Electrophysiological evidence of the differential modulation of approach-related processes toward attractive foods by immersive or mindful viewing conditions.

Awareness of mental events as mere representations rather than as accurate depictions of reality, also known as dereification, is one of the key features of mindfulness meditation. Dereification is juxtaposed to subjective realism, the process of being lost or totally immersed in the contents of one's mind. Excessive subjective realism is a hallmark of several psychiatric disorders. Here, we investigated whether a "mindful" (dereified) compared with an "immersed" (highly subjectively real) attitude, induced by instructions, differentially modulates approach-avoidance tendencies when processing visual stimuli. We presented novices and experienced meditators with neutral and attractive food images under both mindful and immersed states. Then, participants performed an approach-avoidance Task (AAT) during which we obtained behavioral data, salivary volume, EEG recordings, and self-report measures. The approach bias toward attractive food was correlated with N2 amplitude, a marker of response inhibition, and the regulation of this bias by the mindful instruction compared to the immersed instruction was associated with a modulation of the visual N1 amplitude, a marker of early selective attention. Individuals with more expertise in mindfulness meditation engaged in less late affective reappraisal during mindfulness than during immersion, as measured by lower amplitude in the late positive potential (LPP). Additionally, the ERPs sensitive to the AAT manipulation was also associated to self-report measures of subjective realism, food bias, and mindfulness meditation expertise but not to salivation measures. These findings provide novel insights into the mechanisms by which mindfulness-based interventions could be effective in a range of psychiatric conditions.

The impact of MEG source reconstruction method on source-space connectivity estimation: A comparison between minimum-norm solution and beamforming.

Despite numerous important contributions, the investigation of brain connectivity with magnetoencephalography (MEG) still faces multiple challenges. One critical aspect of source-level connectivity, largely overlooked in the literature, is the putative effect of the choice of the inverse method on the subsequent cortico-cortical coupling analysis. We set out to investigate the impact of three inverse methods on source coherence detection using simulated MEG data. To this end, thousands of randomly located pairs of sources were created. Several parameters were manipulated, including inter- and intra-source correlation strength, source size and spatial configuration. The simulated pairs of sources were then used to generate sensor-level MEG measurements at varying signal-to-noise ratios (SNR). Next, the source level power and coherence maps were calculated using three methods (a) L2-Minimum-Norm Estimate (MNE), (b) Linearly Constrained Minimum Variance (LCMV) beamforming, and (c) Dynamic Imaging of Coherent Sources (DICS) beamforming. The performances of the methods were evaluated using Receiver Operating Characteristic (ROC) curves. The results indicate that beamformers perform better than MNE for coherence reconstructions if the interacting cortical sources consist of point-like sources. On the other hand, MNE provides better connectivity estimation than beamformers, if the interacting sources are simulated as extended cortical patches, where each patch consists of dipoles with identical time series (high intra-patch coherence). However, the performance of the beamformers for interacting patches improves substantially if each patch of active cortex is simulated with only partly coherent time series (partial intra-patch coherence). These results demonstrate that the choice of the inverse method impacts the results of MEG source-space coherence analysis, and that the optimal choice of the inverse solution depends on the spatial and synchronization profile of the interacting cortical sources. The insights revealed here can guide method selection and help improve data interpretation regarding MEG connectivity estimation.

Oscillatory brain activity correlates with risk perception and predicts social decisions.

In social interactions, the perception of how risky our decisions are depends on how we anticipate other people's behaviors. We used electroencephalography to study the neurobiology of perception of social risk, in subjects playing the role of proposers in an iterated ultimatum game in pairs. Based on statistical modeling, we used the previous behaviors of both players to separate high-risk [HR] offers from low-risk [LR] offers. The HR offers present higher rejection probability and higher entropy (variability of possible outcome) than the LR offers. Rejections of LR offers elicited both a stronger mediofrontal negativity and a higher prefrontal theta activity than rejections of HR offers. Moreover, prior to feedback, HR offers generated a drop in alpha activity in an extended network. Interestingly, trial-by-trial variation in alpha activity in the medial prefrontal, posterior temporal, and inferior pariental cortex was specifically modulated by risk and, together with theta activity in the prefrontal and posterior cingulate cortex, predicted the proposer's subsequent behavior. Our results provide evidence that alpha and theta oscillations are sensitive to social risk and underlie a fine-tuning regulation of social decisions.

Psychobiotic Effects on Anxiety Are Modulated by Lifestyle Behaviors: A Randomized Placebo-Controlled Trial on Healthy Adults.

Psychobiotics are modulators of the Microbiota-Gut-Brain Axis (MGBA) with promising benefits to mental health. Lifestyle behaviors are established modulators of both mental health and the MGBA. This randomized placebo-controlled clinical trial (NCT04823533) on healthy adults (N = 135) tested 4 weeks of probiotic supplementation (Lactobacillus helveticus R0052 and Bifidobacterium longum R0175). We assessed effects on wellbeing, quality of life, emotional regulation, anxiety, mindfulness and interoceptive awareness. We then analyzed if lifestyle behaviors modulated probiotic effectiveness. Results showed no significant effects of probiotic intake in whole sample outcomes. Correlational analyses revealed Healthy Behaviors were significantly correlated with wellbeing across scales. Moreover, the linear mixed-effects model showed that the interaction between high scores in Healthy Behaviors and probiotic intake was the single significant predictor of positive effects on anxiety, emotional regulation, and mindfulness in post-treatment outcomes. These findings highlight the relevance of controlling for lifestyle behaviors in psychobiotic and mental health research.

Attentional and meta-cognitive processes underlying mind wandering episodes during continuous naturalistic reading are associated with specific changes in eye behavior.

Although eye movements during reading have been studied extensively, their variation due to attentional fluctuations such as spontaneous distractions is not well understood. Here we used a naturalistic reading task combined with an attentional sampling method to examine the effects of mind wandering-and the subsequent metacognitive awareness of its occurrence-on eye movements and pupillary dynamics. Our goal was to better understand the attentional and metacognitive processes involved in the initiation and termination of mind wandering episodes. Our results show that changes in eye behavior are consistent with underlying independent cognitive mechanisms working in tandem to sustain the attentional resources required for focused reading. In addition to changes in blink frequency, blink duration, and the number of saccades, variations in eye movements during unaware distractions point to a loss of the perceptual asymmetry that is usually observed in attentive, left-to-right reading. Also, before self-detected distractions, we observed a specific increase in pupillary diameter, indicating the likely presence of an anticipatory autonomic process that could contribute to becoming aware of the current attentional state. These findings stress the need for further research tackling the temporal structure of attentional dynamics during tasks that have a significant real-world impact.

Emotional Influences on Cognitive Flexibility Depend on Individual Differences: A Combined Micro-Phenomenological and Psychophysiological Study.

Imagine a scenario where you are cooking and suddenly, the contents of the pot start to come out, and the oven bell rings. You would have to stop what you are doing and start responding to the changing demands, switching between different objects, operations and mental sets. This ability is known as cognitive flexibility. Now, add to this scenario a strong emotional atmosphere that invades you as you spontaneously recall a difficult situation you had that morning. How would you behave? Recent studies suggest that emotional states do modulate cognitive flexibility, but these findings are still controversial. Moreover, there is a lack of evidence regarding the underlying brain processes. The purpose of the present study was, therefore, to examine such interaction while monitoring changes in ongoing cortical activity using EEG. In order to answer this question, we used two musical stimuli to induce emotional states (positive/high arousal/open stance and negative/high arousal/closed stance). Twenty-nine participants performed two blocks of the Madrid Card Sorting Task in a neutral silence condition and then four blocks while listening to the counterbalanced musical stimuli. To explore this interaction, we used a combination of first-person (micro-phenomenological interview) and third-person (behavior and EEG) approaches. Our results show that compared to the positive stimuli and silence condition, negative stimuli decrease reaction times (RTs) for the shift signal. Our data show that the valance of the first emotional block is determinant in the RTs of the subsequent blocks. Additionally, the analysis of the micro-phenomenological interview and the integration of first- and third-person data show that the emotional disposition generated by the music could facilitate task performance for some participants or hamper it for others, independently of its emotional valence. When the emotional disposition hampered task execution, RTs were slower, and the P300 potential showed a reduced amplitude compared to the facilitated condition. These findings show that the interaction between emotion and cognitive flexibility is more complex than previously thought and points to a new way of understanding the underlying mechanisms by incorporating an in-depth analysis of individual subjective experience.

Enhanced response inhibition and reduced midfrontal theta activity in experienced Vipassana meditators.

Response inhibition - the ability to suppress inappropriate thoughts and actions - is a fundamental aspect of cognitive control. Recent research suggests that mental training by meditation may improve cognitive control. Yet, it is still unclear if and how, at the neural level, long-term meditation practice may affect (emotional) response inhibition. The present study aimed to address this outstanding question, and used an emotional Go/Nogo task and electroencephalography (EEG) to examine possible differences in behavioral and electrophysiological indices of response inhibition between Vipassana meditators and an experience-matched active control group (athletes). Behaviorally, meditators made significantly less errors than controls on the emotional Go/Nogo task, independent of the emotional context, while being equally fast. This improvement in response inhibition at the behavioral level was accompanied by a decrease in midfrontal theta activity in Nogo vs. Go trials in the meditators compared to controls. Yet, no changes in ERP indices of response inhibition, as indexed by the amplitude of the N2 and P3 components, were observed. Finally, the meditators subjectively evaluated the emotional pictures lower in valence and arousal. Collectively, these results suggest that meditation may improve response inhibition and control over emotional reactivity.

Neural Correlates of Conscious Motion Perception.

The nature of the proper neural signature of conscious perception remains a topic of active debate. Theoretical support from integrative theories of consciousness is consistent with such signature being P3b, one of the main candidates in the literature. Recent work has also put forward a mid-latency and more localized component, the Visual Awareness Negativity (VAN), as a proper Neural Correlate of Consciousness (NCC). Early local components like P1 have also been proposed. However, experiments exploring visual NCCs are conducted almost exclusively using static images as the content to be consciously perceived, favoring ventral stream processing, therefore limiting the scope of the NCCs that have been identified. Here we explored the visual NCCs isolating local motion, a dorsally processed feature, as the primary feature being consciously perceived. Physical equality between Seen and Unseen conditions in addition to a minimal contrast difference between target and no-target displays was employed. In agreement with previous literature, we found a P3b with a wide centro-parietal distribution that strongly correlated with the detection of the stimuli. P3b magnitude was larger for Seen vs. Unseen conditions, a result that was consistently observed at the single subject level. In contrast, we were unable to detect VAN in our data, regardless of whether the subject perceived or not the stimuli. In the 200-300 ms time window we found a N2pc component, consistent with the high attentional demands of our task. Early components like P1 were not observed in our data, in agreement with their proposed role in the processing of visual features, but not as proper NCCs. Our results extend the role of P3b as a content independent NCC to conscious visual motion perception.

Effects of a brief mindfulness-meditation intervention on neural measures of response inhibition in cigarette smokers.

Research suggests that mindfulness-practices may aid smoking cessation. Yet, the neural mechanisms underlying the effects of mindfulness-practices on smoking are unclear. Response inhibition is a main deficit in addiction, is associated with relapse, and could therefore be a candidate target for mindfulness-based practices. The current study hence investigated the effects of a brief mindfulness-practice on response inhibition in smokers using behavioral and electroencephalography (EEG) measures. Fifty participants (33 females, mean age 20 years old) underwent a protocol of cigarette exposure to induce craving (cue-exposure) and were then randomly assigned to a group receiving mindfulness-instructions or control-instructions (for 15 minutes approximately). Immediately after this, they performed a smoking Go/NoGo task, while their brain activity was recorded. At the behavioral level, no group differences were observed. However, EEG analyses revealed a decrease in P3 amplitude during NoGo vs. Go trials in the mindfulness versus control group. The lower P3 amplitude might indicate less-effortful response inhibition after the mindfulness-practice, and suggest that enhanced response inhibition underlies observed positive effects of mindfulness on smoking behavior.

Compared to self-immersion, mindful attention reduces salivation and automatic food bias.

Immersing ourselves in food images can sometimes make it feel subjectively real, as if the actual food were right in front of us. Excessive self-immersion into mental content, however, is a hallmark of psychological distress, and of several psychiatric conditions. Being aware that imagined events are not necessarily an accurate depiction of reality is a key feature of psychotherapeutic approaches akin to mindfulness-based interventions. Yet, it is still largely unknown to what extent one's engagement with mental content, considering it as real, biases one's automatic tendencies toward the world. In this study, we measured the change in subjective realism induced by a self-immersion and a mindful attention instruction, using self-reports and saliva volumes. Then, we measured behaviorally the impact of subjective realism changes on automatic approach bias toward attractive food (FAB) using an approach-avoidance task. We found a reduction in saliva volume, followed by a reduction in FAB in the mindful condition compared to the immersed condition. During the immersed condition only, saliva volumes, state and trait measures of subjective realism, and food craving traits were positively correlated with FAB values, whereas meditation experience was negatively correlated to it. We conclude that mindful attention instructions can de-automatize food bias.

Modeling Search Behaviors during the Acquisition of Expertise in a Sequential Decision-Making Task.

Our daily interaction with the world is plagued of situations in which we develop expertise through self-motivated repetition of the same task. In many of these interactions, and especially when dealing with computer and machine interfaces, we must deal with sequences of decisions and actions. For instance, when drawing cash from an ATM machine, choices are presented in a step-by-step fashion and a specific sequence of choices must be performed in order to produce the expected outcome. But, as we become experts in the use of such interfaces, is it possible to identify specific search and learning strategies? And if so, can we use this information to predict future actions? In addition to better understanding the cognitive processes underlying sequential decision making, this could allow building adaptive interfaces that can facilitate interaction at different moments of the learning curve. Here we tackle the question of modeling sequential decision-making behavior in a simple human-computer interface that instantiates a 4-level binary decision tree (BDT) task. We record behavioral data from voluntary participants while they attempt to solve the task. Using a Hidden Markov Model-based approach that capitalizes on the hierarchical structure of behavior, we then model their performance during the interaction. Our results show that partitioning the problem space into a small set of hierarchically related stereotyped strategies can potentially capture a host of individual decision making policies. This allows us to follow how participants learn and develop expertise in the use of the interface. Moreover, using a Mixture of Experts based on these stereotyped strategies, the model is able to predict the behavior of participants that master the task.

Attending to the heart is associated with posterior alpha band increase and a reduction in sensitivity to concurrent visual stimuli.

Attentional mechanisms have been studied mostly in specific sensory domains, such as auditory, visuospatial, or tactile modalities. In contrast, attention to internal interoceptive visceral targets has only recently begun to be studied, despite its potential importance in emotion, empathy, and self-awareness. Here, we studied the effects of shifting attention to the heart using a cue-target detection paradigm during continuous EEG recordings. Subjects were instructed to count either a series of visual stimuli (visual condition) or their own heartbeats (heart condition). Visual checkerboard stimuli were used as attentional probes throughout the task. Consistent with previous findings, attention modulated the amplitude of the heartbeat-evoked potentials. Directing attention to the heart significantly reduced the visual P1/N1 amplitude evoked by the attentional probe. ERPs locked to the attention-directing cue revealed a novel frontal positivity around 300 ms postcue. Finally, spectral power in the alpha band over parieto-occipital regions was higher while attending to the heart-when compared to the visual task-and correlated with subject's performance in the interoceptive task. These results are consistent with a shared, resource-based attentional mechanism whereby allocating attention to bodily signals can affect early responses to visual stimuli.

Spontaneous Alpha Power Lateralization Predicts Detection Performance in an Un-Cued Signal Detection Task.

Focusing one's attention by external guiding stimuli towards a specific area of the visual field produces systematical neural signatures. One of the most robust is the change in topological distribution of oscillatory alpha band activity across parieto-occipital cortices. In particular, decreases in alpha activity over contralateral and/or increases over ipsilateral scalp sites, respect to the side of the visual field where attention was focused. This evidence comes mainly from experiments where an explicit cue informs subjects where to focus their attention, thus facilitating detection of an upcoming target stimulus. However, recent theoretical models of attention have highlighted a stochastic or non-deterministic component related to visuospatial attentional allocation. In an attempt to evidence this component, here we analyzed alpha activity in a signal detection paradigm in the lack of informative cues; in the absence of preceding information about the location (and time) of appearance of target stimuli. We believe that the unpredictability of this situation could be beneficial for unveiling this component. Interestingly, although total alpha power did not differ between Seen and Unseen conditions, we found a significant lateralization of alpha activity over parieto-occipital electrodes, which predicted behavioral performance. This effect had a smaller magnitude compared to paradigms in which attention is externally guided (cued). However we believe that further characterization of this spontaneous component of attention is of great importance in the study of visuospatial attentional dynamics. These results support the presence of a spontaneous component of visuospatial attentional allocation and they advance pre-stimulus alpha-band lateralization as one of its neural signatures.

MEG Connectivity and Power Detections with Minimum Norm Estimates Require Different Regularization Parameters.

Minimum Norm Estimation (MNE) is an inverse solution method widely used to reconstruct the source time series that underlie magnetoencephalography (MEG) data. MNE addresses the ill-posed nature of MEG source estimation through regularization (e.g., Tikhonov regularization). Selecting the best regularization parameter is a critical step. Generally, once set, it is common practice to keep the same coefficient throughout a study. However, it is yet to be known whether the optimal lambda for spectral power analysis of MEG source data coincides with the optimal regularization for source-level oscillatory coupling analysis. We addressed this question via extensive Monte-Carlo simulations of MEG data, where we generated 21,600 configurations of pairs of coupled sources with varying sizes, signal-to-noise ratio (SNR), and coupling strengths. Then, we searched for the Tikhonov regularization coefficients (lambda) that maximize detection performance for (a) power and (b) coherence. For coherence, the optimal lambda was two orders of magnitude smaller than the best lambda for power. Moreover, we found that the spatial extent of the interacting sources and SNR, but not the extent of coupling, were the main parameters affecting the best choice for lambda. Our findings suggest using less regularization when measuring oscillatory coupling compared to power estimation.

Molecular coupling between voltage sensor and pore opening in the Arabidopsis inward rectifier K+ channel KAT1.

Animal and plant voltage-gated ion channels share a common architecture. They are made up of four subunits and the positive charges on helical S4 segments of the protein in animal K+ channels are the main voltage-sensing elements. The KAT1 channel cloned from Arabidopsis thaliana, despite its structural similarity to animal outward rectifier K+ channels is, however, an inward rectifier. Here we detected KAT1-gating currents due to the existence of an intrinsic voltage sensor in this channel. The measured gating currents evoked in response to hyperpolarizing voltage steps consist of a very fast (tau = 318 +/- 34 micros at -180 mV) and a slower component (4.5 +/- 0.5 ms at -180 mV) representing charge moved when most channels are closed. The observed gating currents precede in time the ionic currents and they are measurable at voltages (less than or equal to -60) at which the channel open probability is negligible ( approximately 10-4). These two observations, together with the fact that there is a delay in the onset of the ionic currents, indicate that gating charge transits between several closed states before the KAT1 channel opens. To gain insight into the molecular mechanisms that give rise to the gating currents and lead to channel opening, we probed external accessibility of S4 domain residues to methanethiosulfonate-ethyltrimethylammonium (MTSET) in both closed and open cysteine-substituted KAT1 channels. The results demonstrate that the putative voltage-sensing charges of S4 move inward when the KAT1 channels open.

The Underlying Social Dynamics of Paradigm Shifts.

We develop here a multi-agent model of the creation of knowledge (scientific progress or technological evolution) within a community of researchers devoted to such endeavors. In the proposed model, agents learn in a physical-technological landscape, and weight is attached to both individual search and social influence. We find that the combination of these two forces together with random experimentation can account for both i) marginal change, that is, periods of normal science or refinements on the performance of a given technology (and in which the community stays in the neighborhood of the current paradigm); and ii) radical change, which takes the form of scientific paradigm shifts (or discontinuities in the structure of performance of a technology) that is observed as a swift migration of the knowledge community towards the new and superior paradigm. The efficiency of the search process is heavily dependent on the weight that agents posit on social influence. The occurrence of a paradigm shift becomes more likely when each member of the community attaches a small but positive weight to the experience of his/her peers. For this parameter region, nevertheless, a conservative force is exerted by the representatives of the current paradigm. However, social influence is not strong enough to seriously hamper individual discovery, and can act so as to empower successful individual pioneers who have conquered the new and superior paradigm.

Paradoxical Expectation: Oscillatory Brain Activity Reveals Social Interaction Impairment in Schizophrenia.

BACKGROUND: People with schizophrenia show social impairments that are related to functional outcomes. We tested the hypothesis that social interaction impairments in people with schizophrenia are related to alterations in the predictions of others' behavior and explored their underlying neurobiological mechanisms. METHODS: Electroencephalography was performed in 20 patients with schizophrenia and 25 well-matched control subjects. Participants played as proposers in the repeated version of the Ultimatum Game believing that they were playing with another human or with a computer. The power of oscillatory brain activity was obtained by means of the wavelet transform. We performed a trial-by-trial correlation between the oscillatory activity and the risk of the offer. RESULTS: Control subjects adapted their offers when playing with computers and tended to maintain their offers when playing with humans, as such revealing learning and bargaining strategies, respectively. People with schizophrenia presented the opposite pattern of behavior in both games. During the anticipation of others' responses, the power of alpha oscillations correlated with the risk of the offers made, in a different way in both games. Patients with schizophrenia presented a greater correlation in computer games than in human games; control subjects showed the opposite pattern. The alpha activity correlated with positive symptoms. CONCLUSIONS: Our results reveal an alteration in social interaction in patients with schizophrenia that is related to oscillatory brain activity, suggesting maladjustment of expectation when patients face social and nonsocial agents. This alteration is related to psychotic symptoms and could guide further therapies for improving social functioning in patients with schizophrenia.

Estimation of neural dynamics from MEG/EEG cortical current density maps: application to the reconstruction of large-scale cortical synchrony.

There is a growing interest in elucidating the role of specific patterns of neural dynamics--such as transient synchronization between distant cell assemblies--in brain functions. Magnetoencephalography (MEG)/electroencephalography (EEG) recordings consist in the spatial integration of the activity from large and multiple remotely located populations of neurons. Massive diffusive effects and poor signal-to-noise ratio (SNR) preclude the proper estimation of indices related to cortical dynamics from nonaveraged MEG/EEG surface recordings. Source localization from MEG/EEG surface recordings with its excellent time resolution could contribute to a better understanding of the working brain. We propose a robust and original approach to the MEG/EEG distributed inverse problem to better estimate neural dynamics of cortical sources. For this, the surrogate data method is introduced in the MEG/EEG inverse problem framework. We apply this approach on nonaveraged data with poor SNR using the minimum norm estimator and find source localization results weakly sensitive to noise. Surrogates allow the reduction of the source space in order to reconstruct MEG/EEG data with reduced biases in both source localization and time-series dynamics. Monte Carlo simulations and results obtained from real MEG data indicate it is possible to estimate non invasively an important part of cortical source locations and dynamic and, therefore, to reveal brain functional networks.

Estimating the time-course of coherence between single-trial brain signals: an introduction to wavelet coherence.

This paper introduces the use of wavelet analysis to follow the temporal variations in the coupling between oscillatory neural signals. Coherence, based on Fourier analysis, has been commonly used as a first approximation to track such coupling under the assumption that neural signals are stationary. Yet, stationary neural processing may be the exception rather than the rule. In this context, the recent application to physical systems of a wavelet-based coherence, which does not depend on the stationarity of the signals, is highly relevant. This paper fully develops the method of wavelet coherence and its statistical properties so that it can be practically applied to continuous neural signals. In realistic simulations, we show that, in contrast to Fourier coherence, wavelet coherence can detect short, significant episodes of coherence between non-stationary neural signals. This method can be directly applied for an 'online' quantification of the instantaneous coherence between two signals.

On the temporality of creative insight: a psychological and phenomenological perspective.

Research into creative insight has had a strong emphasis on the psychological processes underlying problem-solving situations as a standard model for the empirical study of this phenomenon. Although this model has produced significant advances in our scientific understanding of the nature of insight, we believe that a full comprehension of insight requires complementing cognitive and neuroscientific studies with a descriptive, first-person, phenomenological approach into how creative insight is experienced. Here we propose to take such first-person perspective while paying special attention to the temporal aspects of this experience. When this first-person perspective is taken into account, a dynamic past-future interplay can be identified at the core of the experience of creative insight, a structure that is compatible with both biological and biographical evidences. We believe this approach could complement and help bring together biological and psychological perspectives. Furthermore, we argue that because of its spontaneous but recurrent nature, creative insight could represent a relevant target for the phenomenological investigation of the flow of experience itself.