MANAGING THE TARGET-POOL BANDWIDTH: POSSIBLE NOISE REDUCTION FOR ANOMALOUS COGNITION EXPERIMENTS

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• Publication Date: September 1, 1994
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The Journal of Parapsychology, Vol. 58, September 1994
MANAGING THE
TARGET POOL BANDWIDTH:
POSSIBLE NOISE REDUCTION FOR
ANOMALOUS COGNITION EXPERIMENTS
BY EDWIN C. MAY, S. JAMES P. SPOTTISWOODE,
AND CHRISTINE L. JAMES
ABSTRACT: Lantz and colleagues recently reported in the first of two studies that experi-
enced receivers from the Cognitive Sciences Laboratory produced significant evidence for
anomalous cognition (AC) of static targets but showed little evidence for AC of dynamic
targets. This result was surprising: It was directly opposite to the results that were derived
from the 1994 Bem and Honorton ganzfeld database. In Lantz et al.'s experiment, the
topics of the dynamic targets were virtually unlimited, whereas the topics for the static
targets were constrained in content, size of cognitive elements, and range of affect. In a
second experiment, they redesigned the target pools to correct this imbalance and ob-
served significant improvement of AC functioning. We incorporate these findings into a
definition of target-pool bandwidth and propose that the proper selection of bandwidth
will lead to a reduction of incorrect information in free-response AC.
Effect sizes from forced-choice experiments are much lower than
those from free-response studies. For example, in precognition (Honor-
ton & Ferrari, 1989) and real-time (Honorton, 1975) forced-choice ex-
periments, the effect size (i.e., z/J) is 0.02, whereas in the free-response
ganzfeld (Bem & Honorton, 1994), the effect size is 0.159. Even if we
consider the ganzfeld response as a "forced-choice" among four alterna-
tives, the it effect size, which converts 1-in-n into an effective binary-
choice hitting rate (Rosenthal, 1991; Rosenthal & Rubin, 1989), is
0.5123 ? 0.0004 for card guessing and 0.5854 ? 0.0287 for the ganzfeld
(t(-2 x106) = 46.2, p = 0). The large t score is probably due to the large
number of forced-choice trials (i.e., 2 x 106). Considering that the mean
of the forced-choice effect size is 2.56 smaller than that of the ganzfeld,
however, there is clearly a meaningful difference. One potential source
of noise in forced-choice experiments, particularly when trial-by-trial
feedback is given, is memory of the previous trial and knowledge of the
complete set of possibilities. For example, suppose a receiver (i.e., par-
ticipant, subject) is asked to guess if a particular card from a normal
deck of playing cards is red or black. Suppose further that there is some
An earlier version of this paper was presented at the 37th Annual Convention of the
Parapsychological Association, held in Amsterdam, The Netherlands, August 7-10, 1994.
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304 The Journal of Parapsychology
putative information coming either from the card or from the mind of a
sender and that the receiver is a "good" imager (i.e., can easily picture a
brilliant image of a playing card in his mind). The receiver's task, then,
can be reduced to simple signal detection. Yet, if anomalous cognition
(AC) 1 is not a robust information-transfer mechanism (and it appears
that it is not), the "signal" is easily lost among the vibrant internal im-
agery from the memory of all alternative playing cards. The resulting
effect sizes, therefore, are reduced.
The ganzfeld itself was developed as a somatic-sensory noise reduc-
tion procedure (Honorton & Harper, 1974). Honorton argued that by
placing a receiver in a sensory-reduced environment, the receiver's reac-
tions to the environment would be sharply reduced, encouraging a com-
mensurate reduction of noise. On the basis of results from our current
work, we argue that a major contributor of noise in any free-response
study is cognitive and arises, in part, because of the target-pool design.
One result from the ganzfeld experiments suggests that dynamic tar-
gets produce stronger results than do static targets (Bem & Honorton,
1994). Lantz, Luke, and May (1994) attempted to replicate this finding
in two lengthy experiments in 1992 and 1993. The first of these ex-
plored, in a 2 x 2 design, the relationship between sender versus no-
sender and static-versus-dynamic target type on the quality of the AC.
Because Lantz et al. reported no significant effects or interactions as
having been due to the sender condition, we will ignore that aspect of
this first experiment. In the second experiment, they conducted all trials
without a sender and changed the characteristics of the target pool. This
paper describes the insights gained from these two studies, which led
both to the concept of target-pool bandwidth, and to a potential way of
reducing noise in free-response AC.
SUMMARY OF THE FIRST ANOMALOUS COGNITION EXPERIMENT-1992
We begin by summarizing the experiment and pertinent results from
a study that was conducted in 1992, the details of which may be found in
Lantz et al. (1994). In the experiment, a static-versus-dynamic target
condition was included to replicate the findings from the ganzfeld.
]The Cognitive Sciences Laboratory has adopted the term anomalous mental phenomena
instead of the more widely known psi. Likewise, we use the terms anomalous cognition and
anomalous perturbation for ESP and PK, respectively. We have done so because we believe
that these terms are more naturally descriptive of the observables and are neutral in that
they do not imply mechanisms. These new terms will be used throughout this paper.
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Managing the Target-Pool Bandwidth 305
Target Pools
For the static targets, Lantz et al. used a subset of 50 of our traditional
collection of magazine photographs (May et al., 1990). These targets
had the following characteristics:
Topic homogeneity. The photographs contained outdoor scenes of set-
tlements (e.g., villages, towns, cities), water (e.g., coasts, rivers and
streams, waterfalls), and topography (e.g., mountains, hills, deserts).
Size homogeneity. Target elements are all roughly the same size. That
is, there are no size surprises such as an ant in one photograph and the
moon in another.
Affectivity homogeneity. As much as possible, the targets included ma-
terials that invoke neutral affectivity.
This pool is perhaps better characterized by what it does not contain.
There are no people, animals, transportation devices, or situations in
which one would find these items-and no emotionally arousing pic-
tures.
The dynamic targets, on the other hand, followed lines similar to
those from the ganzfeld studies. Lantz et al. digitized and compressed
video clips from a variety of popular movies or documentaries. With the
exception of cartoons and sexually oriented material, the clips could
contain virtually anything. Examples included an indoor motor bike
race and a slow panoramic scan of the statues on Easter Island. Almost
all of the characteristics of the static target pool were violated. The only
common characteristic was thematic homogeneity within any given dy-
namic clip; across targets there were no restrictions on content.
Data Analysis and Results
For each response, a single analyst conducted (in the usual way) a
blind ranking of five targets-the intended one and four decoys. The
expected mean-chance rank was 3. Effect sizes were computed by:
LIC, - (RQ - R?)
where Nis the number of rank possibilities (i.e., 5 in our case) and RE
and Ro are the expected and observed average ranks, respectively. The
p values were computed from z = ES x '\Fn where n is the number of trials.
Each receiver participated in 20 trials for each target type, regardless
of sender condition. Table I shows the average rank, the effect size, and
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its associated p value for the static target condition. We see that the
combined data are significant and that two of our most experienced
receivers, Receivers 9 and 372, produced independently significant re-
sults.
TABLE 1
RESULTS FOR STATIC TARGETS-1992 EXPERIMENT

ES
p value
9
2.40
0.424
.034
131
3.10
-0.071
.653
372
2.40
0.424
.034
389
2.75
0.177
.240
518
2.60
0.283
.119
Totals'
2.65
0.247
3
6.8 x 10
'Totals are post hoc.
Table 2 shows the same data for the dynamic target condition.
TABLE 2
RESULTS FOR DYNAMIC TARGETS - 1992 EXPERIMENT
Receiver ES
p value
9 3.00 0.0
00 .500
131 2.50 0.3
54 .057
372 3.40 -0.2
83 .897
389 3.00 0.0
00 .500
518 3.10 -0.0
71 .624
Totals' 3.00 0.0
00 .500
'Totals are post hoc.
With the possible exception of Receiver 131, AC on the dynamic
targets failed to show any evidence of functioning. The difference be-
tween these two target conditions favors the static targets (t(198) = 1.75,
P< .08, two-tailed).
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Managing the Target-Pool Bandwidth 307
Hypothesis Formulation and Discussion
That static targets are better than dynamic ones is surprising, not only
because it fails to support the ganzfeld result, but also because it suggests
the opposite. There are a number of possible contributing factors for
this outcome. They include statistical artifacts, idiosyncrasies of our re-
ceivers compared to the ganzfeld participants, and procedural differ-
ences. Another possibility may be that, as in the ganzfeld, participants
used a rank-order technique for judging even though only the first-place
matches were used for the statistic. Because absolute measures of AC are
better than relative measures in process-oriented research, and because
the target type inference was based on relative measures, perhaps this
accounts for some of the result. A full discussion of these points may be
found in Lantz et al. (1994).
We propose a different explanation: A fundamental difference be-
tween the experiment's dynamic and static target pools is, in itself, a
source of noise.
The sources of noise in the forced-choice domain are reasonably
understood (i.e., memory in conjunction with complete knowledge of
the target-pool elements). A new insight for us was another potential
source of noise in the free-response domain. To understand this noise
source, we must first assume that AC data are weak and difficult to
recognize. Target pools that contain a large number of diverse cognitive
elements, in conjunction with receivers who believe that this is the case,
are a source of noise. Receivers will tend to report any imagined impres-
sions, for those impressions might be part of the target. Because AC is
assumed to be weak, most of the generated impressions are from the
receiver's imagination rather than from the target. Furthermore, it fol-
lows that the noise will increase when these impressions cannot be inter-
nally edited and must be reported. That is, noise is generated not so
much from an active imagination, but imagination coupled with an
agreement not to edit the internal experience.
Editing our internal experience is something we all do in our daily
communication. We rarely report to a friend that our mind momentarily
wandered during an interesting discussion. Humans appear to have an
ability for multi-processing, but we use situational filters to communicate
coherently. So, why would we deny this same ability to participants in AC
experiments? In Figure 1, we represent schematically the contributions
to the noise produced by memory and the noise produced by not editing
imagination.
As the number of differentiable cognitive elements in a target pool
increases from two (for a binary choice) to nearly infinite (for the uni-
verse), we propose that there is a trade-off between noise arising from
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308
The Journal of Parapsychology
memory and noise arising from unedited imagination. For target pools
containing fewer elements, the noise contribution from memory (i.e.,
the curve labeled "Memory" in Figure 1) exceeds impressions arising
from edited imagination. Regardless of one's internal fantasies, there is
usually a complete protocol restriction on allowable responses. The re-
verse is true for target pools that contain a large number of cognitive
elements: The contribution to the noise because of unedited imagina-
tion exceeds that arising from memory. In this case, protocols usually
suggest that receivers report nearly all internal impressions (e.g., in the
ganzfeld protocol), and because there will likely be far more of these
impressions than there are target elements, the noise is increased. At the
same time, because there are a large number of elements, and because
it is difficult to remember all possible elements and their factorial com-
binations, the contribution to the noise owing to memory is reduced.
Differentiable Cognitive Elements in the Target Pool
2 5
0
va
c
~'eq
Figure 1. Schematic representation of sources of cognitive noise.
We represent schematically the combination of these two sources of
noise by the U-shaped curve in Figure 1 labeled "Combination.'"Without
stretching the schematic nature of this argument, we propose that there
may be a target pool that minimizes the two noise contributions simulta-
neously. That is, if we can accept some noise from each source, we may be
able to prevent either from overwhelming the signal themselves.
We suggest that our photograph target pool represents one good
example: There are enough differentiable elements to reduce the
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Managing the Target Pool Bandwidth 309
effects of memory, but few enough to allow reasonable editing of inter-
nal experiences that arise from imagination.
The receivers in our experiments have, over time, learned the natural
limitations of the target pool by experience and by instruction. They
have become skilled at internal editing and do not report impressions
that they know are absent from the overall target pool. Thus, there is less
incorrect material in their responses.
In the Lantz et al. 1992 experiment, where the dynamic targets could
be virtually anything, the receivers were unable to produce significant
evidence of AC. They also produced, what is for us, significantly reduced
functioning with static targets. We speculate that this drop of function-
ing in both target conditions arose because the protocol would not allow
the receivers to edit their internal experience. The dynamic targets
could consist of anything, and the receivers were blind to the static-ver-
sus-dynamic target condition. They were therefore unable to edit their
imaginations, even for the static targets. To illustrate this point, suppose
that half the target pool was ESP cards and the other half was the ganz-
feld dynamic targets but that the receivers were blind to the target con-
dition. In any given trial, even though the target is actually the star ESP
card, the receiver is inclined to report all internal imagery, whether it be
cartoon figures, car races, or sex scenes from movies. This increases the
incorrect information over what it would be for a simpler target pool of
ESP cards alone.
A strong word of caution is in order. Editing of internal experience
because of sensory knowledge of the target pool cannot inflate a differ-
ential rank-order statistic. It will, however, bias any rating scale toward
larger values. This is not a problem if ratings are used in correlational or
comparative studies.
We define the term target pool bandwidth as the number of differenti-
able cognitive elements in the target pool. Forced-choice experiments
usually represent small bandwidths, video clips usually represent a large
bandwidth, and the magazine photographs represent an intermediate
bandwidth. At this time, the definition is qualitative, but we will indicate
ways in which it can be made more quantitative. Nonetheless, the target
pool bandwidth concept is testable.
The following hypotheses formed the basis of Lantz et al.'s second
study in 1993:
1. A significant increase of AC will be observed for dynamic targets
if the dynamic pool is designed with an intermediate target pool band-
width that matches the static pool from the 1992 study.
2. An increase of AC will be observed for static targets because the
receivers will be able to edit their internal experience.
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310 The Journal of Parapsychology
SUMMARY OF THE SECOND ANOMALOUS COGNITION EXPERIMENT: 1993
The details of the 1993 study may also be found in Lantz et al. (1994).
In that study, they included a static-versus-dynamic target condition to
replicate the findings from the ganzfeld, but dropped the sender condi-
tion: All trials were conducted without a sender.
Target Pools
For this experiment, Lantz et al. redesigned both the static and dy-
namic targets with the constraint that they all must conform to the topic,
size, and affectivity homogeneity of the original static targets. Surpris-
ingly enough, they identified a large number of videos that could be
edited to produce 50 segments comparable to the static targets: an air-
plane ride through Bryce Canyon in Utah or a scanning panoramic view
ofYosenrite Falls. They selected a single frame from within each dynamic
target video clip, which was characteristic of the entire clip, to act as its
static equivalent.
Thus, they were able to improve the target pools in two ways:
1. The dynamic pool possessed an intermediate target-pool band-
width.
2. The bandwidths of the dynamic and static pools were nearly iden-
tical, by design.
Data Analysis and Results
For each response, a single analyst conducted (in the usual way) a
blind ranking of five targets: the intended one and four decoys.. Lantz et
al. computed effect sizes in the same way as was done in the 1992 study.
Three receivers individually participated in 10 trials for each target
type, and a fourth, Receiver 372, participated in 15 trials per target type.
Table 3 shows the average rank, the effect size, and its associated p value
for the static target condition. We see that the combined data are signifi-
cant and that three of the four receivers produced independently signifi-
cant results.
Lantz et al. observed a significant increase of AC for the static targets
in the 1993 experiment compared to that of the 1992 experiment
(t(143) = 1.68, p< .047). Three of the four receivers were independently
significant, and their results improved from their 1992 effort. Thus, the
second hypothesis (i.e., an increase in AC for static targets) was strongly
supported. Table 4 shows the same data for the dynamic targets.
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Managing the Target-Pool Bandwidth. 311
TABLE 3
RESULTS FOR STATIC TARGETS: 1993 EXPERIMENT
Receiver
9
2.20
0.565
.037
372
1.87
0.801
9.7 x 10-4
389
3.10
-0.071
.589
518
1.90
0.778
7.2x103
Totals
2.22
0.550
1.1 x 10-5
TABLE 4
RESULTS FOR DYNAMIC TARGETS: 1993 EXPERIMENT
9
1.70
0.919
1.8x103
372
1.93
0.754
1.8 x 10-3
389
3.00
0.000
.500
518
2.40
0.424
.091
Totals
2.22
0.550
1.1 x 10,
Using the rank-order statistics just described, Lantz et al. saw no dif-
ference between static and dynamic targets in their 1993 study. The first
hypothesis was confirmed: They observed a significant increase of AC
with dynamic targets in 1993 from that of.1992 (t(143) = 3.06,
p