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REVIEW ARTICLE
published: 25 March 2014
doi: 10.3389/fnhum.2014.00146
Predicting the unpredictable: critical analysis and practical
implications of predictive anticipatory activity
Julia A. Mossbridge1*, Patrizio Tressoldi 2, Jessica Utts 3, John A. Ives4, Dean Radin 5and
Wayne B. Jonas 4
1Department of Psychology, Northwestern University, Evanston, IL, USA
2Dipartimento di Psicologia Generale, Universita di Padova, Padova, Italy
3Department of Statistics, University of California at Irvine, Irvine, CA, USA
4Samueli Institute, Alexandria, VA, USA
5Consciousness Research Laboratory, Institute of Noetic Sciences, Petaluma, CA, USA
Edited by:
Etzel Cardeña, University of Lund,
Sweden
Reviewed by:
Daryl J. Bem, Cornell University, USA
Douglas Miller Stokes, Freelance
Writer, USA
*Correspondence:
Julia A. Mossbridge, Department of
Psychology, Northwestern University,
2029 N. Sheridan Road, Evanston,
IL 60208, USA
e-mail: j-mossbridge@northwestern.edu
A recent meta-analysis of experiments from seven independent laboratories (n=26)
indicates that the human body can apparently detect randomly delivered stimuli occurring
1–10 s in the future (Mossbridge et al., 2012). The key observation in these studies is that
human physiology appears to be able to distinguish between unpredictable dichotomous
future stimuli, such as emotional vs. neutral images or sound vs. silence.This phenomenon
has been called presentiment (as in “feeling the future”). In this paper we call it
predictive anticipatory activity (PAA). The phenomenon is “predictive” because it can
distinguish between upcoming stimuli; it is “anticipatory” because the physiological
changes occur before a future event; and it is an “activity” because it involves changes in
the cardiopulmonary, skin, and/or nervous systems. PAA is an unconscious phenomenon
that seems to be a time-reversed reflection of the usual physiological response to a
stimulus. It appears to resemble precognition (consciously knowing something is going to
happen before it does), but PAA specifically refers to unconscious physiological reactions as
opposed to conscious premonitions.Though it is possible that PAA underlies the conscious
experience of precognition, experiments testing this idea have not produced clear results.
The first part of this paper reviews the evidence for PAA and examines the two most difficult
challenges for obtaining valid evidence for it: expectation bias and multiple analyses. The
second part speculates on possible mechanisms and the theoretical implications of PAA for
understanding physiology and consciousness. The third part examines potential practical
applications.
Keywords: presentiment, predictive coding, anticipatory activity, neural prediction, temporal processing
PART 1. THE EVIDENCE FOR PREDICTIVE ANTICIPATORY
ACTIVITY
Predictive anticipatory activity (PAA) is defined here as statistically
reliable differences between physiological measures recorded sec-
onds before an unpredictable emotional event occurs vs. seconds
before an unpredictable neutral event occurs. An emotional or
arousing event is defined as an event that activates the sympathetic
nervous system; while a neutral event activates the sympathetic
nervous system to a lesser degree or not at all. A colloquial defi-
nition of PAA is“sensing the future,” or presentiment (e.g., Radin,
1997,2004;Radin and Borges, 2009). Here we use the more
descriptive term PAA to indicate that this phenomenon is pre-
dictive of randomly selected future events, anticipates these events
more often than chance, and is based on physiological activity in
the autonomic and central nervous systems. In this section, we
present the evidence for this phenomenon. We then discuss its
implications (Part 2) and potential applications (Part 3).
Predictive anticipatory activity is postulated to be an uncon-
scious physiological phenomenon that may be thought of as
a preview of our conscious awareness of future emotional or
arousing events. A metaphor may help to provide an intuitive feel
for this effect – watching a river move past a stick. The metaphor
works as follows (Figure 1): imagine that the direction of the
water’s current is the conscious experience of the flow of time
(temporal flow), and imagine that an intrusion in the flow (the
stick) is an emotional, arousing, or otherwise important event. The
largest disturbance in the water made by the intrusion is down-
stream (in the “forward” time direction), which is analogous to
our conscious reaction to experiencing the important event. But
if one examines the flow of water near the stick, one will also see
a small perturbation upstream, anticipating the intrusion in the
water downstream due to the back pressure. Similar to PAA, this
upstream perturbation is a hint of things to come. It is not nor-
mally part of our conscious awareness and, as with disturbances
in a flow of water, the majority of the effect of an intrusion is
downstream of the intrusion.
In contrast to PAA, precognition maybedefinedasaperception
or a behavior (not a physiological measure) that is influenced by
future events. For example, a recent series of experiments pub-
lished in the Journal of Personality and Social Psychology suggested
that perception of a future event may influence decisions and
memory in the present (Bem, 2011; also see Maier et al., in press;
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Mossbridge et al. Predicting the unpredictable
FIGURE 1 |Back-pressure perturbations from a downstream intrusion
(an arousing/important event) in a stream of water may be a useful
metaphor for predictive anticipatory activity (PAA). We are not
normally conscious of PAA effects because downstream perturbations are
much larger in magnitude.
Ritchie et al., 2012). Though it seems plausible that precognition is
related to PAA, examination of that possibility is beyond the scope
of this article.
Experimental tests of PAA generally use one of two designs,
both of which involve a series of randomly interspersed emotional
and neutral events. The most common paradigm is one in which
participants passively view and/or listen to a series of stimuli that
are randomized in terms of stimulus type (e.g., emotional vs. neu-
tral). A less common paradigm is one in which participants actively
guess the outcome of each in a series of future events. In both
paradigms, care must be taken to ensure that a truly random series
of events is generated and that participants or experimenters can-
not infer the upcoming event type through usual sensory means.
Physiological data (skin conductance, heart rate, respiration rate,
EEG activity, etc.) are recorded continuously during the experi-
ment (Figure 2A) Each trial may be assessed on a trial-by-trial
basis (see Recommendations for Designing Reliable PAA Sensing
Tools, below), but more typically Tpre is evaluated by averaging it
across multiple trials of similar types (Figure 2B; e.g., emotional
vs. neutral) in the series.
More than 40 experiments investigating PAA in humans have
been published over the past 36 years (including: Hartwell, 1978;
Radin et al., 1995,2011;Bierman and Radin, 1997;Radin, 1997,
2004;Don et al., 1998;Bierman, 2000;Bierman and Scholte, 2002;
McDonough et al., 2002;Spottiswoode and May, 2003;McCraty
et al., 2004a,b;Sartori et al., 2004;May et al., 2005;Tressoldi et al.,
2005,2009,2011;Radin and Borges, 2009;Bradley et al., 2011).
This literature prompted a meta-analytic examination of PAA
to assess the combined evidence and repeatability of the phe-
nomenon (Mossbridge et al., 2012). The meta-analysis tested
the hypothesis that the difference between physiology preceding
emotional and neutral events is in the same direction as the dif-
ference after those same events; in other words, it tested the
hypothesis that the pre- and post-event physiological differences
have the same sign (positive or negative). Using statistically conser-
vative methods, the analysis revealed a small but highly statistically
significant effect size in support of the hypothesis [fixed effect:
overall ES =0.21, 95% CI =0.15–0.27, z=6.9, p<2.7 ×10−12 ;
random effects: overall (weighted) ES =0.21, 95% CI =0.13–
0.29, z=5.3, p<5.7 ×10−8]. Higher quality studies produced a
larger overall effect size and greater level of significance, indicating
that lack of quality was not responsible for the significant result
(Mossbridge et al., 2012)1.
It is important to note that a meta-analysis is only as good as the
data that it examines. Both questionable research practices (QRP)
and physiological artifacts have the potential to produce results
that mimic a PAA effect. If QRPs are sufficiently widespread, they
could potentially be responsible for the highly significant meta-
analytic results discussed here. Possible bias can be introduced
by experimenter fraud, selective reporting, filter artifacts imposed
on the raw data, multiple analyses, and anticipatory and order
effects. These and other possible explanations for PAA have been
critically examined and found to be lacking in explanatory power
(Mossbridge et al., 2012). Here we briefly examine two of the more
important criticisms of the evidence for PAA: multiple analyses
and order effects, with a focus on expectation bias.
CRITICISMS OF THE EVIDENCE FOR PAA
p-Hacking
One QRP that appears to be common throughout behavioral,
social and medical research is to try to create a statistically signifi-
cant effect using alternative analyses when the originally planned
analysis did not find a significant effect (Simmons et al., 2011).
If some of the PAA researchers used this technique to produce a
significant PAA result, without noting the results as post hoc, then
a meta-analysis based on those results would have an inflated out-
come. This activity, dubbed“p-hacking” because it involvescutting
through the data in many ways to obtain a p-value low enough
to declare statistical significance, is a concern when determining
the validity of any reported experimental phenomenon. The ques-
tion is whether p-hacking can explain the significant meta-analytic
results for PAA.
To answer this question the authors performed a meta-analysis
on a subset of the data. This subset consisted of studies using elec-
trodermal activity as the measure of interest, and the meta-analysis
of these studies confirmed the presence of a highly significant
overall effect (Mossbridge et al., 2012). Electrodermal activity
measures have fewer parameters than EEG and fMRI data, so
a researcher who wished to perform p-hacking would have few
parameter choices and thus fewer chances to get a significant effect.
One critical parameter in electrodermal studies is the duration of
the pre-stimulus activity under examination (Tpre). Interestingly,
within each publication and more often than not between pub-
lications, experimenters who performed multiple studies using
1Another meta-analysis using Bayesian statistics and including tests of PAAas well as
tests for several other non-ordinary experiences revealed similar results (Tressoldi,
2011), but because that meta-analysis was not limited to PAA alone, it is beyond the
scope of this review.
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Mossbridge et al. Predicting the unpredictable
FIGURE 2 |Schematic of a generalized PAA trial and overall results.
(A) One trial of a series of trials. The pre-event (Tpre), event (Tevent), and
post-event (Tpost ) durations are on the order of seconds. The physiological
activities of interest are recorded continuously throughout the series of
trials. (B) PAA effect. Data recorded during Tpre are baselined to a period
preceding Tpre and are most often averaged across trials within each event
type to provide an average Tpre response for the emotional event and an
average Tpre response for the neutral event.The PAA effect is usually
defined by the difference between these two averaged changes in Tpre
physiology.
electrodermal activity as a measure of interest consistently used
the same Tpre duration (most often3sbeforethestimulus), even
when significant results were not found (see Anticipatory Period
column in Appendix table A1; Mossbridge et al., 2012). This is not
behavior that is consistent with p-hacking strategies.
Another feature of the same PAAmeta-analysis was that it tested
a hypothesis that differed from any explicit hypothesis stated by
the authors of the original studies. That is, for the studies included
in the meta-analysis, when a hypothesis was formally stated it
was of the form that there would be a statistically reliable differ-
ence between the pre-event physiology for an emotional upcoming
event as compared to another (relatively neutral) upcoming event.
The direction of this difference was usually not predicted. How-
ever,the hypothesis of the PAA meta-analysis was that the direction
of the pre-event difference would explicitly mirror the direction
of the post-event difference (Mossbridge et al., 2012). In other
words, if the direction of the pre-event difference in a physio-
logical measure was the same as the direction of the post-event
difference in the same physiological measure, the effect size for
the study was given a positive sign (in support of the hypothe-
sis), and if the direction of the pre- and post-event differences
were not the same, then the effect size was given a negative sign
(in contradiction to the hypothesis). Thus, even if researchers p-
hacked to get a significant effect in an individual study, it would
not necessarily be an effect in the same direction as that tested
by the meta-analysis, and therefore it would not necessarily sup-
port the hypothesis of the meta-analysis. In fact, several studies
examined in the meta-analysis did show effects in directions that
opposed the hypothesis of the meta-analysis itself. In this way
the meta-analysis was decoupled from one possible source of p-
hacking. Nevertheless, the cumulative results remained highly
significant.
From these analyses, it appears that p-hacking and other forms
of unreported multiple analyses are not a compelling explanation
for PAA. However, it is always possible that the evidence for PAA
is influenced by more subtle variations in analyses. Until there is
a gold standard experiment that is replicated across laboratories
using exactly the same experimental procedure, physiological mea-
sures, and statistical analyses, there remains the possibility that
multiple analyses could influence the body of evidence support-
ing PAA. Toward this end, we recommend that all researchers
who investigate PAA register their experiments in advance, at
any of several registries designed for experiments examining
exceptional experiences2or at a general experimental research
registry3.
Order effects and expectation bias
Order effects may occur in any experiment with multiple sequen-
tial trials, including PAA studies. For example, forward priming
describes a situation in which previous events influence responses
to future events. Thus, responses to the word “flower” are faster
if the word is preceded by the word “tree” vs. the word “knife”
(Meyer and Schvaneveldt, 1971). Psychophysiologists who wish
to avoid priming effects typically use randomization methods to
help ensure that it is unlikely for a majority of the participants to
systematically experience the same trial order. This increases the
likelihood that spurious order effects will average out over partic-
ipants and will not influence the cumulative results. In addition,
the greater the number of trials in any given experiment, the less
likely that similar trial orders may occur. If order effects are largely
responsible for PAA, there should be a significant negative correla-
tion between study effect size and the number of trials performed.
However, this is not the case (Mossbridge et al., 2012).
While order effects do not appear to be a problem in these
data, expectation bias is a more subtle effect that requires closer
examination. Expectation bias is related to the human propensity
to expect a “tail” in a coin toss after observing a series of “head”
outcomes (the gambler’s fallacy). The reason expectation bias can
potentially explain PAA is that a series of (randomly selected)
2http://www.koestler-parapsychology.psy.ed.ac.uk/TrialRegistry.htmlxsxsxs
3https://osf.io/
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Mossbridge et al. Predicting the unpredictable
neutral stimuli may produce a physiological shift toward excite-
ment as the presumably imminent emotional trial approaches.
In a sequence of trials with several such series of neutral events
preceding emotional events, simulations suggest that the result-
ing physiological data could mimic a PAA effect (Dalkvist et al.,
2002;Wackermann, 2002). Thus to understand the mechanisms
underlying PAA, it is crucial to determine for each PAA experi-
ment whether expectation bias was a potential explanation for the
reported outcome.
There are several ways to quantify expectation bias. For exam-
ple, one can examine a plot of the physiological measure of interest
during Tpre for an emotional event vs. the number of neutral tri-
als preceding that emotional event. If expectation bias is a viable
explanation for the PAA effect in a given experiment, then the
activity during Tpre for emotional events with greater numbers
of neutral events preceding them will be larger than for those
with fewer neutral events preceding them (Radin, 2004). Of the 26
studies examined in the recent PAA meta-analysis, 19 of them used
this method or similar methods to empirically determine whether
expectation bias could explain the PAA effect. None of them found
that it could. Further, the overall effect size of the subset of stud-
ies that performed expectation bias analyses was greater than the
effect size of the seven studies that did not perform such analy-
ses, lending little support to the idea that expectation bias creates
the PAA effect in general (Mossbridge et al., 2012). However, it is
worth noting that studies revealing larger effects usually include
more details about attempts to account for mundane explanations
such as expectation bias, so there may be an inherent bias here.
Several statistical methods can be used to correct for expec-
tation bias if evidence for that bias is found (e.g., Dalkvist et al.,
2013). At least one of us (Mossbridge) has found an expecta-
tion bias effect in one PAA study, but because removing the bias
produced a larger PAA effect, expectation was not a viable expla-
nation. The bias was removed by discarding data from all but
the first trial of the experimental session, because any significant
PAA effect on the first trial could not be explained by expectations
produced by preceding trials (Mossbridge et al., 2011). Impor-
tantly, this method revealed a larger PAA effect than the traditional
trial-averaging method (compare Figures 1–6 in Mossbridge et al.,
2012). This stronger effect could be due to the reduction of “tem-
poral blurring” when physiological measures preceding only the
first trial are examined (see Implications of PAA for Physiology
and Consciousness Research, below). Based on this larger effect
when only the first trial is considered, experiments are underway
in which each individual performs only a single trial4. Despite
obvious drawbacks due to the increase in inter-individual noise,
and the effort involved in collecting data, this approach guarantees
that expectation bias is not a viable explanation for any observed
PAA effect.
The remainder of this article is based on the assumption that
PAA reflects a true anticipatory prediction rather than being
a physiological artifact or the result of bias and QRP. This
assumption is made to allow us to explore the concept of PAA
beyond the initial existential question.
4Dick Bierman has also performed a slightly different protocol of the single-trial
study and found a presentiment effect, but this has not been published.
TYPES OF ANTICIPATORY PHYSIOLOGICAL ACTIVITY
Three broad categories of anticipatory physiological effects are well
established in neuroscience and psychophysiology: anticipation of
intentional motor activity, anticipation of stimulus detection, and
anticipation of a complex firing pattern. PAA may be a novel,
fourth category, or it may overlap with one or more of the three
established categories.
Anticipation of intentional motor activity is supported by neu-
rophysiological evidence indicating that the neural anticipation
of our conscious awareness of having a will to move occurs at
least 500 ms (Libet et al., 1983;Haggard and Eimer, 1999) and
as much as 10 s (Soon et al., 2008;Bode et al., 2011) before the
first conscious report of the will to move. Anticipation of stimulus
detection is supported by the fact that EEG alpha activity during
the pre-stimulus period for trials presenting stimuli that will be
detected differs from alpha activity during pre-stimulus periods
preceding stimuli that will not be detected (Ergenoglu et al., 2004;
Mathewson et al., 2009;Panzeri et al., 2010). The explanation here
is that specific phases and/or amplitudes of neural oscillations
facilitate or suppress detection of the upcoming stimulus. Also,
anticipation during sleep of a complex firing pattern to be used in
the future, a phenomenon dubbed“preplay,” has been observed in
mouse hippocampal neurons during sleep before entering a novel
maze (Dragoi and Tonegawa, 2011). The firing pattern recorded
during sleep has greater-than-expected similarity to the patterns
recorded when the mouse eventually navigates the maze, an effect
explained by the researchers with the idea that the hippocampus
recycles generalizable firing patterns from its recent history to cre-
ate the complex firing patterns accompanying spatial exploration.
For these three categories of anticipatory effects, reasonable expla-
nations using the usual cause-preceding-effect assumption are
sufficient to explain the results. The usual causal temporal assump-
tions do not suffice, however, when attempting to understand PAA,
because it apparently represents a statistically reliable retrocausal
effect. In the next section we examine potential mechanism for
PAA.
PART 2. POTENTIAL MECHANISMS FOR PAA AND
IMPLICATIONS OF PAA
POTENTIAL MECHANISMS FOR PAA
Delayed conscious experience
One seemingly reasonable explanation for PAA is that our con-
scious mind is wrong about when events occur. That is, our
conscious experience of events is delayed by seconds relative to
some external/physical time of which we are not conscious. Mean-
while, unconscious neural processes are much less delayed relative
to this external time. The explanation goes as follows: one impor-
tant role of the unconscious is to assess the environment and
mobilize physiological resources when it senses challenging exter-
nal events. Once resources are mobilized and the body is readied,
the conscious mind is presented with an ordered version of events
that is necessarily temporally delayed so the conscious mind does
not initiate counter-productive actions that might interfere with
the preparation of physiological resources. Because challenging
external events can occur at any time, the conscious mind is
always receiving delayed and filtered information about sensory
and motor events. Virtually all behavior is unconscious, and
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Mossbridge et al. Predicting the unpredictable
conscious awareness rides on top of this activity like an unfolding
and delayed story.
This delayed conscious experience hypothesis predicts that we
should find brain areas with activity that predicts upcoming con-
sciously perceived events seconds before they occur. As mentioned
previously, outside the PAA literature, Bode et al. (2011) and Soon
et al. (2008) have reported that up to 10 s before the conscious
experience of a decision to produce a motor event, brain activ-
ity predicts conscious decisions. These data support the delayed
conscious experience hypothesis, but do they reflect PAA?
Although PAA may seem like a sensory counterpart to the pre-
dictive coding observed in the motor system, it differs in terms of
the order of events and by not involving inferred events or making
a decision. In PAA experiments, the physiological and stimulus
events are in the wrong order to be explained causally, and they
are time-stamped by a computer (not subjectively reported by
research participants). Regardless of the absolute times when these
events occur,a physiological reaction occurs before the stimulus to
which it seems to be linked. Thus PAA neither supports nor refutes
the delayed conscious experience hypothesis, but this hypothesis
is not a viable explanation for PAA.
Quantum biology
A potentially more viable way to understand PAA effects is that
they might reflect an epiphenomenon associated with quantum
processing in biological systems. Aharonov et al. (1964,1988)
suggested that one way to explain quantum effects is via inter-
actions between future and past events. This idea has recently
been supported by advances in quantum measurement, so-called
“weak measurements,” which demonstrate that observations in
the future do indeed affect observations in the past (Aharonov
et al., 1964,1988;Hosten and Kwiat, 2008;Dixon et al., 2009). Fur-
ther support of a similar “retrocausal” phenomenon in physics is
provided by experimental verification of delayed-choice entangle-
ment (Ma et al., 2012). Finally, because quantum effects have been
shown to manifest in biological systems at physiological tempera-
tures, e.g., in photosynthetic reactions (e.g., Scholes,2011;Dawlaty
et al., 2012;Olaya-Castro et al., 2012), it is no longer inconceivable
that retrocausal quantum effects can occur in the human nervous
system.
However, one problem with a quantum biological explanation
for PAA is that retrocausal effects on the order of seconds would
have to be explainable via quantum processes, and we know of no
evidence so far that these effects can occur at that time scale5.
Nevertheless, exploration into biological quantum effects is in
its infancy, and most biological models have yet to entertain the
consequences of retrocausation. Thus, the idea that PAA may be
related to quantum effects is speculative and currently difficult
to test. However, the quantum biology hypothesis demonstrates
the value of anomalous phenomena in driving science forward
by motivating scientists to search for novel explanations based
on emerging scientific concepts. For further discussion of the
philosophical and quantum mechanical arguments for time sym-
metry and retrocausation the reader is referred to an article on
5Elementary forms of coherence vanish quickly, but it is possible that coherence in
living systems might be “pumped”and sustained for a relatively longer time.
backward causation in the Stanford Encyclopedia of Philosophy6
and to Bierman (2010).
IMPLICATIONS OF PAA FOR PHYSIOLOGY AND CONSCIOUSNESS
RESEARCH
Physiology
The most mundane implication of PAA for physiologists is that the
time-honored convention of establishing a baseline for physiolog-
ical post-event measures by subtracting mean pre-event activity
may obscure important physiological effects in two ways (Bier-
man and Radin, 1997;Mossbridge et al., 2012). First, by assuming
that pre-event activity is equivalent between event types (without
testing this assumption), PAA may be hiding in plain sight. Indeed,
several re-examinations of pre-event activity reported in psy-
chophysiology studies conducted for other purposes suggest that
the PAA effect actually is present but overlooked (Bierman, 2000;
Mossbridge et al., 2012). Of course, when researchers are perform-
ing a conventional psychophysiology experiment it is unlikely that
they will feel the need to closely examine expectation bias or use
truly random techniques to specifically rule out order bias. Thus
PAA results found in data from such studies could potentially be
due to these mundane explanations.
A second way that baselining data to pre-event physiological
activity could obscure important physiological effects is by falsely
increasing or decreasing post-event physiological differences. This
can occur because pre-event activity is rarely equivalent between
event types due to PAA, so subtracting these differing values can
produce misleading post-event data as a result.
A more intriguing implication of PAA for those attempting to
understand human physiology is that there seems to be a cor-
relation between pre- and post-event responses, such that the
magnitude of a post-event response seems to correlate with the
magnitude of the corresponding pre-event response. Note that a
simple correlation between pre- and post- responses is not what
is being discussed here; certainly across individuals there is a
strong correlation between the physiological state before and after
any event, partially due to the fact that there are stronger inter-
individual physiological variations than intra-individual varia-
tions. Instead, what has been observed is a correlation between the
magnitude of the change in a physiological measure before an event
and the magnitude of a change of that physiological measure after
the event. We call this “temporal mirroring.” To investigate the idea
of temporal mirroring in PAA, Radin (2004) quantitatively tested
temporal mirroring using independent ratings of emotionality
for different stimuli and found a significant correlation between
pre-stimulus response size and stimulus emotionality. In another
study,men had large blood-oxygen level dependent (BOLD) post-
responses to erotic images randomly distributed along with violent
and neutral images, and in men the only significant PAA effect
occurred for erotic but not violent images (Bierman and Scholte,
2002). Meanwhile, women in the same study had large BOLD post-
responses to violent but not erotic images, which also matched
their PAA effects. Others have noted similar gender effects for
which post-event differences in responding mirrored pre-event
6http://plato.stanford.edu/entries/causation-backwards/
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Mossbridge et al. Predicting the unpredictable
differences (McCraty et al., 2004b;Radin and Lobach, 2007;Radin
and Borges, 2009;Mossbridge et al., 2011).
Another parameter dependence suggesting temporal mirror-
ing is the relationship between PAA effects for single-modality
events (auditory or visual stimuli presented alone) vs. events
that are more ecologically valid in that they incorporate multiple
modalities (e.g., emotional auditory and visual stimuli presented
simultaneously). Well known in the multimodal literature is the
idea that responses to stimuli presented in multiple modalities are
more robust than responses to each modality alone (e.g., Meredith
and Stein, 1986;Meredith et al., 1987). According to the“Hypoth-
esis of Functional Equivalence,” any pre-stimulus PAA activity,if it
exists, should be drawn on with same readiness as a post-stimulus
response to a stimulus (Carpenter, 2012), supporting the func-
tional value of temporal mirroring. Along these lines, in at least
one report (Radin, 2004), PAA effects for events presented using
multiple modalities are quantitatively larger than PAA effects for
single-modality events, though several methodological differences
between experiments preclude strong conclusions being drawn
from these data.
Thus, it appears that the pre- and post-event physiological
responses may mirror one another in size across participants
(though pre-event responses are generally smaller than their post-
event counterparts), implying that physiological processes are
predicting either the importance of the future event to the organ-
ism or perhaps the future physiological response itself. These two
interpretations may seem similar, but they have different implica-
tions for understanding the physiological mechanisms underlying
PAA. The idea that PAA predicts the importance of the future
event to the organism suggests that even if no physiological post-
event response occurs due to some manipulation of the organism’s
physiology or due to a probable event not occurring, PAA would
occur before a highly probable important event. In contrast, if PAA
predicts an organism’s future physiological response, then no PAA
effect would occur if no physiological post-event response occurs.
These differing interpretations of the pre-to-post-event mirroring
phenomenon have important implications for applications that
attempt to harness and amplify PAA, and these implications will be
discussed below (see Part 3: PotentialApplications of PAA Sensing
Tools).
One final implication of PAA for our understanding of physi-
ological systems is that PAA responses apparently decay with time
prior to an event. If the size of a PAA response did not decay with
time, one would never expect to find PAA, as arbitrarily timed
future events that are important would be “temporally blurred”
with arbitrarily timed future events that are not important. This
is clearly not the case, as inter-trial intervals as short as 10 s have
produced significant PAA effects. This does not necessarily mean
that PAA effects completely vanish beyond 10 s, but it does indi-
cate that there is some decay of PAA with time preceding the
event. Thus, the physiological mechanisms underlying PAA are
temporally localized in relation to each event7.
7The temporal issue might be related to the boundary conditions of each trial. In
other words, the backward temporal information flow could end with the presen-
tation of the stimulus. This could potentially be tested by delaying feedback over
multiple trials, some of which are a long sequence of emotional targets, and some
of which are a long sequence of calm targets.
Consciousness
A major implication of PAA for our understanding of con-
sciousness is that there must be a necessity for PAA to remain
non-conscious most of the time. That is, for most people at
most times there is a clear difference between the forward tem-
poral flow of information and experience of which we are aware
and a seemingly symmetric flow of information within the non-
conscious portions of our experience, as evidenced by the existence
of PAA. Why should this be the case? If some part of our ner-
vous system can obtain information about events seconds in the
future, would we not have evolved to make this information
conscious?
One answer to this question is that the information is not
conscious because most of the time it is not useful, like the major-
ity of information that is processed unconsciously. Under this
assumption, the mirroring of future physiological states by our
unconscious physiological processes is just a side effect of how
physiological systems (and in a more general sense the unfolding
of events in time) work. The idea is that there has to be a physio-
logical post-event response to produce the PAA prediction of that
response, so there is then no point to being consciously aware of
PAA effects as the event will occur in short order and there may be
nothing we can do to stop it.
A seemingly paradoxical PAA experiment called a “bilking
experiment” is one in which a participant’s PAA response is used
to avoid a future emotional event that presumably caused the PAA
response to occur in the first place. If such a PAA response can
be shown to exist when there is no accompanying future emo-
tional event, this would invalidate the idea that PAA requires a
post-stimulus response and would support the idea that PAA pre-
dicts probable vs. actual events. One of us (Tressoldi et al., 2013)
has preliminary data that support this idea. However, such bilk-
ing experiments are in their infancy, making it difficult to draw
conclusions.
Another answer to “Why aren’t we conscious of PAA?” is that
the conscious mind is not especially skilled at making quick deci-
sions. Unconscious processing is increasingly being recognized as
a powerful resource that provides the results of its calculations to
conscious awareness for further use and elaboration (e.g., Kah-
neman, 2011). Converging evidence suggests that unconscious
processing can result in learning and decision making that bet-
ters, or at least matches, those resulting from conscious processing
(e.g., De Houwer et al., 1997;Dijksterhuis et al., 2006;Strick et al.,
2011;Voss et al., 2012;Atas et al., 2013;Hassin, 2013). Thus, it
might be evolutionarily advantageous for unconscious processing
to assess upcoming events, filter them, mobilize resources, and
only then inform conscious awareness (see Potential Mechanisms
for PAA and Delayed Conscious Experience, above).
PART 3. POTENTIAL APPLICATIONS OF PAA SENSING TOOLS
Assuming we can understand PAA well enough to amplify and
characterize it for a given event of interest, the potential uses of
PAA-sensing tools (PAASTs) largely depend on the delay between
the PAA signal and the event of interest. Potential applications
also depend on whether the PAA is caused by the high a priori
probability of an emotional event or is the result of an actual and
unavoidable emotional event.
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Mossbridge et al. Predicting the unpredictable
Applications that could benefit from a few seconds advance
notice may include: slamming on the brakes of a vehicle to prevent
a crash, taking cover in advance of an explosion, or in gen-
eral orchestrating quick movements to effect a fortuitous result
within a few seconds. Applications requiring 10s of seconds might
include: course corrections for vehicles, preparing to move out of
a location, locating a hiding spot and then hiding there, preparing
for a medical emergency, communicating information verbally, or
in general, orchestrating more complex chains of action.
POTENTIAL ROADBLOCKS TO DESIGNING RELIABLE PAA SENSING
TOOLS
How does one amplify and characterize PAA for an event of interest
so that one can determine the practical temporal window of usabil-
ity for a PAAST? The amplification and characterization process
itself could present several difficulties, which we speculate about
here (see Recommendations for Designing Reliable PAA Sensing
Tools, below, for potential solutions to these problems).
One critical problem to overcome during the characterization
process is that when a PAAST is used outside of the laboratory,
many events occur beyond the event of interest. For instance, one
potentially life-saving application of PAASTs could be to predict
the detonation of an improvised explosive device (IED). A PAAST
device, when working perfectly, would emit an alert 10–20 s before
the detonation of an IED, providing time to avoid the device or
take cover. When working well, the PAAST device should not
be triggered by emotional events such as an individual soldier’s
phone call from a friend or a near miss in a firefight. The specific
physiological PAA “signature” of a soldier to the IED detonation
must be isolated.
When the signal is characterized and is being amplified, time
course is likely critical. Any “temporal blurring” that might occur
due to an overlap in physiological responses either before or after
the IED detonation must be minimized. For example, if a soldier
goes into a simulation where he will be faced with 20 IED deto-
nations in a short time period, a temporal blurring of his or her
physiology may occur because responses to later detonations will
include responses to previous detonations.
A third potential roadblock is that in the process of charac-
terizing and amplifying PAA to a simulated IED detonation, the
event itself may become uninteresting, producing small post-event
physiological responses. If the post-event physiological response
is small, this would likely reduce the size of the matching PAA
response (see Physiology, above). Thus a soldier must be kept
engaged and the simulated IED detonation must maintain its
emotional and cognitive impact value.
Finally,i t is important to addressa p erceived paradox that seems
like a potential stumbling block, but may not be. The paradox goes
like this: if PAA is a reflection of the future physiological state of an
individual, and the actions taken once a PAA alert is given change
the physiological state of that person, the PAA alert may not work
in the first place. Imagine this scenario (Figure 3A): a PAAST
gives a soldier an IED alert. The soldier takes cover away from a
nearby trash heap but hears the sound of the subsequent explosion
of the IED. The soldier has a typical post-detonation emotional
response, which is what produced the PAA alert. Now imagine
FIGURE 3 |Schematic illustrating two possibilities for the operation of a
PAA-sensing tool. (A) A soldier sees the PAA alert, takes cover, and sees the
IED explosion from a safe location. (B) A soldier sees the PAA alert, takes
cover, and does not see or hear the IED explosion. Note that in either case,
injury was avoided, even though the second case seems theoretically
paradoxical (see text for details).
Frontiers in Human Neuroscience www.frontiersin.org March 2014 |Volume 8 |Article 146 |7
Mossbridge et al. Predicting the unpredictable
this paradoxical scenario (Figure 3B): a PAAST gives a soldier an
IED alert. The soldier hides in a tank and puts on headphones.
The soldier does not have a typical post-detonation emotional
response, so there could not have been a PAA alert. However,
there was a PAA alert. How could this work? If the second sce-
nario can occur, it means one of two things: (1) that PAA does
not reflect the future physiological state of the individual, or (2)
that a non-typical post-detonation response is still an emotional
response to saving one’s own life and so can still produce PAA.
The PAAST still saved the soldier’s life, regardless of how it worked
(see above for Potential Mechanisms for PAA and Implications of
PAA). There may be a theoretical paradox here8, but perhaps not a
practical one.
RECOMMENDATIONS FOR DESIGNING RELIABLE PAA-SENSING TOOLS
Recommendations for designing reliable PAASTs are speculative,
as they are based on results from studies varying broadly in their
events of interests, methodology, and participants. However, here
we make an attempt to outline best practices, as they would
currently be defined, for designing a reliable PAAST.
The first step in designing any PAAST would seem to be finding
the time course of the decay of PAA for the event of interest.
Again, taking the example of IED detonation, once this delay is
known, the optimal inter-detonation interval to produce the most
reliable PAA effect will become apparent, and the usefulness of that
delay can be assessed for the application. Thus, one critical initial
experiment would be to use variations in the inter-detonation
interval to determine the extent to which the PAA effect can be
amplified by reducing temporal blurring with respect to the PAA
response (see Implications of PAA for Physiology and Consciousness
Research and Physiology, above).
After finding the critical delay for the IED detonation event
across a group of soldiers, the next step would be to characterize
the specific physiological “tell” or signature of each soldier who will
be using the PAAST. What are the respiration, temperature, blood
volume, skin conductance, EEG,and heart rate signatures for each
soldier? Obtaining this information would require exposing each
soldier to multiple simulated experiences with IED detonations.
Based on the little knowledge we have about PAA, these simulation
protocols should share several characteristics. To ensure the robust
emotional responses that produce reliable PAA, each simulated
IED detonation should include at least auditory and visual infor-
mation, with somatosensory and olfactory cues where possible.
To reduce the influence of responses to previous events (tempo-
ral blurring) and to ensure continued strong responses after the
upcoming event that seem to produce strong PAA (temporal mir-
roring), delays between simulated detonations should be relatively
long (on the order of minutes or hours) and randomly timed.
To ensure the generalizability of the PAA signature across mul-
tiple situations, detonations should occur in differing scenarios.
Because the device must distinguish PAA to IED detonations from
emotional responses to other events, events causing emotional
responses (but that are not IED detonations) should be inter-
mixed within the series of IED detonations. Finally, to ensure
the continued autonomic responses to the IED detonation, any
8If PAA predicts probable rather than actual futures,there would be no paradox.
decrement in the post-stimulus response should be monitored
and the simulation stopped at this point and resumed again when
the post-stimulus response is robust.
During the entire simulation time, the soldier should be mov-
ing and behaving in a life-like environment while physiological
data are being recorded continuously. Once enough simulated IED
detonations are recorded (likely 30–60), the data from multiple
physiological systems preceding each detonation can be analyzed
on a trial-by-trial basis using non-linear machine-learning meth-
ods to find the characteristic PAA for that soldier. The reason we
suggest automated learning is that non-linear, complex relation-
ships between physiological variables and their time courses could
exist that allow a fuller characterization of PAA. Along this line of
thinking, one of us (Mossbridge) has preliminary data showing
that such algorithms may be able to use EEG activity to determine
the correct response to an upcoming random event (pressing the
left or right mouse key as a correct response to an unpredictable
event) on a trial-by-trial basis with above 75% accuracy in ¾ of
untrained individuals9. We note that without the use of machine
learning, finding the combination of electrodes and time points
that would produce this predictive effect would have been difficult.
Characterizing the PAA for each soldier could be time consum-
ing, and one possible way to reduce this investment is to screen
soldiers to find those who have particularly reliable PAA effects,
then characterize PAA to simulated IED explosions in only those
soldiers. These PAA-sensitive soldiers could then use the result-
ing personalized PAAST as “a canary in the coal mine” for their
whole team. Another possible time-saving method might be to
run multiple soldiers on the IED simulation, then combine their
data to characterize a generalized PAA to the simulated IED deto-
nations that can be applied to soldiers who were not tested in the
simulated environment. The reliability of this method, of course,
would depend on the physiological similarity between the soldiers
from whom the data were obtained and those in the field. One
possible way to bridge this difference would be to use a generic
PAAST on multiple soldiers in combat, so that, for instance, if
three of four soldiers have their PAAST activated, all four soldiers
would take cover. Assuming an algorithm combining the soldiers’
data would not alert the soldiers when only one soldier has a PAA
response, this kind of generic physiological profile/multiple-user
approach could potentially also reduce the chance of false alarms
and increase the likelihood of avoiding real danger.
SUMMARY AND CONCLUSIONS
In summary we have made the following points in this article.
•PAA, the predictive physiological anticipation of a truly ran-
domly selected and thus unpredictable future event, has been
under investigation for more than three decades, and a recent
conservative meta-analysis suggests that the phenomenon is real.
•Neither QRP, expectation bias, nor physiological artifacts seem
to be able to explain PAA.
9For study results from the registered analysis, see http://www.koestler-
parapsychology.psy.ed.ac.uk/Documents/Study_Results_1004.pdf. Note that
because the final analysis producing a significant effect was exploratory rather than
confirmatory, these results should be replicated before any strong conclusions are
drawn.
Frontiers in Human Neuroscience www.frontiersin.org March 2014 |Volume 8 |Article 146 |8
Mossbridge et al. Predicting the unpredictable
•The mechanisms underlying PAAare not yet clear, but two viable
yet difficult-to-test hypotheses are that quantum processes are
involved in human physiology or that they reflect fundamental
time symmetries inherent in the physical world.
•The evidence indicates that there is a temporal mirroring
between pre- and post-event physiological events, so that the
nature of the post-event physiological response is a reflection of
the characteristics of the PAA for that event.
•Temporal blurring, in which closely overlapped emotional
events may confuse or minimize both post-event responses and
PAA before the event, may be a critical factor in isolating and
amplifying PAA.
•The principles of temporal mirroring and temporal blurring
both guide the recommendations for designing reliable PAASTs.
•Future research with multiple stimulus modalities, long inter-
trial intervals, multiple individuals simultaneously exposed
to the same stimulus, and machine-learning techniques
will advance our understanding of the nature of PAA and
allow a better harnessing of the delay before future events
unfold.
REFERENCES
Aharonov,Y.,Albert, D. Z., and Vaidman, L. (1988). How the result of a measurement
of a component of the spin of a spin-1/2 particle can turn out to be 100. Phys.
Rev. Lett. 60, 1351–1354. doi: 10.1103/PhysRevLett.60.1351
Aharonov, Y., Bergmann, P. G., and Lebowitz, J. L. (1964). Time symmetry
in the quantum process of measurement. Phys. Rev. 134, B1410–B1416. doi:
10.1103/PhysRev.134.B1410
Atas, A., Faivre, N., Timmermans, B., Cleeremans, A., and Kouider, S. (2013).
Nonconscious learning from crowded sequences. Psychol. Sci. 25, 113–119. doi:
10.1177/0956797613499591
Bem, D. (2011). Feeling the future: experimental evidence for anomalous retroac-
tive influences on cognition and affect. J. Pers. Soc. Psychol. 100, 407–425. doi:
10.1037/a0021524
Bierman, D. (2000). Anomalous baseline effects in mainstream emotion research
using psychophysiological variables. J. Parapsychol. 64, 239–240.
Bierman, D. (2010). Consciousness induced restorationof time-symmetry (CIRTS),
a psychophysical theoretical perspective. J. Parapsychol. 74, 273–300.
Bierman, D., and Radin, D. (1997). Anomalous anticipatory response on
randomized future conditions. Percept. Mot. Skills 84, 689–690. doi:
10.2466/pms.1997.84.2.689
Bierman, D., and Scholte, H. (2002). A fMRI brain imaging study of presentiment.
J. ISLIS 20, 380–389.
Bode, S., He, A. H., Soon, C. S., Trampel, R., Turner, R., and Haynes, J. D. (2011).
Tracking the unconscious generation of free decisions using ultra-high field fMRI.
PLoS ONE 6:e21612. doi: 10.1371/journal.pone.0021612
Bradley, R., Gillin, M., McCraty, R., and Atkinson, M. (2011). Non-local intu-
ition in entrepreneurs and non-entrepreneurs: results of two experiments using
electrophysiological measures. Int. J. Entrep. Small Bus. 12, 343–372. doi:
10.1504/IJESB.2011.039012
Carpenter, J. (2012). First Sight: ESP and Parapsychology in Everyday Life. Lanham,
MD: Rowman & Littlefield Publishers.
Dalkvist, J., Mossbridge, J., and Westerlund, J. (2013). How to handle expecta-
tion bias in presentiment experiments. Paper Presented at the Proceedings of the
Parapsychological Association, 56th Meeting, Paris.
Dalkvist, J., Westerlund, J., and Bierman, D. (2002). “A computational expectation
bias as revealed by simulations of presentiment experiments,” in Proceedings of
the 45th Annual Convention of the Parapsychological Association, Paris, 62–79.
Dawlaty, J., Ishizaki, A., De, A., and Fleming, G. (2012). Microscopic quantum
coherence in a photosynthetic-light-harveting antenna. Philos. Trans. R. Soc. A
370, 3672–3691. doi: 10.1098/rsta.2011.0207
De Houwer, J., Hendrickx, H., and Baeyens, F. (1997). Evaluative learning
with “subliminally” presented stimuli. Conscious. Cogn. 61, 87–107. doi:
10.1006/ccog.1996.0281
Dijksterhuis, A., Bos, M. W., Nordgren, L. F., and van Baaren, R. B. (2006). On
making the right choice: the deliberation-without-attention effect. Science 311,
1005–1007. doi: 10.1126/science.1121629
Dixon, P. B., Starling, D. J., Jordan, A. N., and Howell, J. C. (2009). Ultrasensitive
beam deflection measurement via interferometric weak value amplification. Phys.
Rev. Lett. 102, 173601. doi: 10.1103/PhysRevLett.102.173601
Don, N., Donough, B., and Warren, C. (1998). Event-related potentials (ERP)
indicators of unconscious PSI: a replication using subjects unselected for PSI.
J. Parapsychol. 62, 127–145.
Dragoi, G., and Tonegawa, S. (2011). Preplay of future place cell sequences by
hippocampal cellular assemblies. Nature 469, 397–401. doi: 10.1038/nature09633
Ergenoglu, T., Demiralp, T., Bayraktaroglu, Z., Ergen, M., Beydagi, H., and Uresin,
Y. (2004). Alpha rhythm of the EEG modulates visual detection performance in
humans. Cogn. Brain Res. 20, 8. doi: 10.1016/j.cogbrainres.2004.03.009
Haggard, P., and Eimer, M. (1999). On the relation between brain potentials and
the awareness of voluntary movements. Exp. Brain Res. 126, 128–133. doi:
10.1007/s002210050722
Hartwell, J. (1978). Contingent negative variation as an index of precognitive
information. Eur. J. Parapsychol. 2, 83–103.
Hassin, R. (2013). Yes it can: on the functional abilities of the human unconscious.
Perspect. Psychol. Sci. 8, 195–207. doi: 10.1177/1745691612460684
Hosten, O.,and Kwiat, P. (2008). O bservation of the spin hall effect of light via weak
measurements. Science 319, 787–790. doi: 10.1126/science.1152697
Kahneman, D.(2011). Thinking, Fast and Slow. New York: Farrar, Straus and Giroux.
Libet, B., Wright, E. W. Jr., and Gleason, C. A. (1983). Preparation- or intention-to-
act, in relation to pre-event potentials recorded at the vertex. Electroencephalogr.
Clin. Neurophysiol. 56, 367–372. doi: 10.1016/0013-4694(83)90262-6
Ma, X., Zotter, S., Kofler, J., Ursin, R., Jennewein, T., Brukner, C., et al. (2012).
Experimental delayed-choice entanglement swapping. Nat. Phys. 8, 479–484. doi:
10.1038/nphys2294
Maier, M. A., Büchner, V. L., Kuhbandner, C., Pflitsch, M., Fernández-Capo,M., and
Gámiz-Sanfeliu, M. (in press). Feeling the future again: retroactive avoidance of
negative stimuli. Available at: http://ssrn.com/abstract=2388097
Mathewson, K. E., Gratton, G., Fabiani, M., Beck, D. M., and Ro, T. (2009). To see
or not to see: prestimulus alpha phase predicts visual awareness. J. Neurosci. 29,
8. doi: 10.1523/JNEUROSCI.3963-08.2009
May, E. C., Paulinyi, T., and Vassy, Z. (2005). Anomalous anticipatory skin conduc-
tance response to acoustic stimuli: experimental results and speculation about a
mechanism. J. Altern. Complement. Med. 11, 8. doi: 10.1089/acm.2005.11.695
McCraty,R., Atkinson, M., and Bradley, R. T. (2004a). Electrophysiological evidence
of intuition: Part 1. The surprising role of the heart. J. Altern. Complement. Med.
10, 11.
McCraty,R., Atkinson, M., and Bradley, R. T.(2004b). Electrophysiological evidence
of intuition: Part 2. A system-wide process? J. Altern. Complement. Med. 10, 12.
McDonough, B., Don, N., and Watson, C. (2002). Differential event-related
potentials to targets and decoys in a guessing task. J. Sci. Explor. 16, 187–206.
Meredith, M.A., Nemitz, J. W.,and Stein, B. E. (1987). Determinants of multisensory
integration in superior colliculus neurons. I. Temporal factors. J. Neurosci. 7,
3215–3229.
Meredith, M. A., and Stein, B. E. (1986). Visual, auditory, and somatosensory
convergence on cells in superior colliculus results in multisensory integration.
J. Neurophysiol. 56, 640–662.
Meyer, D. E., and Schvaneveldt, R. W. (1971). Facilitation in recognizing pairs of
words: evidence of a dependence between retrieval operations. J. Exp. Psychol. 90,
227–234. doi: 10.1037/h0031564
Mossbridge, J., Grabowecky, M., and Suzuki, S. (2011). Physiological markers of
future outcomes: three experiments on subconscious psi perception during con-
current performance of a guessing task. Paper Presented at the 54th Conference of
the Parapsychology Association, Paris.
Mossbridge, J., Tressoldi, P.,and Utts, J. (2012). Predictive physiological anticipation
preceding seemingly unpredictable stimuli: a meta-analysis. Front. Psychol. 3:390.
doi: 10.3389/fpsyg.2012.00390
Olaya-Castro, A., Nazir, A., and Fleming, G. (2012). Quantum-coherent energy
transfer: implications for biology and new energy technologies. Philos. Trans. R.
Soc. A 370, 3613–3617. doi: 10.1098/rsta.2012.0192
Panzeri, S., Brunel, N., Logothetis, N. K., and Kayser, C. (2010). Sensory neu-
ral codes using multiplexed temporal scales. Trends Neurosci. 33, 10. doi:
10.1016/j.tins.2009.12.001
Frontiers in Human Neuroscience www.frontiersin.org March 2014 |Volume 8 |Article 146 |9
Mossbridge et al. Predicting the unpredictable
Radin, D. (1997). Unconscious perception of future emotions: an experiment in
presentiment. J. Sci. Explor. 11, 163–180.
Radin, D. (2004). Electrodermal presentiments of future emotions. J. Sci. Explor. 18,
253–273.
Radin, D., and Borges, A. (2009). Intuition through time: what does the seer see?
Explore (NY), 5, 200–211. doi: 10.1016/j.explore.2009.04.002
Radin, D.,and Lobach, E. (2007). Toward understanding the placebo effect: investi-
gating a possible retrocausal factor. J. Altern. Complement. Med. 13, 733–739. doi:
10.1089/acm.2006.6243
Radin, D., Taylor, R., and Braud, W. (1995). Remote mental influence of
electrodermal activity: a pilot replication. Eur. J. Parapsychol. 11, 19–34.
Radin, D., Vieten, C., Michel, L., and Delorme, A. (2011). Electrocortical activity
prior to unpredictable stimuli in meditators and nonmeditators. Explore 7, 286–
299. doi: 10.1016/j.explore.2011.06.004
Ritchie, S., Wiseman,R., and French, C. (2012). Failing the future: three unsuccessful
attempts to replicate Bem’s “Retroactive facilitation of recall” effect. PLoS ONE
7:e33423. doi: 10.1371/journal.pone.0033423
Sartori, L., Massaccessi, S., Martinell, M., and Tressoldi, P. (2004). Physiologi-
cal correlates of ESP: heart rate differences between targets and nontargets. J.
Parapsychol. 68, 351–360.
Scholes, G. (2011). Coherence in photosynthesis. Nat. Phys. 7, 448–449. doi:
10.1038/nphys2013
Simmons, J. P., Nelson, L. D., and Simonsohn, U. (2011). False-positive psychology:
undisclosed flexibility in data collection and analysis allows presenting anything
as significant. Psychol. Sci. 22, 1359–1366. doi: 10.1177/0956797611417632
Soon, C. S., Brass, M., Heinze, H. J., and Haynes, J. D. (2008). Unconscious deter-
minants of free decisions in the human brain. Nat. Neurosci. 11, 543–545. doi:
10.1038/nn.2112
Spottiswoode, S., and May, E. (2003). Skin conductance prestimulus response:
analyses, artifacts and a pilot study. J. Sci. Explor. 17, 617–641.
Strick, M., Dijksterhuis, A., Bos, M., Sjoerdsma, A., and van Baaren, R. B. (2011).
A meta-analysis on unconscious thought effects. Soc. Cogn. 29, 738–762. doi:
10.1521/soco.2011.29.6.738
Tressoldi, P. (2011). Ext raordinary claims require extraordinary evidence: the case of
non-local perception, a classifcal and Bayesian review of evidences. Front. Psychol.
2:117. doi: 10.3389/fpsyg.2011.00117
Tressoldi, P. E., Martinelli, M., and Semenzato, L. (2013). Does pupil dilation predict
real or future probable events? Available at: http://ssrn.com/abstract=2371577
Tressoldi, P., Marinelli, M., Massaccessi, S., and Sartori, L. (2005). Heart rate dif-
ferences between targets and non-targets in intuitivate tasks. Hum. Physiol. 31,
6446–6650. doi: 10.1007/s10747-005-0108-y
Tressoldi, P., Martinelli, M., Semenzato, L., and Cappato, S. (2011). Let
your eyes predict: prediction accuracy of pupillary responses to random
alerting and neutral sounds. Sage Open 1, 1–7. doi: 10.1177/2158244011
420451
Tressoldi, P., Martinelli, M., Zaccaria, E., and Massaccessi, S. (2009). Implicit
intuition: how heart rate can contribute to predict future events. J. Soc. Psych.
Res. 73.
Voss, J., Lucas, H., and Paller, K. (2012). More than a feeling: pervasive influences
of memory without awareness of retrieval. Cogn. Neurosci. 3, 193–207. doi:
10.1080/17588928.2012.674935
Wackermann, J. (2002). On cumulative effects and averaging artefacts in randomised
S-R experimental designs. Paper Presented at the 45th Annual Convention of the
Parapsychological Association, Paris, 293–305.
Conflict of Interest Statement: The authors declare that the research was conducted
in the absence of any commercial or financial relationships that could be construed
as a potential conflict of interest.
Received: 16 January 2014; accepted: 27 February 2014; published online: 25 March
2014.
Citation: Mossbridge JA, Tressoldi P, Utts J, Ives JA, Radin D and Jonas WB (2014)
Predicting the unpredictable: critical analysis and practical implications of predictive
anticipatory activity. Front. Hum. Neurosci. 8:146. doi: 10.3389/fnhum.2014.00146
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