkopf K-P, Cain DP. Inhibitory effects of acute exposure to low-intensity 60-Hz
magnetic fields on electrically kindled seizures in rats. Brain Res 1988; 442: 255-60.
14 Adair RK. Constraints on biological effects of weak extremely-low-frequency
electromagnetic fields. Phys Rev A 1991; 43(Pt 2): 1039-48.
15 Bucha V. Solar and geomagnetic variability and changes of weather and climate. J Atmos
Terr Phys 1991; 53(Pt 11): 1161-72.
16 Mayaud PN. Derivation, meaning, and use of geomagnetic indices. Geophys Monogr Ser
1980; 22: 1-154.
17 Cohen J. Statistical power analysis for the behavioral sciences. Hillsdale: Lawrence Erlbaum
Associates, 1988.
18 Neppe VM, Tucker GJ. Neuropsychiatric aspects of seizure disorders. In: Yodofsky SC,
Hales RE editors Textbook of Neuropsychiatry, 2 nd. Ed, Washington D.C .: American
Psychiatric Press, pp 397-426.
19 Randall W. The solar wind and human birth rate: a possible relationship due to magnetic
disturbances. Int J Biometeorol 1990; 34: 42-8.
£
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TABLE 1 -- CLINICAL DATA
:
Patient ID
Sex
Age
Seizure Type*
Medication
TLG1
M
48
GTC
PTH
TLG2
F
40
CPS + 2° GTC
CBZ
TLG3
M
28
CPS
CBZ + VPA
TLG4
M
31
CPS
PHT + CBZ
TLG5
F
36
A
PRIM + PB + (CZP)
TLG6
M
29
CPS
CBZ + PHT
TLG7
M
4
SPS + 20GTC
CBZ + PHT
TLG8
F
40
GTC
PHT
TLG9
M
22
CPS + 2° GTC
VPA
TLG10
F
34
SPS + 2º GTC
VPA
TLG11
M
14
CPS + 2° GTC
CBZ + VPA + NZP
TLG12
F
21
CPS + 2º GTC
CZP
TLG13
F
26
SPS
CBZ
TLG14
F
34
CPS
PHT + PB + CBZ
TLG15
M
44
CPS
PHT + PB + CBZ
TLG16
F
52
CPS
PRIM + CBZ
TLG17
F
49
CPS
PHT
RR1
F
5
A
UM
NE1
M
1
IS + CPS
ACTH + VPA
NE2
F
7
CPS + 2° GTC
DPH + CBZ
NE3
F
26
GTC
DPH
WO1
F
31
CPS
UM, VPA
*Seizure types are designated: A, absence seizure; CPS, complex partial seizure; GTC, gen-
eralized tonic-clonic seizure; 2º GTC, secondary generalized tonic-clonic seizure; IS, infan-
tile spasms; SPS, simple partial seizure.
¡Medications are designated: ACTH, adrenocorticotropic hormone; CBZ, carbemazepine;
CZP, clonazepam; DPH, diphenyl hydantoin; NZP, nitrazepam; PHT, phenytoin; PB, pheno-
barbital; PHT, phenytoin; PRIM, primidone; VPA, Na-valproate; UM, unmedicated.
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TABLE 2 -- SEIZURE DATA
Patient
ID
Period of No. of
Seizure Epoch -1* Epoch-1 Epoch -2+ Epoch -2 Epoch -1
data col.
seizures
freq.
t
p
t
p
r
TLG1
205
7
0.034
1.03
0.17
3.10
.01
0.359
TLG2
574
320
0.56
0.70
0.24
-0.28
.61
0.039
TLG3
182
42
0.23
-2.59
0.99
-3.08
.998
-0.382
TLG4
300
13
0.043
2.08
0.031
1.85
.045
0.518
TLG5
268
1449
5.4
0.41
0.34
-0.50
.69
0.011
TLG6
370
130
0.35
0.30
0.38
-1.87
.97
0.026
TLG7
482
11
0.023
0.06
0.48
-0.23
.59
0.018
TLG8
174
7
0.040
1.20
0.14
0.35
.37
0.412
TLG9
293
82
0.28
0.55
0.29
-1.13
.87
0.060
TLG10
323
17
0.053
-0.12
0.55
0.86
.20
-0.029
TLG11
180
49
0.27
0.48
0.32
0.17
.43
0.068
TLG12
182
17
0.094
0.79
0.22
2.80
.0064
0.187
TLG13
320
101
0.32
1.81
0.037
0.44
.33
0.178
TLG14
724
133
0.18
-2.08
0.98
-2.41
.99
-0.179
TLG15
2360
768
0.33
0.61
0.27
-0.62
.73
0.022
TLG16
166
71
0.43
0.93
0.18
0.40
.35
0.11
TLG17
185
12
0.065
-0.93
0.81
-0.02
.51
0.257
RR1
111
36
0.32
1.48
0.074
2.13
.020
0.241
NE1
87
167
1.9
-0.22
0.59
-0.28
.61
-0.017
NE2
5164
109
0.021
-1.15
0.87
-1.74
.96
-0.11
NE3
563
281
0.50
1.45
0.074
3.29
.00057
0.086
WO1
62
276
4.5
2.89
0.0021
3.64
.00016
0.172
*Epoch -1 refers to comparisons between the day of the seizures and previous days.
+Epoch -2 refers to comparisons with the day 2 days before the seizure day.
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