Presentiment in the brain
Just published:
Toward Understanding the Placebo Effect: Investigating a Possible Retrocausal Factor, Dean Radin and Eva Lobach, Journal of Alternative and Complementary Medicine, Volume 13, Number 7, 2007, pp. 733–739
Objective: Conventional models of placebo effects assume that all mind–body responses associated with expectation can be explained by ordinary causal processes. This experiment tested whether some placebo effects may also involve retrocausal, or time-reversed, influences.
Design: Slow cortical potentials in the brain were monitored while adult volunteers anticipated either a flash of light or no flash, selected with equal probability by a noise-based random number generator. Data were collected in individual sessions of 100 trials, contributed by 13 female and 7 male adult participants.
Outcome measures: Ensemble median slow cortical potentials 1 second prior to a light flash were compared with the same measures prior to no flash. A nonparametric randomized permutation technique was used to statistically assess the observed difference. Electroencephalographic data were analyzed separately by gender.
Results: Females’ slow cortical potentials significantly differentiated before stimulus onset (z = 2.72, p = 0.007, two-tailed); males showed a suggestive effect in the opposite direction (z = 1.64, p = 0.10, two-tailed). Examination of alternative explanations indicated that the significant effect in females was not caused by anticipatory strategies, equipment or environmental artifacts, or violation of statistical assumptions.
Conclusions: This experiment, in accordance with previous studies showing similar, unconscious “presentiment” effects in humans, suggests that comprehensive models seeking to explain placebo effects, and in general how expectation affects the mind and body, may require consideration of retrocausal influences.
To download this article for free, go here.
Toward Understanding the Placebo Effect: Investigating a Possible Retrocausal Factor, Dean Radin and Eva Lobach, Journal of Alternative and Complementary Medicine, Volume 13, Number 7, 2007, pp. 733–739
Objective: Conventional models of placebo effects assume that all mind–body responses associated with expectation can be explained by ordinary causal processes. This experiment tested whether some placebo effects may also involve retrocausal, or time-reversed, influences.
Design: Slow cortical potentials in the brain were monitored while adult volunteers anticipated either a flash of light or no flash, selected with equal probability by a noise-based random number generator. Data were collected in individual sessions of 100 trials, contributed by 13 female and 7 male adult participants.
Outcome measures: Ensemble median slow cortical potentials 1 second prior to a light flash were compared with the same measures prior to no flash. A nonparametric randomized permutation technique was used to statistically assess the observed difference. Electroencephalographic data were analyzed separately by gender.
Results: Females’ slow cortical potentials significantly differentiated before stimulus onset (z = 2.72, p = 0.007, two-tailed); males showed a suggestive effect in the opposite direction (z = 1.64, p = 0.10, two-tailed). Examination of alternative explanations indicated that the significant effect in females was not caused by anticipatory strategies, equipment or environmental artifacts, or violation of statistical assumptions.
Conclusions: This experiment, in accordance with previous studies showing similar, unconscious “presentiment” effects in humans, suggests that comprehensive models seeking to explain placebo effects, and in general how expectation affects the mind and body, may require consideration of retrocausal influences.
To download this article for free, go here.
Comments
Based on your empirical results or from semantics I don't see a preferece for either term except, with the PK explanation, cause comes before effect which is usually how people view the world.
Is it because the model for how PK works is also by choosing a possible future so that PK is the same thing as retrocausation? In which case retrocausation is semantically preferable?
Unless that is proven to be the underlying mechanims of both phenomena isn't PK an equally likely explanation?
I'm interested to know if you submit these kinds of studies to 'mainstream' journals for publication?
Thanks
Dave
Both are published by mainstream academic presses, the former by Mary Ann Liebert, Inc. and the latter by Elsevier. And both journals are indexed in all the usual online bibliographic indices.
Because mainstream is a social construction, one way to assess the "mainstreamedness" of CAM research is by what the science media pays attention to. Apropos, on Friday I was interviewed about the intentional chocolate experiment (mentioned in another post) by a reporter for Earth & Sky, a science program on National Public Radio (www.earthsky.org).
Of course, the difference between surprising events in daily life vs. controlled lab experiments is that for the former we can't be sure if something is chance or not, but for the latter we can precisely calculate the difference between chance and non-chance.
I did like the movie Signs. One person's meaningless coincidence can be perceived by another person as a meaningful synchronicity.
I thought that was kind of more how they were putting it towards the end of the film, but I think by the time the film is over it's pretty clear that psi stuff is supposed to be going on. The wife has some kind of flash before she dies, and gives Mel Gibson just the right mental phrase he needs to know just the right thing to do when he thinks of his wife's death when he's confronted by the alien. Maybe M. Night didn't set out to offer an opinion about psi when he made this movie, but I don't think he was trying to be a relativist or something. I think he was trying to say that stuff in the universe that can maybe take care of us is true, and you should at least be open to that (whether it's the "universe" manifested in psi, or "God," or whatever you want to call it).
Sorry for the off-topic comment, but you don't have an e-mail on the site.
How carefully is latency taken into account in presentiment experiments, generally speaking?
A friend of mine said that even a slightly longer cable from the tone generator to the recorder than the one from the heart rate monitor to the recorder can make it appear as if there is precognition.
He said if a tone is generated (Time A), and the subjects' heart rate is monitored (Time B), they must take into account the time it takes for the source pulse to travel to the recording device. This is an issue in the recording industry and processing times have to be taken into account to ensure proper tracking.
In any case, the physiological signals we record are marked (in time-synched channels) within a millisecond of the stimulus onset, so even when using faster-moving EEG signals potential time lags aren't an issue.
Regarding this paper:
http://www.scientificexploration.org/jse/articles/pdf/18.2_radin.pdf
A friend of mine said:
"there are no presentations of confidence intervals or error bars. Standard physiology practice would be to divide the data into two independent sets and display them superimposed to demonstrate repeatability. The statistical method described is far more complex than the nature of the data calls for (a simple t-test comparing the AUC from 0-3 seconds between the two groups would have sufficed). Taken together, these are all suspicious. Add to this that the data is far cleaner than other published data from dermal galvanic response studies run in reputable labs.
taken together, these points suggest what I will charitably call a lack of credibility. The experiment is simple enough. I would like to see it run under an independent site audit."
How do you respond?
The computational statistic used is actually very simple, but more importantly it avoids parametric assumptions and takes into account autocorrelations inherent in the data. A simple t-test would not be appropriate. In any case, the analytical procedure used comes directly from the psychophysiological literature. I agree that it can be useful to plot error bars (especially for those who only look at the figures).
> the data is far cleaner than other published data from dermal galvanic response studies run in reputable labs.
The curves are ensemble averages over many repeated trials. Given the low-noise nature of the data, the ensemble mean should be very smooth. Indeed, similar curves involving skin conductance level (not "dermal galvanic response") data are commonly observed in the psychophysiological literature.
> The experiment is simple enough. I would like to see it run under an independent site audit.
I don't know what an "independent site audit" is supposed to mean, but the experiment has been independently and successfully replicated in skin conductance, heart rate, EEG, and in my last (not yet published) study, pupil dilation.
I was wondering if you would take a gander at this:
http://forums.randi.org/showthread.php?t=123007
A thread titled: Simulating "Presentiment" Experiments
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"A series of experiments by Dean Radin and others purport to show that the human mind reacted precognitively to stimuli.
The basic design of these experiments is that people are shown, in a random order, a series of photographs - some provoking a strong emotional reaction, some not. Skin conductance is measured both before and after and the results seem to show that dermal activity is higher when the emotional provoking is shown, both before and after the photograph is actually displayed. See Electrodermal Presentiments of Future Emotions for example. In some experiments MRI is used.
I decided to see if these results could be explained by an anticipation effect based on the photographs previously seen. It turns out they can.
The simulation produces 10 seconds worth of data and randomly chooses a state 1 or 0 after the first 5 seconds - representing "emotional" and "calm". The data in the first half of the run is influenced by variables based on past states, the second half is influenced by a function simulating an emotional reaction. A purely random number is also generated to simulate noise.
And yet when data from a series of tests is aggregated, it appears that there is a difference both before and after the random number is actually generated."
[...]
http://picasaweb.google.com.au/robin1658/Presentiments#
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Do you know of a link to a study that shows that an anticipation effect is inapplicable?
Thanks!
The idea is well understood and has been studied in detail.
The bottom line is that analysis of the actual physiological data recorded in these studies does not support the idea that the results can be explained by anticipatory strategies. This is true not only for the data in my studies, but also for the successful replications reported by others.
"I wonder how thoroughly "Robin" read p. 269-271 in your 2004 study before he created this simulation?"
I did, but it was not clear from the bizarre procedure you were following that you were talking about the same thing.
Instead of simply analysing the data in the experiment you perform a new experiment, using a smaller sample and a different protocol.
You say the effect is well understood but you completely leave out any analysis of runs "emotional" trails.
And as I point out, the strategy you use to rule out anticipation effect in your experiment also rules out the anticipation effect in my simulation.
Even though we know it is there.
"I wonder how thoroughly "Robin" read p. 269-271 in your 2004 study before he created this simulation?""
Well enough to demonstrate (in post #23) that the proposed strategy to test for the anticipation effect would be ineffective.
What we tested on actual data recorded in these experiments is whether this plausible-sounding strategy was actually followed. The answer is no, so the presentiment effect is not adequately explained by this strategy.
A randomized permutation technique is a type of computational statistic. Monte Carlo and bootstrap methods are other commonly used methods.
Permutation methods compare an observed measurement to a distribution of similar measurements constructed by randomly permuting one or more key variables associated with the original measurement. It allows you to ask whether the original measurement was really unique, or whether it tends to show up by chance (just like many other statistical tests). It is useful when the actual measurement distribution is unknown, or known but skewed, or otherwise unsuitable for the usual array of parametric statistics.