A macroscopic violation of no-signaling in time inequalities? How to test temporal entanglement with behavioral observables

In this paper we applied for the \ufb01rst time the no-signaling in time (NSIT) formalism discussed by Ko\ufb02er and Brukner (2013) to investigate temporal entanglement between binary human behavioral unconscious choices at t1 with binary random outcomes at t2. NSIT consists of a set of inequalities and represents mathematical conditions for macro-realism which require only two measurements in time. The analyses of three independent experiments show a strong violation of NSIT in two out of three of them, suggesting the hypothesis of a quantum-like temporal entanglement between human choices at t1 with binary random outcomes at t2. We discuss the potentialities of using NSIT to test temporal entanglement with behavioral measures

Predictive physiological anticipatory activity preceding seemingly unpredictable stimuli: An update of Mossbridge et al\u2019s meta-analysis

Background: This is an update of the Mossbridge et al\u2019s meta-analysis related to the physiological anticipation preceding seemingly unpredictable stimuli which overall effect size was 0.21; 95% Confidence Intervals: 0.13 - 0.29 Methods: Nineteen new peer and non-peer reviewed studies completed from January 2008 to June 2018 were retrieved describing a total of 27 experiments and 36 associated effect sizes. Results: The overall weighted effect size, estimated with a frequentist multilevel random model, was: 0.28; 95% Confidence Intervals: 0.18-0.38; the overall weighted effect size, estimated with a multilevel Bayesian model, was: 0.28; 95% Credible Intervals: 0.18-0.38. The weighted mean estimate of the effect size of peer reviewed studies was higher than that of non-peer reviewed studies, but with overlapped confidence intervals: Peer reviewed: 0.36; 95% Confidence Intervals: 0.26-0.47; Non-Peer reviewed: 0.22; 95% Confidence Intervals: 0.05-0.39. Similarly, the weighted mean estimate of the effect size of Preregistered studies was higher than that of Non-Preregistered studies: Preregistered: 0.31; 95% Confidence Intervals: 0.18-0.45; No-Preregistered: 0.24; 95% Confidence Intervals: 0.08-0.41. The statistical estimation of the publication bias by using the Copas selection model suggest that the main findings are not contaminated by publication bias. Conclusions: In summary, with this update, the main findings reported in Mossbridge et al\u2019s meta-analysis, are confirmed

Extraordinary Claims Require Extraordinary Evidence: The Case of Non-Local Perception, a Classical and Bayesian Review of Evidences

Starting from the famous phrase “extraordinary claims require extraordinary evidence,” we will present the evidence supporting the concept that human visual perception may have non-local properties, in other words, that it may operate beyond the space and time constraints of sensory organs, in order to discuss which criteria can be used to define evidence as extraordinary. This evidence has been obtained from seven databases which are related to six different protocols used to test the reality and the functioning of non-local perception, analyzed using both a frequentist and a new Bayesian meta-analysis statistical procedure. According to a frequentist meta-analysis, the null hypothesis can be rejected for all six protocols even if the effect sizes range from 0.007 to 0.28. According to Bayesian meta-analysis, the Bayes factors provides strong evidence to support the alternative hypothesis (H1) over the null hypothesis (H0), but only for three out of the six protocols. We will discuss whether quantitative psychology can contribute to defining the criteria for the acceptance of new scientific ideas in order to avoid the inconclusive controversies between supporters and opponents

On the primacy and irreducible nature of first-person versus third-person information

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Feeling the future: A meta-analysis of 90 experiments on the anomalous anticipation of random future events

In 2011, one of the authors (DJB) published a report of nine experiments in the Journal of Personality and Social Psychology purporting to demonstrate that an individual\u2019s cognitive and affective responses can be influenced by randomly selected stimulus events that do not occur until after his or her responses have already been made and recorded, a generalized variant of the phenomenon traditionally denoted by the term precognition. To encourage replications, all materials needed to conduct them were made available on request. We here report a meta-analysis of 90 experiments from 33 laboratories in 14 countries which yielded an overall effect greater than 6 sigma, z = 6.40, p = 1.2 7 10 with an effect size (Hedges\u2019 g) of 0.09. A Bayesian analysis yielded a Bayes Factor of 5.1 7 10 , greatly exceeding the criterion value of 100 for \u201cdecisive evidence\u201d in support of the experimental hypothesis. When DJB\u2019s original experiments are excluded, the combined effect size for replications by independent investigators is 0.06, z = 4.16, p = 1.1 7 10 , and the BF value is 3,853, again exceeding the criterion for \u201cdecisive evidence.\u201d The number of potentially unretrieved experiments required to reduce the overall effect size of the complete database to a trivial value of 0.01 is 544, and seven of eight additional statistical tests support the conclusion that the database is not significantly compromised by either selection bias or by intense \u201cp -hacking\u201d\u2014the selective suppression of findings or analyses that failed to yield statistical significance. P-curve analysis, a recently introduced statistical technique, estimates the true effect size of the experiments to be 0.20 for the complete database and 0.24 for the independent replications, virtually identical to the effect size of DJB\u2019s original experiments (0.22) and the closely related \u201cpresentiment\u201d experiments (0.21). We discuss the controversial status of precognition and other anomalous effects collectively known as psi

The Physics of Mind-Matter Interaction at a Distance

The aim of this work is identification and localisation of the interaction between mind and matter, specifically with respect to random number generators, and identification of the type of energy that can alter the degree of randomness of bit-string outputs of these electronic devices. Regarding localisation of the mind/random-number- generator interaction, we believe it occurs through the production of electron+gap pairs in the inversely polarised P-N junction of the Zener diode that is used as a white noise generator, with resulting peaks of non-random current. Conversely, regarding the type of energy acting on the analogue signal, we believe it is made of photons of wavelength ranging from 0.2 to 1.1 \u3bcm, each therefore carrying an energy of between 6.2 and 1.14 eV. The most controversial part concerns the means by which the human mind can produce this type of energy from a distance to act directly on a chosen target, in that it is not possible for it to have been emitted by either the body or brain as biophotons

Does System 1 Process both Local and Nonlocal Information in Intuitive Judgment and Decision Making? Available Evidence and a Research Agenda Proposal

This paper argues that System 1, (the mental processing system mainly involved in the processing of unconscious information) in contrast to System 2, (mainly involved in the processing of conscious information), processes not only local information conveyed by sensory organs, but also nonlocal ones, that is, those beyond the detection range of sensory organs. The striking similarities observed between the characteristics of local and nonlocal information processing by System 1, offer the possibility of using most of the experimental protocols used to investigate local information for the nonlocal information. Available evidence is presented and a research agenda is outlined that could raise fascinating questions and answer about the functioning of the human mind

Stage 1 Registered Report: Anomalous perception in a Ganzfeld condition - A meta-analysis of more than 40 years investigation

This meta-analysis is an investigation into anomalous perception (i.e., conscious identification of information without any conventional sensorial means). The technique used for eliciting an effect is the ganzfeld condition (a form of sensory homogenization that eliminates distracting peripheral noise). The database consists of peer-reviewed studies published between January 1974 and June 2020 inclusive. The overall effect size will be estimated using a frequentist model and a Bayesian random model. Moderator analysis will be used to examine the influence of level of experience of participants and the type of task. Publication bias will be estimated by using three different tests. Trend analysis will be conducted on the cumulative database

A new method to detect event-related potentials based on Pearson\u2019s correlation

Event-related potentials (ERPs) are widely used in brain-computer interface applications and in neuroscience. Normal EEG activity is rich in background noise, and therefore, in order to detect ERPs, it is usually necessary to take the average from multiple trials to reduce the effects of this noise. The noise produced by EEG activity itself is not correlated with the ERP waveform and so, by calculating the average, the noise is decreased by a factor inversely proportional to the square root of N, where N is the number of averaged epochs. This is the easiest strategy currently used to detect ERPs, which is based on calculating the average of all ERP\u2019s waveform, these waveforms being time- and phase-locked. In this paper, a new method called GW6 is proposed, which calculates the ERP using a mathematical method based only on Pearson\u2019s correlation. The result is a graph with the same time resolution as the classical ERP and which shows only positive peaks representing the increase\u2014in consonance with the stimuli\u2014in EEG signal correlation over all channels. This new method is also useful for selectively identifying and highlighting some hidden components of the ERP response that are not phase-locked, and that are usually hidden in the standard and simple method based on the averaging of all the epochs. These hidden components seem to be caused by variations (between each successive stimulus) of the ERP\u2019s inherent phase latency period (jitter), although the same stimulus across all EEG channels produces a reasonably constant phase. For this reason, this new method could be very helpful to investigate these hidden components of the ERP response and to develop applications for scientific and medical purposes. Moreover, this new method is more resistant to EEG artifacts than the standard calculations of the average and could be very useful in research and neurology. The method we are proposing can be directly used in the form of a process written in the well-known Matlab programming language and can be easily and quickly written in any other software language