TARGET AND SENDER DEPENDENCIES IN ANOMALOUS COGNITION (DRAFT TECHNICAL PROTOCOL)
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Publication Date:
December 2, 1991
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iftrAmEMwslotr9r Release 2001/03/8/3:441-RDP96-00789R9p_ipp0171041R911
Target and Sender Dependencies
in
Anomalous Cognition
Prepared by:
Edwin C. May, Ph.D. and Nevin D. Lantz
2 December 1991
mArui
IIIN 8
Science Applications International Corporation
An Employee-Owned Company
Presented to:
The Scientific Oversight Committee
Submitted by:
Science Applications International Corporation
Cognitive Sciences Laboratory
1010 El Camino Real, Suite 330
Menlo Park, California 94025
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 ii
LIST OF TABLES iii
I OBJECTIVE 1
II INTRODUCTION 2
III APPROACH 4
1. Target-pool Selection 4
2. Target Perparation 4
3. Target Selection 8
4. Receiver Selection 8
5. Sender Selection 9
6. Session Protocol 9
7. Analysis 10
8. Hypotheses 10
IV DISCUSSIONS AND CONCLUSIONS 12
1. Null Result 12
2. Significant Deviations 12
V GLOSSARY 14
REFERENCES 15
APPENDIX 16
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LIST OF FIGURES
1. City with a Mosque 5
2. Green Intensity Distribution for the City Target (Macro-pixel, 3,3) 6
3. City with Mosque (1AS I = 1.98 bits/0.25 i n2) 6
4. Pacific Islands (ISI = 1.35 bits/0.25 i n2) 7
5. Zener Target Cards (Average I AS = (J.15 bits/0.25 in) 7
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LIST OF TABLES
1. Effect Size as a Function of Target Type 3
2. Potential Correlation of AS with Effect Size 8
3. Experiment Conditions 9
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I. 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 anomalous cognition (AC) quality depends upon a sender.*
* Definitions of terms can be found in Section V (i.e., Glossary) on page 14.
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II. 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 anomalous cognition (AC). In this section, we review the pertinent literature that describes at-
tempts to improve the quality of AC by categorizing target content.
At a recent conference, Delanoy reported on a survey of the literature for successful AC experiments,
and, she categorized the target material according to perceptual, psychological and physical character-
istics.1* Except for trends related to dynamic, multi-sensory targets, she was unable to observe system-
atic correlations of AC quality with her target categories.
Watt examined the AC-target question from a theoretical perspective.2 She concluded that the "best"
AC targets are those that are meaningful, have emotional impact, and contain human interest; those
targets that have physical features that stand out from their backgrounds or contain movement, novelty,
and incongruity are also good targets.
The difficulty with either the survey of the experimental literature or the psychologically oriented
theoretical approach is that understanding the sources of the variation in AC quality is problematical.
Using a vision analogy, 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 AC research, the same difficulty arises. Until we understand the influence of these factors on
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 Gansfeld experiments, receivers are placed in a
state of mild sensory isolation and asked to describe their mental imagery. After each trial, the analysis
was performed by the receiver, who was asked to rank order four pre-defined targets, which include the
actual target and three decoys; the chance first-place rank hitting rate was 0.25. In 355 trails collected
from 241 different receivers, Honorton et al. found a hitting rate of 0.31 (z = 3.89, p < 5 x 1O?) for an
effect size of 0.20. 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 conduced with a sender.
In a carefully conducted meta-analysis, Honorton and Ferrari report significant hitting in forced-
choice, precognition experiments.41- They analyzed 53 years of experiments conducted by 62 different
investigators using a limited set of symbols (i.e., called Zener cards) as target material. Fifty thousand
? References may be found at the end of the document.
t Forced-choice means targets are randomly chosen from a known and limited set of possibilities (e.g., red or black playing
cards). Precognition means that the target is generated randomly after the guess has been registered.
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subjects contributed a total of approximately 2 x 106 individual trials. The overa
corresponding to a p-value of 6.3 x 10-25. Similarly, in an earlier review articl
7.5 x 105 forced-choice Zener card trials that were collected from 1934 to 1939
overall effect size of 0.016?0.001.5
Puthoff and Targ publish the results of 39 AC real-time trials where the targets
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
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1 effect size was 0.020
, Honorton analyzed
d found a significant
ere natural scenes in
Target 'Type
Trials
Effect Size
Symbols (Real-Time)
7.5 x 105
0.016 ? 0.001
Symbols (Precognitive)
2.0 x 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
The effect sizes shown in Table 1 are qualitatively monotonically related to targe
appropriate quantitative description for target type is currently unknown. Yet, t
one of the experimentally observed and theoretically conceived target concepts
Watt, respectively.
A number of confounds exist, however, in this database for the effect-size measur
but the Puthoff and Targ study (i.e., targets were natural scenes), the receivers we
they did not participate in the various experiments on the basis of their known ab
the large effect size for the Puthoff and Targ study because of the accomplished
scene targets, or some combination of both? While there are a number of other e
derance of the data were from unselected individuals. In many of the trials, a se
on the target material, and as in most perception experiments, psychological fact
tribute to the variance in the effect sizes.
t "complexity;" yet an
rget "complexity" was
ound by Delanoy and
s. For example, in all
e unselected. That is,
ity as receivers. So, is
eceivers, the natural-
ceptions, the prepon-
er was concentrating
rs and boredom con-
In this pilot experiment, we will apply one physical measure to static and dynamic photographs to quan-
tify the relationship between target type and AC quality. By careful selection of arget content, we will
minimize the psychological factors in perception. In addition, we will minimize individual differences
by conducting many trials with each receiver and by only choosing receivers who have previously dem-
onstrated excellent AC skill.
Because the previous database included trials with and without senders, we will xplore the effects of a
sender on AC quality, as well.
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III. APPROACH
1. Target-pool Selection
The static target material for this pilot study will be an existing set of 100 National Geographic magazine
photographs. This set has been divided into 20 sets of five photographs that were determined to be
visually dissimilar by a fuzzy set analysis.7 The dynamic target material will be approximately 50, 60 to
90 second clips from popular video movies. These clips will be selected because they:
? are thematically coherent,
? contain obvious geometric elements (e.g., wings of air craft), and
? are emotionally neutral.
The intent of these selection criteria is to control for cognitive surprise, to provide target elements that
are easily sketched, and to control for psychological factors such as perceptual defensiveness.
The video segments will be drawn from a variety of themes including adventure, documentary, and fantasy.
2. Target Preparation
The target variable that we will consider in this experiment is the total change of entropy per unit area,
per unit time. We have chosen this quantity because it is qualitatively related to the "complexity" of
target type shown in Table 1, and because it represents 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:
Nk-1
Sk = pikl0g2(pik),
j-0
where pjk 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 = i g b. The total change of the entropy in differential
form is given by:
?
dsk = vs? ? dr + ask ?dt . (1)
at
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.
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2.1 Static Photographs
Each target from the pool of 100 National Geographic magazine photographs will be
inch (dpi) for eight bits of information of red, green. and blue intensity. At 0.25 in
example, this scanning density provides 625 pixels for each 0.25 x 0.25 in2 patch t
For a specified resolution, the target photograph is divided into an integral num
eluding a thin border, if necessary. The entropy for the (i,j) macro-pixel is coin
N - 1
Si = p; iog2(p, ),
wherepi is computed empirically from the pixels in the (i, j) macro-pixel only. Fo
target photograph shown in Figure 1.
;gum loom -5
anned at 100 dots per
spatial resolution, for
compute the py.
er of macro-pixels ex-
uted as:
example, consider the
f.::????,..: ? ?
Figure 1. City with a Mosque
Figure 2 shows the probability density for green macro-pixel (3,3), which is sho
the upper left hand corner of Figure 1.* The probability density and the photogr
of the intensity in this patch is near zero value (i.e., no intensity of green in this c
ion, Sij are calculated for the entire scene. For the photograph shown in Figure
43, and j ranges from zero to 32 for a total of 1,452 macro-pixels.
" The original photograph was 8.5 x 11 inches, and we have standardized on 0.25 inch resolution.
n as a white square in
ph indicates that most
se). In a similar fash-
, i ranges from zero to
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?F+'
0
0.4
0.0
20
40 60
Intensity (j)
80
A
100
Figure 2. Green Intensity Distribution for the City Target (Macro-pixel 3,3).
We will use a standard algorithm to compute the 2-dimensional spatial gradient of these 1,452 values 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 1.98 bits/0.25 in2.*
?,?.