PHENOMENOLOGICAL RESEARCH AND ANALYSIS

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• Publication Date: September 29, 1994
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Final Report
Phenomenological Research
and Analysis
Authors:
Edwin C. May, Ph.D., Wanda L. W. Luke, and Christine L. James
29 September 1994
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AMMAII2Wi TM/
Science Applications International Corporation
An Employee-Owned Company
Presented to:
U. S. Government
Contract MDA908-93? C-0004
(Client Private)
Submitted by:
Science Applications International Corporation
Cognitive Sciences Laboratory
1V t0 El Qamino Rept Suite 330, P.O. Box 1412, Menlo Park, CA 94025 ? [phone]
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TABLE OF CONTENTS
LIST OF FIGURES ii
LIST OF TABLES iii
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I. EXECUTIVE SUMMARY 1
II. TECHNICAL OVERVIEW 2
1. Biophysical Measurements 2
2. Data Patterns/Parameter Correlations 11
3. Theoretical Issues 15
4. Applied Research 18
5. Research Methodology and Support 25
III. GLOSSARY 27
REFERENCES 28
APPENDIX A: Autonomic Detection of Remote Observation 30
APPENDIX B: Target and Sender Dependencies in AC Experiments 31
APPENDIX C: Managing the Target Pool Bandwidth 32
APPENDIX D: Shannon Entropy as an Intrinsic Target Property 33
IX E: Ganzfeld Exi,eriment 34
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LIST OF FIGURES
1.
Stimulus Timing
7
2.
Typical ERD from Direct Stimuli
8
3.
Cluster Diagram
16
4.
Cross-Section of the Detector (Not to Scale)
21
5.
Test Exposure: 2,250 Volts for 28 Hours
22
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LIST OF TABLES
1. AC Results 9
2. Wilcoxon Statistics for ERDs 9
3. 0-7 Point Assessment Scale 10
4. Partial Element List for a Test-bed Experiment 24
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Phenomenological iiesearcn ana Ana!lima: rma
I. EXECUTIVE SUMMARY
Our research has advanced our understanding of applying anomalous mental phenomena to practical
problems and lead us toward a comprehensive theoretical model for the phenomena.* During the con-
tract period ending-29 July 1994, we have:
? Successfully verified a claim from the Former Soviet Union (FSU) and from the U.S. that it is possible
to influence the physiology of an isolated individual exclusively by anomalous mental phenomena.
Furthermore, we were able to demonstrate in our analysis of previous work that the mechanism of
such influence is most likely causal. That is, the mental intention of a distant agent appears to cause
physiological changes in an isolated person.
? Identified an intrinsic property of an AC target (i.e., the gradient of Shannon's entropy). This result
is a break-through in our understanding of the mechanisms of AC. We have shown that detecting AC
is not unlike how our other sensory systems detect their particular inputs (e.g., how the eye detects
light). In the future, all practical applications and laboratory experiments can be significantly im-
proved by choosing targets that possess the largest possible value of this particular parameter.
? Provided a proven method for the detailed evaluation of individual AC-performance in practical ap-
plications, in the laboratory and as a certification procedure.
?
? Set a lower limit for the response of the central nervous system (i.e., brain) to anomalous cognition
(AC) signals. If we could be successful at identifying a brain response, then practical applications and
laboratory research would be sharply improved, even though the estimate for the lower limit is only
0.2 percent change in brain activity.
? Developed and calibrated instrumentation to replicate a physics-type experiment from the FSU that
suggests a new form of energy can be detected. Researchers there speculate that this form of energy
might be responsible as the carrier of anomalous mental phenomena signals. Preliminary results are
ura in! and the final results will be available before 30 September 1994.
?I ?
? Clearly demonstrated that using AC as a technique to send messages is not a productive pursuit.
All of the experiments that we conducted for this year produced highly significant evidence for anoma-
lous mental phenomena. We interpret this success, which is 20 times chance, to our expanding under-
standing of the protocols, mechanisms, and psychology that are responsible for a high level of function-
ing. The magnitude of our AC effects exceed the value that is considered robust by the psychology
research community.
* This report constitutes our final deliverable under contact number MDA908-93-C-0004.
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II. TECHNICAL OVERVIEW
In this section we provide a technical overview of the activity which was conducted under contract num-
ber MDA -004. The technical details of the experiments can be found in the Appendices.
1. Biophysical Measurements
These tasks were to search for possible physiological correlates to anomalous cognition (AC) function-
ing. If such correlations could be found, they would directly lead to improved application and laborato-
ry results.
We conducted two experiments with regard to biophysical measurements that were replications of pre-
vious work. The first of these was an attempt to replicate a finding in the U.S and in the Former Soviet
Union that claimed that some aspect of human physiology can be influenced by an isolated and remote
observer (Schlitz and LaBerge, 1994).* The second was an improved experiment to determine if and
how the central nervous system (i.e., the brain) responds to "signals" that are sensorially isolated from a
receiver.t
1.1 Remote Observation Experiment
A series of experiments has been conducted in the U.S. in which it is claimed that a receiver's electrical
properties of the skin (i.e., electrodermal response) can be influenced by a remote observer. This is a
laboratory example of a frequently reported anecdote: after entering a crowded room, you "sense" that
you are being stared at and discover that you are correct.
A complete write-up of our experiment, which includes the history, methodology, and results can be
found in Appendix A; however, we summarize the findings here.
lino experiments were conducted to measure the extent to which people are able to unconsciously de-
tect another person staring at them from a distance. A close-circuit television set-up was employed in
which a video camera was focused on the experimental volunteer (Observee) while a person in another
room (Observer) concentrated on the image of the distant person as displayed on a color monitor; this
procedure was used to preclude any conventional sensory contact between the two people. During the
experimental session, the Observee's galvanic skin responses were monitored. An automated and com-
puterized system was programmed to record and average the physiological responses of the Observee
during 32 30-second monitoring periods. A random sequence was used to schedule 16 periods of re-
mote observation and 16 control periods when no observation efforts were attempted. A within-sub-
jects evaluation was made for each experimental session with a comparison between the mean amount
of autonomic nervous system activity during the experimental and control conditions. Tiventy four ses-
* References may be found at the end of the document.
t Please see Section III on page 27 for a definition of terms.
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sions were conducted in each of two experiments. As predicted, both experiments yielded significantly
more autonomic activity during the remote observation periods as compared to control periods (Ex-
periment 1: 1=1.878, df = 23, p < 0.036; Experiment 2: t=2.652, df = 23, p < a014). As pre-planned,
the two experiments were combined to increase the statistical power, yielding a significant t-score of
2.652 (df = 47, p < 0.005).
There are two competing anomalous mental phenomena descriptions for these results. Given that this
experiment represents successful replication of a number of such experiments, we do not include the
possibility that these results are a rare or chance statistical deviation. The question we pose for future
experiments is: Is this effect causal (i.e., the Observer forces the skin parameters to be different than
they would otherwise be) or informational (i.e., the Observee is AC-sensitive to know when he/she is
been stared at and responds accordingly)? The methodology we used in our experiment was primarily
designed to replicate both US and FSU similar experiments rather than to answer this particular ques-
tion. Although most of our analyses of so-called anomalous perturbation (AP) experiments demon-
strate informational mechanisms, we have recently analyzed a bio-AP experiment that statistically fa-
vored the causal explanation. Determining the mechanism is very important because it will dictate the
potential applications for this type of phenomenon.
1.2 Central Nervous System Response to AC Signals
The objective of this effort was to test the hypothesis that physiological responses to AC stimuli re-
semble those which occur in response to identical direct visual stimuli.
1.2.1 Background
As part of the research tasking for FY 1993, we had been asked to conduct an investigation of the rela-
tionship between the central and/or the peripheral nervous system and AC. In this section, we review
the pertinent literature and provide a justification for the effort.
1.2.1.1 Prior Research
We only consider AC experiments that use complex material for targets. While there have been sub-
stantial numbers of experiments in which symbols have been used as targets (Honorton, 1975; Honor-
ton and Ferarri, 1989), we will not include that data as part of the behavioral evidence for AC.
In 1976, Puthoff and Targ (1976) published the results of a series of experiments in what was then called
remote viewing. In 51 trials, their results led to an overall effect size of 0.960?0.140 which corresponds
to a 6.8cr effect. In behavioral terms, Cohen (1988) would classify this effect as large.
As part of our FY 1991-1992 effort, we were asked to use magnetoencephalography (MEG) to investi-
gate how, or if, the central nervous system (CNS) responds to "visual" stimuli that are physically and
sensorially isolated from a receiver. The reasoning behind this request was that during an earlier inves-
tigation in FY 1988, we observed, what was suspected to be, instantaneous phase shifts of the dominant
alpha rhythm concomitant with such stimuli. That study itself was originally thought of as a conceptual
replication of even earlier work in which alphapower changes were putatively induced with remote visu-
al stimuli (Rebert and -Rimer, 1974; May, T'arg, and Puthoff, 1977).
As we stated in our final report (May, Luke, and Lantz, 1992), the FY 1992 study did not replicate the
FY 1988 finding (May, Luke, Trask, and Frivold, 1990b). Because of our technical and methodological
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improvements, we concluded that the 1988 results were likely to be spurious. We can, however, specify a
number of possible arguments why the 1988 study failed to replicate:
? AC does not exist.
? AC exists, but the conditions were not conducive for quality AC functioning.
? AC exists, but the target system (i.e., 100 millisecond sinusoidal gratings in the lower left visual field
of the receiver) did not constitute an appropriate stimulus.
We address these issues in order.
The verification of the existence of AC is an epistemological problem. The definition of AC is a nega-
tive one; we are able to describe what AC is not, but there is no statement about what AC is other than
methodological. Colloquially, we might say AC is a form of information transfer when, according to the
currently understood laws of physics, the retrieval of information is impossible. Thus, we say AC exists
if a statistically valid anomaly is observed under the proper methodological conditions.
Since replication is better than distribution theory, it is important to define what replication means in a
2-a domain. Professor Utts, from the statistics department at the University of California at Davis, has
provided a good operational definition, which is based on standard power analysis (Utts, 1988). Since
1975, there have been four major articles published in the reviewed literature that analyze substantial
numbers of experiments that portend AC. All but one use the modern methods of meta-analysis to
determine the final conclusion for each collection of studies. It is important to realize that in all these
analyses, all the published data are included. In addition, the techniques of meta-analysis allow for re-
sponsible estimates of the number of studies that "failed" and were not published.
(1) In "Error Some Place!" Honorton critically reviewed card-guessing experiments, which were con-
ducted between 1934 and 1939 (Honorton, 1975). The AC-targets in these studies were five geo-
metric symbols; circle, square, wavy lines, star, and cross. In almost 800,000 individual card trials
that were obtained after the targets had been specified (i.e., real-time AC), the weighted effect size
was = 0.013?0.001, which corresponds to an overall combined effect of 12.7o. This analysis,
however, was completed before the techniques of meta-analysis were known. Improvements,
which include the analysis of experiment quality, can be found in the next example.
(2) Using the tools of modern meta-analysis, Honorton reviewed the precognition (i.e., a target is ran-
domly generated after the trial had been obtained) card-guessing database (Honorton and Ferarri,
1989). This analysis included 309 separate studies reported by 62 investigators. Nearly two million
individual trials were contributed by more the 50,000 subjects. The combined effect size was
0.020?0.002, which corresponds to an overall combined effect of 11.4o. Two important results
emerge from Honorton's analysis. First, it is often stated by critics that the best results are from
studies with the least methodological controls. To check this hypothesis, Honorton devised an
eight-point quality measure (e.g., automated recording of data, proper randomization techniques)
and scored each study with regard to these measures. There was no significant correlation between
study quality and study score. Second, if researchers improved their experiments over time, one
would expect a significant correlation of study quality with date of publication. Honorton found r =
0.246, df = 307, p < 2 x 10-7. In brief, Honorton concludes that a statistical anomaly exists in this
data that cannot be explained by poor study quality or a large variety of other hypothesis.
In examining AC with complex visual targets, Bern and Honorton analyzed 11 separate studies in-
volving a total of 329 trials (Bern and Honorton, 1994). They report a combined effect size of
0.159?0.055, which corresponds to 2.89o. We wish to call attention to the fact that this effect size is
approximately eight times larger than the effect size reported for studies where the targets are sym-
bols. Since effect sizes are relative measures above mean chance expectation, this result is one, of
(3)
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many, which suggest that the statistically simpler target system of five symbols does not produce as
much AC as do complex targets.
(4) Radin and Nelson (1989) provide, in Foundations of Physics, a meta-analysis of a different form of
AC. The targets were randomly changing binary bits whose random nature was usually derived ei-
ther from electronic noise or radioactive decay. Similar to Honorton's work, they assigned a
16-point quality rating to over 800 individual studies conducted by 68 investigators from 1959 to
1987. They compute an overall weighted effect size of approximately = (3.0?0.5)x 10-4, which
corresponds to 6a. They also find no correlation between study quality and study score.
An independent analysis of these statistics can be found in Statistical Sciences, which is a journal that
invites and publishes contributions and substantial critical comments by recognized leaders in the field
of statistics (Utts, 1991). Although Utts focuses her attention on the meta-analyis of the Ganzfeld, her
analysis, discussion, and defense of the commentary are noteworthy.
These effects are small. To illustrate a point about replication, we will compute, using standard power
analysis, the probability that a new study will demonstrate significant (i.e., p < 0.05) evidence for AC. If
we assume that the actual AC-effect size is given by 7 = 0.159 then the probability of observing a signifi-
cant outcome in 50 trials is only 30%. Although this is six times chance expectation of 5%, there remains
a 70% likelihood that this study would "fail" to replicate. It is exactly this type of realization that is
responsible for a shift in the determination of replication from p-values to effect sizes.
It is clear from these analyses that there is incontrovertible evidence that a statistical, albeit small, in-
formation-transfer anomaly exists that cannot be accounted for by methodological issues or fraud.
Thus, we were strongly motivated to continue our investigations of the CNS in order to identify how the
brain responds to AC stimuli.
1.2.1.2 Conditions for Quality AC Functioning
One of the problems associated with our earlier CNS investigations is that we did not obtain concom-
itant behavioral measures of AC. Many experiments and discussions about what constitutes an AC-
conducive state can be found in the parapsychology literature. It is beyond the scope of this report to
provide an analysis of this research, and there remains substantial disagreement among the researchers
on this point. In Ganzfeld studies, for example, it is assumed that reducing somatisensory noise en-
hances AC, yet in our experiments we observe equivalent or larger effect sizes without the reduction.
Lacking reliable research results on this point, it has been our view that the "ideal" environment for AC
would not be much different than what might be needed to perform any high-level mental task. For
example, the best environment for a person to read and understand a novel might also be sufficient for
producing AC. In most all of our AC experiments, receivers are seated in a quiet and comfortable room
with few external distractions. The atmosphere is cordial, yet businesslike. On the one hand, we would
like to have the receivers be attentive (i.e., we suspect that too relaxed or asleep is not helpful); yet on
the other hand, we do not want them to be distracted. Under these conditions, we routinely observe
large effect sizes for AC.
In our MEG investigations, receivers were required to recline, face down, on a wooden table in a dark,
technically complex room for approximately 30 minuets. A large device (i.e., the MEG and its
associated liquid helium flask) was comfortably touching the back of their heads. In addition, they were
instructed to move as little as possible and relax as much as possible. Some receivers complained that
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various body parts fell "asleep," and that the experience was not particularly pleasant; other receivers
did not mind the setup. No receivers, however, found the experience enjoyable.
We suspect that since this environment was sufficiently different from our usual one, it may have failed
to provide a conducive atmosphere to elicit AC functioning.
1.2.1.3 Target Systems
The meta-analysis of the historical databases clearly show a preference for certain target systems. For
example, as we have shown above, complex visual targets provided better AC than do simple geometric
symbols. In addition, Bern and Honorton have demonstrated a statistical preference for even more
complex targets than static photographs. They observed a significant difference in the Ganzfeld favor-
ing video segments from popular movies over single photographs. There is no evidence in the literature
to suggest that a 100-millisecond long sinusoidal grating constitutes a viable AC target. In fact, our en-
tropy results suggest that it would not be a good target, because it's total change of Shannon entropy is
small (May, Spottiswoode, and James, 1994).
1.2.1.4 Conclusions
Except for the alpha blocking experiment done at SRI in the early 70's, we have not been able to observe
CNS correlates to AC functioning. We think that this may have resulted because of methodological
issues. In the remainder of this section, we describe a much-improved approach that remedies the prob-
lems of the previous methodologies.
1.2.2 Protocol
1.2.2.1 Introduction
Using an electroencephalograph (EEG), we corrected the shortcomings of the previous work. Each
stage of the investigation was built upon the results to date, and represented only modest extensions to
the previous stage. In addition, we used traditional EEG methods for data collection and analysis so
that comparisons with the established literature were straight forward." We assumed that AC exists in
general (i.e., within the framework discussed above); however, our approach included a "local" verifica-
tion of AC's existence.
Consider event-related desynchronization (ERD). Spontaneous EEG reveals short-lasting, task- or
event-related amplitude changes in rhythmic activity within the alpha band (i.e., 8 to 12 Hz). This am-
plitude change or desynchronization is one of the elementary phenomena in EEG. It was first described
by Berger (1930) in scalp EEG as alpha blocking, and was later termed ERD by Pfurtscheller and Arani-
bar (1977). ERDs can be quantified as a function of time and can then be used to study cortical activa-
tion patterns during the planning of motor behavior (Pfurtscheller and Aranibar, 1979), sensory stimu-
lation, and cognitive processes (Pfurtscheller, Lindinger and Klimesch, 1986; Klimesch, Pfurtscheller and
LindingerKlimesh, 1987; and Sergeant, Geuze, and Van Winsum, 1987). Kaufman, Schwartz, Salustri
and Williamson (1990) provide a more recent example of cognitive-process-related ERDs, which they
call alpha suppression. 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. Because ERDs arise from external
* For these investigations, we did not require the special properties of a MEG (e.g., source localization), so we used the less com-
plex and more readily available EEG technology.
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stimuli, cognitive tasks, or motor functions, they are a likely variable to use to study how the CNS might
respond to AC stimuli. It would be odd, indeed, if AC was the only stimulus that did not produce an ERD.
1.2.2.2 Target Stimuli
lb overcome the potential problems associated with the earlier stimuli, we used throughout this study
our standard National Geographic target pool. These images are complex, but there is an increasing
database in our laboratory that shows they are suitable for targets in AC experiments. In addition, the
results of the meta-analyses, which were described above, show a significant preference for complex
target systems as opposed to symbols or 100-millisecond long sinusoidal gratings. Our target pool was
digitized for later display on a laboratory PC. Figure 1 shows the stimulus timing. During a trial, a ran-
domly selected photograph was displayed for one second with an inter-stimulus interval (ISI) of 3 seconds.
Stimulus Window Post Stimulus Next Stimulus Window
0 1 4 5
Time (Seconds)
8
Figure 1. Stimulus Timing.
While this stimulus?post stimulus pattern is fixed throughout the session, what happens in a stimulus
window is counter balanced between two stimulus types and random. We created a digital "image" that
was technically identical to the target images (e.g., same resolution, size) except that the color was nu-
merically identical to the background color of the display. These pseudo stimuli could not be detected
visually and, thus, served as a within run control.
1.2.2.3 Receivers
We asked three of our best receivers, 009, 372, and 389 to participate in the experiment. Because of the
pilot nature of this approach, we did not set the total number of trials; rather, time and receiver avail-
ability determined the number of trials for each receiver.
1.2.2.4 Trial Protocol
The following was the sequence of events for each trial:
(1) The receiver was wired at the standard positions for right and left hemisphere EEG for occipital
and parietal measurements referenced to CZ (i.e., the center of the top of the scalp).
(2) The receiver was seated in a sound-attenuated and electrically shielded room that is commonly
used for such measurements.
(3) One of two possible random sequences for pseudo and target stimuli was selected randomly, and
the trial was initiated.
(4) The receiver was instructed to silently obtain AC data for the first five minutes.
(5) The receiver debriefed his/her experience during the next five minutes in words and drawings.
(6) After the response had been collected, the receiver was presented visually with the exact same stim-
ulus pattern that was used in the first five minute interval as feedback.
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After a brief rest, a second trial was conducted, which was identical to the first except that a new target
was selected randomly and the second possible stimulus order was used in step 3 above.
1.2.2.5 AC-Behavior Analysis
An analyst who was otherwise blind to the experiment and trial details, was given a target pack number
that contained the original target and four decoy photographs in random order. The analyst's task was
to rank-order the five targets from best to worst match to the trial behavior response (i.e., writings and
drawings). With the usual sum-of-rank statistic, we could determine the overall level of AC functioning
in the study, for each receiver, and determine the level of AC for each trial.
1.2.2.6 ERD Analysis
The EEG record for each trial contains continuous samples at 500 samples/second for five minutes of
AC-stimuli and five minutes for direct stimuli (i.e., feedback of the target visually). Each epoch con-
tained random sequences of stimuli and pseudo stimuli. These data were low pass filtered to avoid
aliasing, then reduced by five, yielding an effective sampling rate of 100/second. The alpha content (i.e.,
7.81 to 12.7 Hz) was extracted with a 32-pole, FIR, zero phase shift, digital filter, and the alpha power
was estimated by the ensemble square.
We computed an ERD template for each receiver. For each direct stimulus during the feedback five
minute interval, the alpha power was ensemble averaged and normalized by the average alpha power
for one second of prestimulus time. The resulting ERDs were averaged to produce the template for
each trial. Figure 2 shows a typical ERD from one such calculation for receiver 372. We see that for
direct stimuli we expect a latency of approximately 0.5 second (i.e, time after stimulus onset), an 85%
reduction in alpha power and approximately two seconds for recovery.
This template was cross correlated with the data during the AC-portion of the trial. That is, for each
stimulus and for each pseudo stimulus, the maximum of the absolute value of the cross correlation for
?0.2 seconds surrounding the stimulus time was accumulated separately for each stimulus type. A stan-
dard non-parametric sum-of-ranks method was used to compare the resulting two distributions.
0 . 5
cz1)
0 0 . 0
?
c.)
ctl
- 1 0
-1 0
Time (s)
2
3
Figure 2. Average ERD Normalized by Pre-Stimulus Mean.
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1.2.3 Results and Discussion
Table 1 shows the results of the blind rank-order judging for the three receivers;
Table 1.
AC Results
Receiver
Ilials

ES
P-value
009
18
2.389
0.432
0.033
372
24
2.500
0.354
0.042
389
28
2.750
0.177
0.175
Total
70
2.571
0.303
0.006
Ilvo receivers produced independently significant evidence for AC and the combined data were also
significant. Thus we have corrected one of the shortcomings of our earlier efforts; we have independent
evidence for AC.
'able 2 shows the results of the non-parameter Wilcoxon sum-of-ranks test between the distributions
resulting from the pseudo- and AC-stimuli.
Since the total number of stimuli per receiver was over 1600, the statistics shown in Table 2 are not en-
couraging. That is, given we observed significant evidence for AC, how is it that we do not see a signifi-
cant CNS response?
Table 2.
Wilcoxon Statistics for ERDs
Receiver
Z-score
P-value (2t)
009
?0.758
0.448
372
1.509
0.132
389
0.930
0.352
ibtal
?
0.938
0.175
To determine the overall sensitivity of our signal detection methodology, we inserted template ERD's
into copies of the EEG data. Averaged over all receivers, we found that a 0.2 % change from pre-stimu-
lus alpha would lead to a significant difference between the distributions resulting from the AC-stimuli
and the pseudo stimuli. This high sensitivity arises primarily because we have over 1600 stimuli per
receiver and because the cross correlations technique (i.e., frequently referred to as a matched filter)
can be shown to be the best possible signal detection algorithm in a noise environment. Yet, with this
sensitivity we did not observe a statistically significant ERD. We must examine some of our basic as-
sumptions, if we are to understand this result.
One assumption is that a putative ERD would result, on the average, from every AC-stimulus. To test
this, we re-analyzed the behavioral data post hoc. Rank-order analysis does not usually indicate the
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absolute quality of the AC. For example, a response that is a near-perfect description of the target re-
ceives a rank of one. But a response which is barely matchable to the target may also receive a rank of
one. Table 3 shows the rating scale that we used to perform a blind assessment of the quality of theAC
responses, regardless of their rank.
Table 3.
0-7 Point 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 site.
2
Some correct elements, but not sufficient to suggest results beyond chance
expectation.
1
Little correspondence.
0
No correspondence.
lb apply this subjective scale to anAC trial, an analyst begins with a score of seven and determines 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 to zero until the score-description seems reasonable for the trial.
We thought that by analyzing the EEG data only when the AC functioning was high, we might have a
better chance of detecting an ERD. Unfortunately, we found no statistical change of the Wilcoxon Z-
scores only using data from the upper portions of the scale shown in Table 3. Thus, we must examine our
assumptions further.
One implicit assumption in the search for AC-ERDs is that there is a direct casual and temporally stable
link between the stimulus and the response. That is, since the data analysis involves an ensemble aver-
age over time, we must assume that changes in spontaneous alpha that are not associated with the stim-
ulus will be averaged out of the ensemble. It maybe, however, that AC is more complex. In Honorton's
meta-analysis of the precognition data (Honorton and Ferrari, 1989), the precognition of complex visu-
al targets reported by Jahn (1982), and the anecdotal reports of many of our receivers all suggest that
AC may not be stable in time.
One explanation for the significant improvement in AC when complex targets are used instead of sym-
bols may be related to imagery. If a receiver knows the stimulus set (e.g., in the case of Zener cards; star,
cross, square, circle and wavy lines) then he or she is likely unable to differentiate between a vivid inter-
nal image of one of the symbols, which results from memory or imagination, and a putative "signal"
resulting from AC. In the case of more complex targets, such as National Geographic photographs,
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there may be a lesser tendency to remember all possible combinations of elements one may find in such
a target pool. If this speculation is correct, then internal imagery is a source of noise, and we might not
expect to see changes in occipital alpha.
Some receivers report that their internal experiences tend to be kinesthetic rather than visual. These
ideas have not been formally tested in the laboratory, yet they are commonly reported by many of our
excellent receivers. We have assumed that the CNS will respond as if the AC-signal stimulates neurons
near the visual cortex. Given that we were unable to take survey data over the entire scalp, it is possible
that we might not have positioned the EEG electrodes for optimal detection of an AC response.
We recommend that we adopt the new technology of functional magnetic resonance imaging, which can
survey the entire CNS. In addition, we suggest that we optimize the target pool to contain the largest
possible gradient of Shannon entropy. This should be the best possible next step to observe the CNS's
response to an AC stimulus.
2. Data Patterns/Parameter Correlations
The task of this section was to identify parameters that would potentially lead to an increase of AC func-
tioning and assist in determining optimal protocols for potential applications.
2.1 The Gradient of Shannon's Entropy
The primary activity in this category was to determine if the total change of Shannon entropy could be
confirmed as an intrinsic target variable. This effort constituted a replication of our finding during the
1992-1993 period, and led to three papers that have been accepted for publication at the Parapsycholog-
ical Annual Convention. We include these three papers as Appendices B, C, and D and summarize
their findings here.
The Ganzfeld experiments as summarized by Bem and Honorton (1994) suggest that using dynamic
targets produces stronger results than using static ones. Bern and Honorton, however, only analyzed
Ganzfeld studies that included the use of a sender. Since it is known that a sender is not a necessary
requirement in forced-choice trials, we designed and carried out a study to see if a sender is required in
non-Ganzfeld, free-response trials. In the first of two experiments, five experienced receivers partici-
pated in 40 trials each, 10 in each condition of a 2 x 2 design to explore sender and target type. We
observed significant effects for static targets (i.e., exact sum-of-rank probability of p < 0.0073, effect
size = 0.248, n=100), chance results for dynamic targets (i.e.,p < 0.500, effect size = 0.000, n = 100),
and no interaction effects between sender and target-type conditions. One receiver slightly favored the
no sender condition (F(1,36) = 4.43, p