Electrocortical activity prior to unpredictable stimuli in meditators and nonmeditators

Brain signatures of catastrophic events: Emotion, salience, and cognitive control

Anticipatory brain activity makes it possible to predict the occurrence of expected situations. However, events such as traffic accidents are statistically unpredictable and can generate catastrophic consequences. This study investigates the brain activity and effective connectivity associated with anticipating and processing such unexpected, unavoidable accidents. We asked 161 participants to ride a motorcycle simulator while recording their electroencephalographic activity. Of these, 90 participants experienced at least one accident while driving. We conducted both within-subjects and between-subjects comparisons. During the pre-accident period, the right inferior parietal lobe (IPL), left anterior cingulate cortex (ACC), and right insula showed higher activity in the accident condition. In the post-accident period, the bilateral orbitofrontal cortex, right IPL, bilateral ACC, and middle and superior frontal gyrus also showed increased activity in the accident condition. We observed greater effective connectivity within the nodes of the limbic network (LN) and between the nodes of the attentional networks in the pre-accident period. In the post-accident period, we also observed greater effective connectivity between networks, from the ventral attention network (VAN) to the somatomotor network and from nodes in the visual network, VAN, and default mode network to nodes in the frontoparietal network, LN, and attentional networks. This suggests that activating salience-related processes and emotional processing allows the anticipation of accidents. Once an accident has occurred, integration and valuation of the new information takes place, and control processes are initiated to adapt behavior to the new demands of the environment.

'Feeling' or 'sensing' the future? Testing for anomalous cognitions in clinical versus healthy populations

In the study and treatment of psychosis, emotional intelligence (EI) and thinking styles are important patient characteristics for successful outcomes in clinical intervention. Anticipation of unpredictable stimuli (AUS) may be understood as an anomalous perception and anomalous cognition in which an individual supposedly senses and recognizes future stimuli in an unexpected way, also referred to as “hunches or premonitions.” This examined the roles of EI and thinking styles in AUSs in convenience samples of healthy participants (n = 237) versus patients diagnosed with psychosis (n = 118). We adjusted several quadratic and exponential regression models according to the obtained functions. Group means were also compared to examine differences in EI scores for participants with psychosis compared to healthy participants. In the healthy group, EI predicted AUSs with a weight between 42% and 58%. Thinking styles were not correlated with AUSs. However, EI was not correlated with AUSs in the clinical group. Patients with psychosis tended to score higher on AUSs and lower on EI and thinking styles compared to participants in the healthy group. We discuss EI as a variable that can contextualize some anomalous perceptions which are otherwise difficult to classify or measure within the classic psychosis continuum model.

What if consciousness is not an emergent property of the brain? Observational and empirical challenges to materialistic models

The nature of consciousness is considered one of science's most perplexing and persistent mysteries. We all know the subjective experience of consciousness, but where does it arise? What is its purpose? What are its full capacities? The assumption within today's neuroscience is that all aspects of consciousness arise solely from interactions among neurons in the brain. However, the origin and mechanisms of qualia (i.e., subjective or phenomenological experience) are not understood. David Chalmers coined the term "the hard problem" to describe the difficulties in elucidating the origins of subjectivity from the point of view of reductive materialism. We propose that the hard problem arises because one or more assumptions within a materialistic worldview are either wrong or incomplete. If consciousness entails more than the activity of neurons, then we can contemplate new ways of thinking about the hard problem. This review examines phenomena that apparently contradict the notion that consciousness is exclusively dependent on brain activity, including phenomena where consciousness appears to extend beyond the physical brain and body in both space and time. The mechanisms underlying these "non-local" properties are vaguely suggestive of quantum entanglement in physics, but how such effects might manifest remains highly speculative. The existence of these non-local effects appears to support the proposal that post-materialistic models of consciousness may be required to break the conceptual impasse presented by the hard problem of consciousness.

Exploring Personal Development Workshops' Effect on Well-Being and Interconnectedness

Introduction: Personal development workshops are increasingly popular. This study evaluated the relationships between the measures of well-being, interconnectedness, and extended perception in various workshops and explored which kinds of workshops and individual characteristics predicted changes in these outcomes. Materials and Methods: In a prospective, uncontrolled, within-participant design study, adult participants completed questionnaires and online tasks before and after personal development workshops. Three analyses were conducted: (1) examining the relationships between measures by using only pre-workshop measures using Spearman correlations; (2) exploring change scores pre- to post-workshop and workshop using Wilcoxon signed-rank test; (3) assessing workshop format and content, and individual characteristics as predictors of those change scores multivariate nonparametric regression. The following outcomes were collected: Well-being-Arizona Integrative Outcomes Scale, positive and negative affect, Dispositional Positive Emotions Scale-Compassion subscale, Sleep Quality Scale, Numeric Pain Rating Scale; Interconnectedness-Cloninger Self-Transcendence Scale, Inclusion of Nature in Self and Inclusion of the Other in Self; and Extended perception tasks-Intuition Jar, Quick Remote Viewing, Psychokinesis Bubble, and Time Estimation. The following potential predictor variables were collected: demographic, mental health, psychiatric and meditation history, Single General Self-Rated Health Question, Brief Five-Factor Inventory-10, and the Noetic Experience and Belief Scale. Workshop leaders also selected which format and content characteristics applied to their workshop. Results: Interconnectedness measures were significantly and positively correlated with well-being (ρ: 0.27 to 0.33), positive affect (ρ: 0.20 to 0.27), and compassion (ρ: 0.21 to 0.32), and they were negatively correlated with sleep disturbance (ρ: -0.13 to -0.16) and pain (ρ: -0.11 to -0.16). Extended perception task performance was not correlated with interconnectedness or well-being. General personal development workshops improved subjective interconnectedness, well-being, positive emotion, and compassion, and they reduced sleep disturbances, negative emotion, and pain (all p's < 0.00005). The lecture (p = 0.03), small groups (p = 0.001), pairs (p = 0.01), and discussion (p = 0.03) workshop formats were significant predictors of well-being outcomes. The workshop content categories of meditation (p = 0.0002) and technology tools (p = 0.01) were also predictive of well-being outcomes, with meditation being the most consistent predictor of positive well-being changes. Conscientiousness was the only significant individual characteristic predictor (p = 0.002), although it was associated with increases in some well-being measures and decreases in others. Conclusions: This study provides preliminary evidence for the positive relationship between the subjective sense of interconnectedness and multiple well-being measures and the beneficial effects of some personal development workshops.

Applying machine learning EEG signal classification to emotion‑related brain anticipatory activity

Machine learning approaches have been fruitfully applied to several neurophysiological signal classification problems. Considering the relevance of emotion in human cognition and behaviour, an important application of machine learning has been found in the field of emotion identification based on neurophysiological activity. Nonetheless, there is high variability in results in the literature depending on the neuronal activity measurement, the signal features and the classifier type. The present work aims to provide new methodological insight into machine learning applied to emotion identification based on electrophysiological brain activity. For this reason, we analysed previously recorded EEG activity measured while emotional stimuli, high and low arousal (auditory and visual) were provided to a group of healthy participants. Our target signal to classify was the pre-stimulus onset brain activity. Classification performance of three different classifiers (LDA, SVM and kNN) was compared using both spectral and temporal features. Furthermore, we also contrasted the performance of static and dynamic (time evolving) approaches. The best static feature-classifier combination was the SVM with spectral features (51.8%), followed by LDA with spectral features (51.4%) and kNN with temporal features (51%). The best dynamic feature classifier combination was the SVM with temporal features (63.8%), followed by kNN with temporal features (63.70%) and LDA with temporal features (63.68%). The results show a clear increase in classification accuracy with temporal dynamic features.

Reflections on Inner and Outer Silence and Consciousness Without Contents According to the Sphere Model of Consciousness

In the current hypothesis paper, we propose that focusing attention on silence can be used as a paradigm conceptually similar to sensory deprivation, to study consciousness without content. We briefly overview recent influential models of consciousness and consider how they assess the relationship between consciousness and contents. After discussing the strengths and weaknesses of current models, we suggest an extension based on the Sphere Model of Consciousness (SMC) and introduce new definitions for identification and self-awareness as states of consciousness. We further compare Paoletti's theoretical model for the development of self with other influential models, highlighting similarities and differences. We conclude with a discussion of how attentional focus on silence can be empirically tested.

A Critical Analysis on Characterizing the Meditation Experience Through the Electroencephalogram

Meditation practices, originated from ancient traditions, have increasingly received attention due to their potential benefits to mental and physical health. The scientific community invests efforts into scrutinizing and quantifying the effects of these practices, especially on the brain. There are methodological challenges in describing the neural correlates of the subjective experience of meditation. We noticed, however, that technical considerations on signal processing also don't follow standardized approaches, which may hinder generalizations. Therefore, in this article, we discuss the usage of the electroencephalogram (EEG) as a tool to study meditation experiences in healthy individuals. We describe the main EEG signal processing techniques and how they have been translated to the meditation field until April 2020. Moreover, we examine in detail the limitations/assumptions of these techniques and highlight some good practices, further discussing how technical specifications may impact the interpretation of the outcomes. By shedding light on technical features, this article contributes to more rigorous approaches to evaluate the construct of meditation.

Future directions in meditation research: Recommendations for expanding the field of contemplative science

The science of meditation has grown tremendously in the last two decades. Most studies have focused on evaluating the clinical effectiveness of mindfulness-based interventions, neural and other physiological correlates of meditation, and individual cognitive and emotional aspects of meditation. Far less research has been conducted on more challenging domains to measure, such as group and relational, transpersonal and mystical, and difficult aspects of meditation; anomalous or extraordinary phenomena related to meditation; and post-conventional stages of development associated with meditation. However, these components of meditation may be crucial to people's psychological and spiritual development, could represent important mediators and/or mechanisms by which meditation confers benefits, and could themselves be important outcomes of meditation practices. In addition, since large numbers of novices are being introduced to meditation, it is helpful to investigate experiences they may encounter that are not well understood. Over the last four years, a task force of meditation researchers and teachers met regularly to develop recommendations for expanding the current meditation research field to include these important yet often neglected topics. These meetings led to a cross-sectional online survey to investigate the prevalence of a wide range of experiences in 1120 meditators. Results show that the majority of respondents report having had many of these anomalous and extraordinary experiences. While some of the topics are potentially controversial, they can be subjected to rigorous scientific investigation. These arenas represent largely uncharted scientific terrain and provide excellent opportunities for both new and experienced researchers. We provide suggestions for future directions, with accompanying online materials to encourage such research.

Driving with Intuition: A Preregistered Study about the EEG Anticipation of Simulated Random Car Accidents

The study of neural pre-stimulus or "anticipatory" activity opened a new window for understanding how the brain actively constructs the forthcoming reality. Usually, experimental paradigms designed to study anticipatory activity make use of stimuli. The purpose of the present study is to expand the study of neural anticipatory activity upon the temporal occurrence of dichotomic, statistically unpredictable (random) stimuli within an ecological experimental paradigm. To this purpose, we used a simplified driving simulation including two possible, randomly-presented trial types: a car crash end trial and a no car crash end trial. Event Related Potentials (ERP) were extracted -3,000 ms before stimulus onset. We identified a fronto-central negativity starting around 1,000 ms before car crash presentation. By contrast, a whole-scalp distributed positivity characterized the anticipatory activity observed before the end of the trial in the no car crash end condition. The present data are in line with the hypothesis that the brain may also anticipate dichotomic, statistically unpredictable stimuli, relaying onto different pre-stimulus ERP activity. Possible integration with car-smart-systems is also suggested.

Investigating expectation effects using multiple physiological measures

The study aimed at experimentally investigating whether the human body can anticipate future events under improved methodological conditions. Previous studies have reported contradictory results for the phenomenon typically called presentiment. If the positive findings are accurate, they call into doubt our views about human perception, and if they are inaccurate, a plausible conventional explanation might be based on the experimental design of the previous studies, in which expectation due to item sequences was misinterpreted as presentiment. To address these points, we opted to collect several physiological variables, to test different randomization types and to manipulate subjective significance individually. For the latter, we combined a mock crime scenario, in which participants had to steal specific items, with a concealed information test (CIT), in which the participants had to conceal their knowledge when interrogated about items they had stolen or not stolen. We measured electrodermal activity, respiration, finger pulse, heart rate (HR), and reaction times. The participants (n = 154) were assigned randomly to four different groups. Items presented in the CIT were either drawn with replacement (full) or without replacement (pseudo) and were either presented category-wise (cat) or regardless of categories (nocat). To understand how these item sequences influence expectation and modulate physiological reactions, we compared the groups with respect to effect sizes for stolen vs. not stolen items. Group pseudo_cat yielded the highest effect sizes, and pseudo_nocat yielded the lowest. We could not find any evidence of presentiment but did find evidence of physiological correlates of expectation. Due to the design differing fundamentally from previous studies, these findings do not allow for conclusions on the question whether the expectation bias is being confounded with presentiment.

Predicting the unpredictable: critical analysis and practical implications of predictive anticipatory activity

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 etal., 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.