The Functional Role of Neural Oscillations in Non-Verbal Emotional Communication

Neurophysiological Responses to Vicarious Affective Touch: An Electroencephalography (EEG) Study

Affective touch is a somatosensory modality involved in forming and consolidating rewarding social interactions and is hypothesised to be encoded by a population of cutaneous unmyelinated low threshold mechanosensory C-tactile afferents (CT). CTs are preferentially activated by a caressing type of touch delivered at speeds around 3 cm/s (CT-optimal speed) and at skin temperature. Given its social relevance, the vicarious observation of affective touch can cause high empathic resonance in the observer. However, little is known whether the observation of CT-optimal touch is processed differently in the observer's brain than at other CT-suboptimal speeds. In our study, we evaluated subjective reports of the pleasantness/willingness of observers to receive such touch while recording the electroencephalogram (EEG) as they watched touch videos at three different speeds: static, slow (CT-optimal), and fast touch. We found that CT-optimal touch was rated as more pleasant and elicited greater willingness to engage, compared to static or fast touch. CT-optimal touch also led to significantly lower beta power, reflecting greater EEG desynchronisation, compared to the other conditions. Other frequency bands, such as theta and alpha, showed increased modulation to slow and fast touch compared to static touch. However, no differences were found between slow and fast conditions in the alpha and theta bands. Our results suggest that vicarious processing of affective touch at the optimal speed for CT receptors involves broader neural resources and higher activation of somatosensory areas, highlighting the significance of this touch modality in sensory processing.

Oscillating Mindfully: Using Machine Learning to Characterize Systems-Level Electrophysiological Activity During Focused Attention Meditation

Background

There has been rapid growth of neuroelectrophysiological studies that aspire to uncover the "black box" of mindfulness and meditation. Reliance on traditional data analysis methods hinders understanding of the complex, nonlinear, multidimensional, and systemic nature of the functional neuroelectrophysiology of meditation states.

Methods

Thus, to reveal the complex systemic neuroelectrophysiology of meditation, we applied a machine learning extreme gradient boosting classification algorithm and 4 complementary feature importance methods to extract systemic electroencephalography features characterizing mindful states from electroencephalography recorded during a focused attention meditation and a control mind-wandering state among 26 experienced meditators.

Results

The algorithm classified meditation versus mind-wandering states with 83% accuracy, with an area under the receiver operating characteristic curve of 79% and F1 score of 74%. Feature importance techniques identified 10 electroencephalography features associated with increased power and coherence of high-frequency oscillations during focused attention meditation relative to an instructed mind-wandering state.

Conclusions

The findings help delineate the complex systemic oscillatory activity that characterizes meditation.

Alterations in resting-state gamma-activity is adults with autism spectrum disorder: A High-Density EEG study

Autism spectrum disorder (ASD) is a neurodevelopmental disorder with a wide range of symptoms that include deficits in social cognition and difficulties with social interactions. Neural oscillations in the EEG gamma band have been proposed as an important candidate neurobiological marker of higher order cognitive processes and social interactions. We investigated resting-state gamma-activity of patients with ASD (n=23) in order to delineate alterations as compared to typically developing (TD) subjects (n=24). EEG absolute power was examined in the gamma (30-100Hz) frequency band. We found significantly reduced spectral power across the entire gamma range in the ASD group. The decrease was most pronounced over the inferior-frontal and temporo-parietal junction areas. We also found a significant decrease in gamma-activity over the dorsolateral prefrontal cortex, especially in the left side. Since these brain areas have been associated with social functioning, the reduced gamma-activity in ASD may represent a cortical dysfunction that could underlie a diminished capacity to interpret socially important information, thereby interfering with social functioning. The alterations we found may lend support for an improved diagnosis. Furthermore, they can lead to focused therapies, by targeting the dysfunctional brain activity to improve social cognitive and interaction abilities that are compromised in ASD.

HiRENet: Novel convolutional neural network architecture using Hilbert-transformed and raw electroencephalogram (EEG) for subject-independent emotion classification

BACKGROUND AND OBJECTIVES

Convolutional neural networks (CNNs) are the most widely used deep-learning framework for decoding electroencephalograms (EEGs) due to their exceptional ability to extract hierarchical features from high-dimensional EEG data. Traditionally, CNNs have primarily utilized multi-channel raw EEG data as the input tensor; however, the performance of CNN-based EEG decoding may be enhanced by incorporating phase information alongside amplitude information.

METHODS

This study introduces a novel CNN architecture called the Hilbert-transformed (HT) and raw EEG network (HiRENet), which incorporates both raw and HT EEG as inputs. This concurrent use of HT and raw EEG aims to integrate phase information with existing amplitude information, potentially offering a more comprehensive reflection of functional connectivity across various brain regions. The HiRENet model was developed using two CNN frameworks: ShallowFBCSPNet and a CNN with a residual block (ResCNN). The performance of the HiRENet model was assessed using a lab-made EEG database to classify human emotions, comparing three input modalities: raw EEG, HT EEG, and a combination of both signals. Additionally, the computational complexity was evaluated to validate the computational efficiency of the ResCNN design.

RESULTS

The HiRENet model based on ResCNN achieved the highest classification accuracy, with 86.03% for valence and 84.01% for arousal classifications, surpassing traditional CNN methodologies. Considering computational efficiency, ResCNN demonstrated superiority over ShallowFBCSPNet in terms of speed and inference time, despite having a higher parameter count.

CONCLUSION

Our experimental results showed that the proposed HiRENet can be potentially used as a new option to improve the overall performance for deep learning-based EEG decoding problems.

Relationship evolution shapes inter-brain synchrony in affective sharing: The role of self-expansion

The development of social relationships influences a person's self-concept, which in turn affects their perceptions and neural correlates in social interactions. This study employed an EEG-based hyperscanning technique and a longitudinal design to investigate how the evolution of interpersonal relationships impacts inter-brain synchrony during nonverbal social-emotional interactions. The framework for this study is based on the self-expansion model. We found that dyads exhibited enhanced affective sharing abilities and increased brain-to-brain synchrony, particularly in the gamma rhythm across the frontal, parietal, and left temporoparietal regions, after seven months together compared to when they first met. Additionally, the results indicate that inter-brain coupling evolves as relationships develop, with synchrony in nonverbal social-emotional interactions increasing as self-expansion progresses. Crucially, in the deep learning model, interpersonal closeness can be successfully classified by inter-brain synchrony during emotional-social interactions. The longitudinal EEG-hyperscanning design of our study allows for capturing dynamic changes over time, offering new insights into the neurobiological foundations of social interaction and the potential of neural synchrony as a biomarker for relationship dynamics.

Modulating Consciousness through Awareness Training Program and Its Impacts on Psychological Stress and Age-Related Gamma Waves

Aging often leads to awareness decline and psychological stress. Meditation, a method of modulating consciousness, may help individuals improve overall awareness and increase emotional resilience toward stress. This study explored the potential influence of the Awareness Training Program (ATP), a form of consciousness modulation, on age-related brain wave changes and psychological stress in middle-aged adults. Eighty-five participants with mild stress were recruited and randomly assigned to ATP (45.00 ± 8.00 yr) or control (46.67 ± 7.80 yr) groups, matched by age and gender. Ten-minute resting-state EEG data, obtained while the participants' eyes were closed, were collected using a 128-channel EEG system (EGI). A strong positive Pearson correlation was found between fast-wave (beta wave, 12-25 Hz; gamma wave, 25-40 Hz) EEG and age. However, after the 7-week ATP intervention, this correlation became insignificant in the ATP group. Furthermore, there was a significant reduction in stress levels, as measured by the Chinese version of the 10 item Perceived Stress Scale (PSS-10), in the ATP group. These results suggest that ATP may help modulate age-related effects on fast brain waves, as evidenced by the reduced correlation magnitude between age and gamma waves, and lower psychological stress. This suggests that ATP, as a form of consciousness modulation, may improve stress resilience and modulate age-related gamma wave changes.

Rhythms in Speech

Speech can be defined as the human ability to communicate through a sequence of vocal sounds. Consequently, speech requires an emitter (the speaker) capable of generating the acoustic signal and a receiver (the listener) able to successfully decode the sounds produced by the emitter (i.e., the acoustic signal). Time plays a central role at both ends of this interaction. On the one hand, speech production requires precise and rapid coordination, typically within the order of milliseconds, of the upper vocal tract articulators (i.e., tongue, jaw, lips, and velum), their composite movements, and the activation of the vocal folds. On the other hand, the generated acoustic signal unfolds in time, carrying information at different timescales. This information must be parsed and integrated by the receiver for the correct transmission of meaning. This chapter describes the temporal patterns that characterize the speech signal and reviews research that explores the neural mechanisms underlying the generation of these patterns and the role they play in speech comprehension.

Processing of attentional and emotional stimuli depends on retrospective response of foot pressure: Conceptualizing neuron-cognitive distribution in human brain

Cognitive function of human brain requires temporal execution of emotional or attentional tasks, or their inter-dependence influences. Smooth execution of such tasks requires spontaneous distribution of cognitive load at specific regions of brain based on its classification. A strong connectivity between peripheral sensors and central nervous system is thought to assist the cognitive load distribution effectively. Novelty of current study evaluates the modulation of foot pressure and its mapping with distributed cognitive load while executing attentional biased emotional tasks. Emotional stimulus in form of happy and sad faces with attentional paradigm drawn on them were used in the study. Behavioral results were measured with respect to the analysis of response time (RT) and response accuracy (%). Neurological signals were acquired using 10-channel EEG data acquisition system, whereas, another 6 channels were used to measure foot pressure in the left and right feet at three different locations of foot. Acquired signals were further analyzed in time and frequency domains to interpret the cognitive load distribution, and the influence of foot pressure on distribution of cognitive loads. We found that the foot pressure accelerated the response accuracy rate in attending the local scope of attention, which was not in the case of global scope of attention. This means that the global attention does not require any pressure from peripheral sensory neurons. Our event related potential (ERP) results revealed that the early sensory negative N100 characterized the processing of global scope of attention coupled with high-foot pressure. However, the late positive peak of P300 and P600 associated with local scope of attention along with high-foot pressure. The global scope of attention with low-foot pressure modulates delta and theta oscillations. These results largely contribute to the literature on cognitive neuroscience of attention and it corelation with the peripheral sensory foot pressure.

What is autonomous sensory meridian response (ASMR)? A narrative review and comparative analysis of related phenomena

A narrative review of autonomous sensory meridian response (ASMR) was carried out. Definitional factors relevant to ASMR were canvassed. Related, but distinctly unique, sensorial phenomena, including frisson, synaesthesia, and misophonia were considered. Finally, the status of literature with respect to clinical outcomes, individual differences, and current research applications was evaluated. ASMR is a nascent phenomenon that has rapidly progressed in scope and depth of study throughout the past decade; a notable shift from brief-form studies to an increase in formalised trials is noted. Yet, critical questions remain unaddressed, including expectancy and placebo effects, that future research should interrogate.

Aberrant neural correlates of multisensory processing of audiovisual social cues related to social anxiety: An electrophysiological study

BACKGROUND

Social anxiety disorder (SAD) is characterized by abnormal fear to social cues. Although unisensory processing to social stimuli associated with social anxiety (SA) has been well described, how multisensory processing relates to SA is still open to clarification. Using electroencephalography (EEG) measurement, we investigated the neural correlates of multisensory processing and related temporal dynamics in social anxiety disorder (SAD).

METHODS

Twenty-five SAD participants and 23 healthy control (HC) participants were presented with angry and neutral faces, voices and their combinations with congruent emotions and they completed an emotional categorization task.

RESULTS

We found that face-voice combinations facilitated auditory processing in multiple stages indicated by the acceleration of auditory N1 latency, attenuation of auditory N1 and P250 amplitudes, and decrease of theta power. In addition, bimodal inputs elicited cross-modal integrative activity which is indicated by the enhancement of visual P1, N170, and P3/LPP amplitudes and superadditive response of P1 and P3/LPP. More importantly, excessively greater integrative activity (at P3/LPP amplitude) was found in SAD participants, and this abnormal integrative activity in both early and late temporal stages was related to the larger interpretation bias of miscategorizing neutral face-voice combinations as angry.

CONCLUSION

The study revealed that neural correlates of multisensory processing was aberrant in SAD and it was related to the interpretation bias to multimodal social cues in multiple processing stages. Our findings suggest that deficit in multisensory processing might be an important factor in the psychopathology of SA.

10 Minutes Frontal 40 Hz tACS-Effects on Working Memory Tested by Luck-Vogel Task

Working memory is a cognitive process that involves short-term active maintenance, flexible updating, and processing of goal- or task-relevant information. All frequency bands are involved in working memory. The activities of the theta and gamma frequency bands in the frontoparietal network are highly involved in working memory processes; theta oscillations play a role in the temporal organization of working memory items, and gamma oscillations influence the maintenance of information in working memory. Transcranial alternating current stimulation (tACS) results in frequency-specific modulation of endogenous oscillations and has shown promising results in cognitive neuroscience. The electrophysiological and behavioral changes induced by the modulation of endogenous gamma frequency in the prefrontal cortex using tACS have not been extensively studied in the context of working memory. Therefore, we aimed to investigate the effects of frontal gamma-tACS on working memory outcomes. We hypothesized that a 10-min gamma tACS administered over the frontal cortex would significantly improve working memory outcomes. Young healthy participants performed Luck-Vogel cognitive behavioral tasks with simultaneous pre- and post-intervention EEG recording (Sham versus 40 Hz tACS). Data from forty-one participants: sham (15 participants) and tACS (26 participants), were used for the statistical and behavioral analysis. The relative changes in behavioral outcomes and EEG due to the intervention were analyzed. The results show that tACS caused an increase in the power spectral density in the high beta and low gamma EEG bands and a decrease in left-right coherence. On the other hand, tACS had no significant effect on success rates and response times. Conclusion: 10 min of frontal 40 Hz tACS was not sufficient to produce detectable behavioral effects on working memory, whereas electrophysiological changes were evident. The limitations of the current stimulation protocol and future directions are discussed in detail in the following sections.

Neurocognitive Dynamics of Prosodic Salience over Semantics during Explicit and Implicit Processing of Basic Emotions in Spoken Words

How language mediates emotional perception and experience is poorly understood. The present event-related potential (ERP) study examined the explicit and implicit processing of emotional speech to differentiate the relative influences of communication channel, emotion category and task type in the prosodic salience effect. Thirty participants (15 women) were presented with spoken words denoting happiness, sadness and neutrality in either the prosodic or semantic channel. They were asked to judge the emotional content (explicit task) and speakers' gender (implicit task) of the stimuli. Results indicated that emotional prosody (relative to semantics) triggered larger N100, P200 and N400 amplitudes with greater delta, theta and alpha inter-trial phase coherence (ITPC) and event-related spectral perturbation (ERSP) values in the corresponding early time windows, and continued to produce larger LPC amplitudes and faster responses during late stages of higher-order cognitive processing. The relative salience of prosodic and semantics was modulated by emotion and task, though such modulatory effects varied across different processing stages. The prosodic salience effect was reduced for sadness processing and in the implicit task during early auditory processing and decision-making but reduced for happiness processing in the explicit task during conscious emotion processing. Additionally, across-trial synchronization of delta, theta and alpha bands predicted the ERP components with higher ITPC and ERSP values significantly associated with stronger N100, P200, N400 and LPC enhancement. These findings reveal the neurocognitive dynamics of emotional speech processing with prosodic salience tied to stage-dependent emotion- and task-specific effects, which can reveal insights into understanding language and emotion processing from cross-linguistic/cultural and clinical perspectives.

Tackling the Electro-Topography of the Selves Through the Sphere Model of Consciousness

In the current hypothesis paper, we propose a novel examination of consciousness and self-awareness through the neuro-phenomenological theoretical model known as the Sphere Model of Consciousness (SMC). Our aim is to create a practical instrument to address several methodological issues in consciousness research. We present a preliminary attempt to validate the SMC via a simplified electrophysiological topographic map of the Self. This map depicts the gradual shift from faster to slower frequency bands that appears to mirror the dynamic between the various SMC states of Self. In order to explore our hypothesis that the SMC's different states of Self correspond to specific frequency bands, we present a mini-review of studies examining the electrophysiological activity that occurs within the different states of Self and in the context of specific meditation types. The theoretical argument presented here is that the SMC's hierarchical organization of three states of the Self mirrors the hierarchical organization of Focused Attention, Open Monitoring, and Non-Dual meditation types. This is followed by testable predictions and potential applications of the SMC and the hypotheses derived from it. To our knowledge, this is the first integrated electrophysiological account that combines types of Self and meditation practices. We suggest this electro-topographic framework of the Selves enables easier, clearer conceptualization of the connections between meditation types as well as increased understanding of wakefulness states and altered states of consciousness.

Cerebellar contribution to emotional body language perception: a TMS study

Consistent evidence suggests that the cerebellum contributes to the processing of emotional facial expressions. However, it is not yet known whether the cerebellum is recruited when emotions are expressed by body postures or movements, or whether it is recruited differently for positive and negative emotions. In this study, we asked healthy participants to discriminate between body postures (with masked face) expressing emotions of opposite valence (happiness vs anger, Experiment 1), or of the same valence (negative: anger vs sadness; positive: happiness vs surprise, Experiment 2). While performing the task, participants received online transcranial magnetic stimulation (TMS) over a region of the posterior left cerebellum and over two control sites (early visual cortex and vertex). We found that TMS over the cerebellum affected participants' ability to discriminate emotional body postures, but only when one of the emotions was negatively valenced (i.e. anger). These findings suggest that the cerebellar region we stimulated is involved in processing the emotional content conveyed by body postures and gestures. Our findings complement prior evidence on the role of the cerebellum in emotional face processing and have important implications from a clinical perspective, where non-invasive cerebellar stimulation is a promising tool for the treatment of motor, cognitive and affective deficits.

Brain reactivity to emotion persists in NREM sleep and is associated with individual dream recall

The waking brain efficiently detects emotional signals to promote survival. However, emotion detection during sleep is poorly understood and may be influenced by individual sleep characteristics or neural reactivity. Notably, dream recall frequency has been associated with stimulus reactivity during sleep, with enhanced stimulus-driven responses in high vs. low recallers. Using electroencephalography (EEG), we characterized the neural responses of healthy individuals to emotional, neutral voices, and control stimuli, both during wakefulness and NREM sleep. Then, we tested how these responses varied with individual dream recall frequency. Event-related potentials (ERPs) differed for emotional vs. neutral voices, both in wakefulness and NREM. Likewise, EEG arousals (sleep perturbations) increased selectively after the emotional voices, indicating emotion reactivity. Interestingly, sleep ERP amplitude and arousals after emotional voices increased linearly with participants' dream recall frequency. Similar correlations with dream recall were observed for beta and sigma responses, but not for theta. In contrast, dream recall correlations were absent for neutral or control stimuli. Our results reveal that brain reactivity to affective salience is preserved during NREM and is selectively associated to individual memory for dreams. Our findings also suggest that emotion-specific reactivity during sleep, and not generalized alertness, may contribute to the encoding/retrieval of dreams.

A Two-Person Neuroscience Approach for Social Anxiety: A Paradigm With Interbrain Synchrony and Neurofeedback

Social anxiety disorder has been widely recognised as one of the most commonly diagnosed mental disorders. Individuals with social anxiety disorder experience difficulties during social interactions that are essential in the regular functioning of daily routines; perpetually motivating research into the aetiology, maintenance and treatment methods. Traditionally, social and clinical neuroscience studies incorporated protocols testing one participant at a time. However, it has been recently suggested that such protocols are unable to directly assess social interaction performance, which can be revealed by testing multiple individuals simultaneously. The principle of two-person neuroscience highlights the interpersonal aspect of social interactions that observes behaviour and brain activity from both (or all) constituents of the interaction, rather than analysing on an individual level or an individual observation of a social situation. Therefore, two-person neuroscience could be a promising direction for assessment and intervention of the social anxiety disorder. In this paper, we propose a novel paradigm which integrates two-person neuroscience in a neurofeedback protocol. Neurofeedback and interbrain synchrony, a branch of two-person neuroscience, are discussed in their own capacities for their relationship with social anxiety disorder and relevance to the paradigm. The newly proposed paradigm sets out to assess the social interaction performance using interbrain synchrony between interacting individuals, and to employ a multi-user neurofeedback protocol for intervention of the social anxiety.

Sharing Happy Stories Increases Interpersonal Closeness: Interpersonal Brain Synchronization as a Neural Indicator

Our lives revolve around sharing emotional stories (i.e., happy and sad stories) with other people. Such emotional communication enhances the similarity of story comprehension and neural across speaker-listener pairs. The theory of Emotions as Social Information Model (EASI) suggests that such emotional communication may influence interpersonal closeness. However, few studies have examined speaker-listener interpersonal brain synchronization (IBS) during emotional communication and whether it is associated with meaningful aspects of the speaker-listener interpersonal relationship. Here, one speaker watched emotional videos and communicated the content of the videos to 32 people as listeners (happy/sad/neutral group). Both speaker and listeners’ neural activities were recorded using EEG. After listening, we assessed the interpersonal closeness between the speaker and listeners. Compared with the sad group, sharing happy stories showed a better recall quality and a higher rating of interpersonal closeness. The happy group showed higher IBS in the frontal cortex and left temporoparietal cortex than the sad group. The relationship between frontal IBS and interpersonal closeness was moderated by sharing happy/sad stories. Exploratory analysis using support vector regression (SVR) showed that the IBS could also predict the ratings of interpersonal closeness. These results suggest that frontal IBS could serve as an indicator of whether sharing emotional stories facilitate interpersonal closeness. These findings improve our understanding of emotional communication among individuals that guides behaviors during interpersonal interactions.

An Effortful Approach to Social Affiliation in Schizophrenia: Preliminary Evidence of Increased Theta and Alpha Connectivity during a Live Social Interaction

People with schizophrenia often experience a profound lack of motivation for social affiliation—a facet of negative symptoms that detrimentally impairs functioning. However, the mechanisms underlying social affiliative deficits remain poorly understood, particularly under realistic social contexts. Here, we investigated subjective reports and electroencephalography (EEG) functional connectivity in schizophrenia during a live social interaction. Individuals with schizophrenia (n = 16) and healthy controls (n = 29) completed a face-to-face interaction with a confederate while having EEG recorded. Participants were randomly assigned to either a Closeness condition designed to elicit feelings of closeness through self-disclosure or a Small-Talk condition with minimal disclosure. Compared to controls, patients reported lower positive emotional experiences and feelings of closeness across conditions, but they showed comparably greater subjective affiliative responses for the Closeness (vs. Small-Talk) condition. Additionally, patients in the Closeness (vs. Small-Talk) condition displayed a global increase in connectivity in theta and alpha frequency bands that was not observed for controls. Importantly, greater theta and alpha connectivity was associated with greater subjective affiliative responding, greater negative symptoms, and lower disorganized symptoms in patients. Collectively, findings indicate that patients, because of pronounced negative symptoms, utilized a less efficient, top-down mediated strategy to process social affiliation.

Neural Rhythmic Underpinnings of Intergroup Bias: Implications for Peace-Building Attitudes and Dialogue

Intergroup bias is a ubiquitous socio-cognitive phenomenon that, while sustaining human dependence on group living, often leads to prejudice, inequity, and violence; yet, its neural underpinnings remain unclear. Framed within the Israeli-Palestinian conflict and targeting youth, this study utilized magnetoencephalography to describe intrinsic neural oscillatory processes that represent the intergroup bias and may link with engagement in peacemaking in order to shed further light on the neural mechanisms underpinning intergroup conflict. Across the oscillatory spectrum, from very low to very high frequency bands, the only rhythm found to underlie the intergroup bias was the alpha rhythm. Alpha was continuously activated across the task and integrated a rapid perceptual component in occipital cortex with a top-down cognitive-control component in medial cingulate cortex. These components were distinctly associated with real-life intergroup dialog style and expressed attitudes that promote active engagement in peacemaking. Our findings suggest that the cortical alpha rhythm plays a crucial role in sustaining intergroup bias and address its impact on concrete intergroup experiences. Results highlight the need to provide opportunities for active peace-building dialog to youth reared amidst intractable conflicts.

A novel beamformer-based imaging of phase-amplitude coupling (BIPAC) unveiling the inter-regional connectivity of emotional prosody processing in women with primary dysmenorrhea

Objective. Neural communication or the interactions of brain regions play a key role in the formation of functional neural networks. A type of neural communication can be measured in the form of phase-amplitude coupling (PAC), which is the coupling between the phase of low-frequency oscillations and the amplitude of high-frequency oscillations. This paper presents a beamformer-based imaging method, beamformer-based imaging of PAC (BIPAC), to quantify the strength of PAC between a seed region and other brain regions.Approach. A dipole is used to model the ensemble of neural activity within a group of nearby neurons and represents a mixture of multiple source components of cortical activity. From ensemble activity at each brain location, the source component with the strongest coupling to the seed activity is extracted, while unrelated components are suppressed to enhance the sensitivity of coupled-source estimation.Main results. In evaluations using simulation data sets, BIPAC proved advantageous with regard to estimation accuracy in source localization, orientation, and coupling strength. BIPAC was also applied to the analysis of magnetoencephalographic signals recorded from women with primary dysmenorrhea in an implicit emotional prosody experiment. In response to negative emotional prosody, auditory areas revealed strong PAC with the ventral auditory stream and occipitoparietal areas in the theta-gamma and alpha-gamma bands, which may respectively indicate the recruitment of auditory sensory memory and attention reorientation. Moreover, patients with more severe pain experience appeared to have stronger coupling between auditory areas and temporoparietal regions.Significance. Our findings indicate that the implicit processing of emotional prosody is altered by menstrual pain experience. The proposed BIPAC is feasible and applicable to imaging inter-regional connectivity based on cross-frequency coupling estimates. The experimental results also demonstrate that BIPAC is capable of revealing autonomous brain processing and neurodynamics, which are more subtle than active and attended task-driven processing.

Dance on the Brain: Enhancing Intra- and Inter-Brain Synchrony

Dance has traditionally been viewed from a Eurocentric perspective as a mode of self-expression that involves the human body moving through space, performed for the purposes of art, and viewed by an audience. In this Hypothesis and Theory article, we synthesize findings from anthropology, sociology, psychology, dance pedagogy, and neuroscience to propose The Synchronicity Hypothesis of Dance, which states that humans dance to enhance both intra- and inter-brain synchrony. We outline a neurocentric definition of dance, which suggests that dance involves neurobehavioral processes in seven distinct areas including sensory, motor, cognitive, social, emotional, rhythmic, and creative. We explore The Synchronicity Hypothesis of Dance through several avenues. First, we examine evolutionary theories of dance, which suggest that dance drives interpersonal coordination. Second, we examine fundamental movement patterns, which emerge throughout development and are omnipresent across cultures of the world. Third, we examine how each of the seven neurobehaviors increases intra- and inter-brain synchrony. Fourth, we examine the neuroimaging literature on dance to identify the brain regions most involved in and affected by dance. The findings presented here support our hypothesis that we engage in dance for the purpose of intrinsic reward, which as a result of dance-induced increases in neural synchrony, leads to enhanced interpersonal coordination. This hypothesis suggests that dance may be helpful to repattern oscillatory activity, leading to clinical improvements in autism spectrum disorder and other disorders with oscillatory activity impairments. Finally, we offer suggestions for future directions and discuss the idea that our consciousness can be redefined not just as an individual process but as a shared experience that we can positively influence by dancing together.

The Presence of Another Person Influences Oscillatory Cortical Dynamics During Dual Brain EEG Recording

Humans are innately social creatures and the social environment strongly influences brain development. As such, the human brain is primed for and sensitive to social information even in the absence of explicit task or instruction. In this study, we examined the influence of different levels of interpersonal proximity on resting state brain activity and its association with social cognition. We measured EEG in pairs of 13 typically developing (TD) adults seated in separate rooms, in the same room back-to-back, and in the same room facing each other. Interpersonal proximity modulated broadband EEG power from 4-55 Hz and individual differences in self-reported social cognition modulated these effects in the beta and gamma frequency bands. These findings provide novel insight into the influence of social environment on brain activity and its association with social cognition through dual-brain EEG recording and demonstrate the importance of using interactive methods to study the human brain.

Aberrant Whole-Brain Transitions and Dynamics of Spontaneous Network Microstates in Mild Traumatic Brain Injury

Dynamic Functional Connectivity (DFC) analysis is a promising approach for the characterization of brain electrophysiological activity. In this study, we investigated abnormal alterations due to mild Traumatic Brain Injury (mTBI) using DFC of the source reconstructed magnetoencephalographic (MEG) resting-state recordings. Brain activity in several well-known frequency bands was first reconstructed using beamforming of the MEG data to determine ninety anatomical brain regions of interest. A DFC graph was formulated using the imaginary part of phase-locking values, which were obtained from 30 mTBI patients and 50 healthy controls (HC). Subsequently, we estimated normalized Laplacian transformations of individual, statistically and topologically filtered quasi-static graphs. The corresponding eigenvalues of each node synchronization were then computed and through the neural-gas algorithm, we quantized the evolution of the eigenvalues resulting in distinct network microstates (NMstates). The discrimination level between the two groups was assessed using an iterative cross-validation classification scheme with features either the NMstates in each frequency band, or the combination of the so-called chronnectomics (flexibility index, occupancy time of NMstate, and Dwell time) with the complexity index over the evolution of the NMstates across all frequency bands. Classification performance based on chronnectomics showed 80% accuracy, 99% sensitivity, and 49% specificity. However, performance was much higher (accuracy: 91-97%, sensitivity: 100%, and specificity: 77-93%) when focusing on the microstates. Exploring the mean node degree within and between brain anatomical networks (default mode network, frontoparietal, occipital, cingulo-opercular, and sensorimotor), a reduced pattern occurred from lower to higher frequency bands, with statistically significant stronger degrees for the HC than the mTBI group. A higher entropic profile on the temporal evolution of the modularity index was observed for both NMstates for the mTBI group across frequencies. A significant difference in the flexibility index was observed between the two groups for the β frequency band. The latter finding may support a central role of the thalamus impairment in mTBI. The current study considers a complete set of frequency-dependent connectomic markers of mTBI-caused alterations in brain connectivity that potentially could serve as markers to assess the return of an injured subject back to normality.

Neural Decoding of Multi-Modal Imagery Behavior Focusing on Temporal Complexity

Mental imagery behaviors of various modalities include visual, auditory, and motor behaviors. Their alterations are pathologically involved in various psychiatric disorders. Results of earlier studies suggest that imagery behaviors are correlated with the modulated activities of the respective modality-specific regions and the additional activities of supramodal imagery-related regions. Additionally, despite the availability of complexity analysis in the neuroimaging field, it has not been used for neural decoding approaches. Therefore, we sought to characterize neural oscillation related to multimodal imagery through complexity-based neural decoding. For this study, we modified existing complexity measures to characterize the time evolution of temporal complexity. We took magnetoencephalography (MEG) data of eight healthy subjects as they performed multimodal imagery and non-imagery tasks. The MEG data were decomposed into amplitude and phase of sub-band frequencies by Hilbert-Huang transform. Subsequently, we calculated the complexity values of each reconstructed time series, along with raw data and band power for comparison, and applied these results as inputs to decode visual perception (VP), visual imagery (VI), motor execution (ME), and motor imagery (MI) functions. Consequently, intra-subject decoding with the complexity yielded a characteristic sensitivity map for each task with high decoding accuracy. The map is inverted in the occipital regions between VP and VI and in the central regions between ME and MI. Additionally, replacement of the labels into two classes as imagery and non-imagery also yielded better classification performance and characteristic sensitivity with the complexity. It is particularly interesting that some subjects showed characteristic sensitivities not only in modality-specific regions, but also in supramodal regions. These analyses indicate that two-class and four-class classifications each provided better performance when using complexity than when using raw data or band power as input. When inter-subject decoding was used with the same model, characteristic sensitivity maps were also obtained, although their decoding performance was lower. Results of this study underscore the availability of complexity measures in neural decoding approaches and suggest the possibility of a modality-independent imagery-related mechanism. The use of time evolution of temporal complexity in neural decoding might extend our knowledge of the neural bases of hierarchical functions in the human brain.

Decomposed Temporal Complexity Analysis of Neural Oscillations and Machine Learning Applied to Alzheimer's Disease Diagnosis

Despite growing evidence of aberrant neuronal complexity in Alzheimer's disease (AD), it remains unclear how this variation arises. Neural oscillations reportedly comprise different functions depending on their own properties. Therefore, in this study, we investigated details of the complexity of neural oscillations by decomposing the oscillations into frequency, amplitude, and phase for AD patients. We applied resting-state magnetoencephalography (MEG) to 17 AD patients and 21 healthy control subjects. We first decomposed the source time series of the MEG signal into five intrinsic mode functions using ensemble empirical mode decomposition. We then analyzed the temporal complexities of these time series using multiscale entropy. Results demonstrated that AD patients had lower complexity on short time scales and higher complexity on long time scales in the alpha band in temporal regions of the brain. We evaluated the alpha band complexity further by decomposing it into amplitude and phase using Hilbert spectral analysis. Consequently, we found lower amplitude complexity and higher phase complexity in AD patients. Correlation analyses between spectral complexity and decomposed complexities revealed scale-dependency. Specifically, amplitude complexity was positively correlated with spectral complexity on short time scales, whereas phase complexity was positively correlated with spectral complexity on long time scales. Regarding the relevance of cognitive function to the complexity measures, the phase complexity on the long time scale was found to be correlated significantly with the Mini-Mental State Examination score. Additionally, we examined the diagnostic utility of the complexity characteristics using machine learning (ML) methods. We prepared a feature pool using multiple sparse autoencoders (SAEs), chose some discriminating features, and applied them to a support vector machine (SVM). Compared to the simple SVM and the SVM after feature selection (FS + SVM), the SVM with multiple SAEs (SAE + FS + SVM) had improved diagnostic accuracy. Through this study, we 1) advanced the understanding of neuronal complexity in AD patients using decomposed temporal complexity analysis and 2) demonstrated the effectiveness of combining ML methods with information about signal complexity for the diagnosis of AD.

Imbalance between Emotionally Negative and Positive Life Events Retrieval and the Associated Asymmetry of Brain Activity

Sustained focusing on a negative assessment of life events can create negative background and changes in the emotional feedback to new information. In this regard, it is important to assess the balance between self-assessment of emotional memories and their reflection in brain activity. The study was aimed at exploring the brain activity using electroencephalographic (EEG) analysis in six frequency ranges from delta to beta2 during the retrieval of positive or negative emotional memory compared with the resting state. According to ANOVA results, the most informative for differentiation of emotions were the alpha2 and beta2 rhythms with greater synchronization effect for positive than for negative emotions. The memory retrieval, regardless of the valence of emotions, was accompanied by alpha1 desynchronization at the posterior cortex. Self-assessment of the memory intensity was not significantly different due to emotion valences. However, the scores of positive emotions were related positively with beta2 oscillations at the left anterior temporal site, whereas for negative emotions, at the right one. Thus, the emotional autobiographical memory is reflected by activation processes in the visual cortex and areas associated with multimodal information processing, whereas differentiation of the valence of emotions is presented by the high-frequency oscillations at the temporal cortex areas.

On the Hierarchical Organization of Oscillatory Assemblies: Layered Superimposition and a Global Bioelectric Framework

Bioelectric oscillations occur throughout the nervous system of nearly all animals, revealed to play an important role in various aspects of cognitive activity such as information processing and feature binding. Modern research into this dynamic and intrinsic bioelectric activity of neural cells continues to raise questions regarding their role in consciousness and cognition. In this theoretical article, we assert a novel interpretation of the hierarchical nature of "brain waves" by identifying that the superposition of multiple oscillations varying in frequency corresponds to the superimposing of the contents of consciousness and cognition. In order to describe this isomorphism, we present a layered model of the global functional oscillations of various frequencies which act as a part of a unified metastable continuum described by the Operational Architectonics theory and suggested to be responsible for the emergence of the phenomenal mind. We detail the purposes, functions, and origins of each layer while proposing our main theory that the superimposition of these oscillatory layers mirrors the superimposition of the components of the integrated phenomenal experience as well as of cognition. In contrast to the traditional view that localizations of high and low-frequency activity are spatially distinct, many authors have suggested a hierarchical nature to oscillations. Our theoretical interpretation is founded in four layers which correlate not only in frequency but in evolutionary development. As other authors have done, we explore how these layers correlate to the phenomenology of human experience. Special importance is placed on the most basal layer of slow oscillations in coordinating and grouping all of the other layers. By detailing the isomorphism between the phenomenal and physiologic aspects of how lower frequency layers provide a foundation for higher frequency layers to be organized upon, we provide a further means to elucidate physiological and cognitive mechanisms of mind and for the well-researched outcomes of certain voluntary breathing patterns and meditative practices which modulate the mind and have therapeutic effects for psychiatric and other disorders.

Chronic trauma impairs the neural basis of empathy in mothers: Relations to parenting and children's empathic abilities

Early life stress carries long-term negative consequences for children's well-being and maturation of the social brain. Here, we utilize a unique cohort to test its effects on mothers' social brain, targeting mothers' neural empathic response in relation to caregiving and child empathic abilities. Mother-child dyads living in a zone of repeated war-related trauma were followed from early childhood and mother-child behavioral synchrony was repeatedly observed. At pre-adolescence(11-13 years) children's empathic abilities were assessed and mothers(N = 88, N = 44 war-exposed) underwent magnetoencephalography(MEG) while exposed to vicarious pain. All mothers showed alpha suppression in sensorimotor regions, indicating automatic response to others' pain. However, trauma-exposed mothers did not exhibit gamma oscillations in viceromotor cortex, a neural marker of mature empathy which utilizes interoceptive mechanisms for higher-order understanding and does not emerge before adulthood. Mother-child synchrony across the first decade predicted mothers' viceromotor gamma, and both synchrony and maternal viceromotor gamma mediated the relations between war-exposure and child empathic abilities, possibly charting a cross-generational pathway from mothers' mature neural empathy to children's empathic capacities. Our findings are first to probe the maternal social brain in adolescence in relation to parenting and underscore the need for targeted interventions to mothers raising children in contexts of chronic stress.

Human olfactory-auditory integration requires phase synchrony between sensory cortices

Multisensory integration is particularly important in the human olfactory system, which is highly dependent on non-olfactory cues, yet its underlying neural mechanisms are not well understood. In this study, we use intracranial electroencephalography techniques to record neural activity in auditory and olfactory cortices during an auditory-olfactory matching task. Spoken cues evoke phase locking between low frequency oscillations in auditory and olfactory cortices prior to odor arrival. This phase synchrony occurs only when the participant's later response is correct. Furthermore, the phase of low frequency oscillations in both auditory and olfactory cortical areas couples to the amplitude of high-frequency oscillations in olfactory cortex during correct trials. These findings suggest that phase synchrony is a fundamental mechanism for integrating cross-modal odor processing and highlight an important role for primary olfactory cortical areas in multisensory integration with the olfactory system.

Understanding the Effects and Adverse Reactions of Deep Brain Stimulation: Is It Time for a Paradigm Shift Toward a Focus on Heterogenous Biophysical Tissue Properties Instead of Electrode Design Only?

Deep brain stimulation (DBS) has been proven to be an effective treatment modality for various late-stage neurological and psychiatric disorders. However, knowledge on the electrical field distribution in the brain tissue is still scarce. Most recent attempts to understand electric field spread were primarily focused on the effect of different electrodes on rather simple tissue models. The influence of microanatomic, biophysical tissue properties in particular has not been investigated in depth. Ethical concerns restrict thorough research on field distribution in human in vivo brain tissue. By means of a simplified model, we investigated the electric field distribution in a broader area of the subthalamic nucleus (STN). Pivotal biophysical parameters including conductivity, permittivity and permeability of brain tissue were incorporated in the model. A brain tissue model was created with the finite element method (FEM). Stimulation was mimicked with parameters used for monopolar stimulation of patients suffering from Parkinson's disease. Our results were visualized with omnidirectional and segmented electrodes. The stimulated electric field was visualized with superimpositions on a stereotactic atlas (Morel). Owing to the effects of regional tissue properties near the stimulating electrode, marked field distortions occur. Such effects include, for example, isolating effects of heavily myelinated neighboring structures, e.g., the internal capsule. In particular, this may be illustrated through the analysis of a larger coronal area. While omnidirectional stimulation has been associated with vast current leakage, higher targeting precision was obtained with segmented electrodes. Finally, targeting was improved when the influence of microanatomic structures on the electric spread was considered. Our results confirm that lead design is not the sole influence on current spread. An omnidirectional lead configuration does not automatically result in an omnidirectional spread of current. In turn, segmented electrodes do not automatically imply an improved steering of current. Our findings may provide an explanation for side-effects secondary to current leakage. Furthermore, a possible explanation for divergent results in the comparison of the intraoperative awake patient and the postoperative setting is given. Due to the major influence of biophysical tissue properties on electric field shape, the local microanatomy should be considered for precise surgical targeting and optimal hardware implantation.

A touching Sight: EEG/ERP correlates for the vicarious processing of affectionate touch

Observers can simulate aspects of other people's tactile experiences. We asked whether they do so when faced with full-body social interactions, whether emerging representations go beyond basic sensorimotor mirroring, and whether they depend on processing goals and inclinations. In an EEG/ERP study, we presented line-drawn, dyadic interactions with and without affectionate touch. In an explicit and an implicit task, participants categorized images into touch versus no-touch and same versus opposite sex interactions, respectively. Modulations of central Rolandic rhythms implied that affectionate touch displays engaged sensorimotor mechanisms. Additionally, the late positive potential (LPP) being larger for images with as compared to without touch pointed to an involvement of higher order socio-affective mechanisms. Task and sex modulated touch perception. Sensorimotor responding, indexed by Rolandic rhythms, was fairly independent of the task but appeared less effortful in women than in men. Touch induced socio-affective responding, indexed by the LPP, declined from explicit to implicit processing in women and disappeared in men. In sum, this study provides first evidence that vicarious touch from full-body social interactions entails shared sensorimotor as well as socio-affective experiences. Yet, mental representations of touch at a socio-affective level are more likely when touch is goal relevant and observers are female. Together, these results outline the conditions under which touch in visual media may be usefully employed to socially engage observers.

Interactive Brain Activity: Review and Progress on EEG-Based Hyperscanning in Social Interactions

When individuals interact with others, perceived information is transmitted among their brains. The EEG-based hyperscanning technique, which provides an approach to explore dynamic brain activities between two or more interactive individuals and their underlying neural mechanisms, has been applied to study different aspects of social interactions since 2010. Recently there has been an increase in research on EEG-based hyperscanning of social interactions. This paper summarizes the application of EEG-based hyperscanning on the dynamic brain activities during social interactions according to the experimental designs and contents, discusses the possibility of applying inter-brain synchrony to social communication systems and analyzes the contributions and the limitations of these investigations. Furthermore, this paper sheds light on some new challenges to future EEG-based hyperscanning studies and the emerging field of EEG-based hyperscanning for pursuing the broader research field of social interactions.

Brain Networks, Emotion Components, and Appraised Relevance

Modeling emotion processes remains a conceptual and methodological challenge in affective sciences. In responding to the other target articles in this special section on “Emotion and the Brain” and the comments on our article, we address the issue of potentially separate brain networks subserving the functions of the different emotion components. In particular, we discuss the suggested role of component synchronization in producing information integration for the dynamic emergence of a coherent emotion process, as well as the links between incentive salience (“wanting”) and concern-relevance in the elicitation of emotion.

Perception of social synchrony induces mother-child gamma coupling in the social brain

The recent call to move from focus on one brain’s functioning to two-brain communication initiated a search for mechanisms that enable two humans to coordinate brain response during social interactions. Here, we utilized the mother–child context as a developmentally salient setting to study two-brain coupling. Mothers and their 9-year-old children were videotaped at home in positive and conflictual interactions. Positive interactions were microcoded for social synchrony and conflicts for overall dialogical style. Following, mother and child underwent magnetoencephalography while observing the positive vignettes. Episodes of behavioral synchrony, compared to non-synchrony, increased gamma-band power in the superior temporal sulcus (STS), hub of social cognition, mirroring and mentalizing. This neural pattern was coupled between mother and child. Brain-to-brain coordination was anchored in behavioral synchrony; only during episodes of behavioral synchrony, but not during non-synchronous moments, mother’s and child's STS gamma power was coupled. Importantly, neural synchrony was not found during observation of unfamiliar mother-child interaction Maternal empathic/dialogical conflict style predicted mothers’ STS activations whereas child withdrawal predicted attenuated STS response in both partners. Results define a novel neural marker for brain-to-brain synchrony, highlight the role of rapid bottom-up oscillatory mechanisms for neural coupling and indicate that behavior-based processes may drive synchrony between two brains during social interactions.

Review of the Neural Oscillations Underlying Meditation

Objective: Meditation is one type of mental training that has been shown to produce many cognitive benefits. Meditation practice is associated with improvement in concentration and reduction of stress, depression, and anxiety symptoms. Furthermore, different forms of meditation training are now being used as interventions for a variety of psychological and somatic illnesses. These benefits are thought to occur as a result of neurophysiologic changes. The most commonly studied specific meditation practices are focused attention (FA), open-monitoring (OM), as well as transcendental meditation (TM), and loving-kindness (LK) meditation. In this review, we compare the neural oscillatory patterns during these forms of meditation.

Method: We performed a systematic review of neural oscillations during FA, OM, TM, and LK meditation practices, comparing meditators to meditation-naïve adults.

Results: FA, OM, TM, and LK meditation are associated with global increases in oscillatory activity in meditators compared to meditation-naïve adults, with larger changes occurring as the length of meditation training increases. While FA and OM are related to increases in anterior theta activity, only FA is associated with changes in posterior theta oscillations. Alpha activity increases in posterior brain regions during both FA and OM. In anterior regions, FA shows a bilateral increase in alpha power, while OM shows a decrease only in left-sided power. Gamma activity in these meditation practices is similar in frontal regions, but increases are variable in parietal and occipital regions.

Conclusions: The current literature suggests distinct differences in neural oscillatory activity among FA, OM, TM, and LK meditation practices. Further characterizing these oscillatory changes may better elucidate the cognitive and therapeutic effects of specific meditation practices, and potentially lead to the development of novel neuromodulation targets to take advantage of their benefits.

The role of the cerebellum in explicit and incidental processing of facial emotional expressions: A study with transcranial magnetic stimulation

Growing evidence suggests that the cerebellum plays a critical role in non-motor functions, contributing to cognitive and affective processing. In particular, the cerebellum might represent an important node of the "limbic" network, underlying not only emotion regulation but also emotion perception and recognition. Here, we used transcranial magnetic stimulation (TMS) to shed further light on the role of the cerebellum in emotional perception by specifically testing cerebellar contribution to explicit and incidental emotional processing. In particular, in three different experiments, we found that TMS over the (left) cerebellum impaired participants' ability to categorize facial emotional expressions (explicit task) and to classify the gender of emotional faces (incidental emotional processing task), but not the gender of neutral faces. Overall, our results indicate that the cerebellum is involved in perceiving the emotional content of facial stimuli, even when this is task irrelevant.

Brain-to-Brain Synchrony during Naturalistic Social Interactions

The evolution of humans as a highly social species tuned the brain to the social world; yet the mechanisms by which humans coordinate their brain response online during social interactions remain unclear. Using hyperscanning EEG recordings, we measured brain-to-brain synchrony in 104 adults during a male-female naturalistic social interaction, comparing romantic couples and strangers. Neural synchrony was found for couples, but not for strangers, localized to temporal-parietal structures and expressed in gamma rhythms. Brain coordination was not found during a three-minute rest, pinpointing neural synchrony to social interactions among affiliative partners. Brain-to-brain synchrony was linked with behavioral synchrony. Among couples, neural synchrony was anchored in moments of social gaze and positive affect, whereas among strangers, longer durations of social gaze and positive affect correlated with greater neural synchrony. Brain-to-brain synchrony was unrelated to episodes of speech/no-speech or general content of conversation. Our findings link brain-to-brain synchrony to the degree of social connectedness among interacting partners, ground neural synchrony in key nonverbal social behaviors, and highlight the role of human attachment in providing a template for two-brain coordination.

Analysis of functional brain connections for positive-negative emotions using phase locking value

In this study, we investigate the brain networks during positive and negative emotions for different types of stimulus (audio only, video only and audio + video) in [Formula: see text], and [Formula: see text] bands in terms of phase locking value, a nonlinear method to study functional connectivity. Results show notable hemispheric lateralization as phase synchronization values between channels are significant and high in right hemisphere for all emotions. Left frontal electrodes are also found to have control over emotion in terms of functional connectivity. Besides significant inter-hemisphere phase locking values are observed between left and right frontal regions, specifically between left anterior frontal and right mid-frontal, inferior-frontal and anterior frontal regions; and also between left and right mid frontal regions. ANOVA analysis for stimulus types show that stimulus types are not separable for emotions having high valence. PLV values are significantly different only for negative emotions or neutral emotions between audio only/video only and audio only/audio + video stimuli. Finding no significant difference between video only and audio + video stimuli is interesting and might be interpreted as that video content is the most effective part of a stimulus.

Low-frequency oscillations employ a general coding of the spatio-temporal similarity of dynamic faces

Brain networks use neural oscillations as information transfer mechanisms. Although the face perception network in occipitotemporal cortex is well-studied, contributions of oscillations to face representation remain an open question. We tested for links between oscillatory responses that encode facial dimensions and the theoretical proposal that faces are encoded in similarity-based "face spaces". We quantified similarity-based encoding of dynamic faces in magnetoencephalographic sensor-level oscillatory power for identity, expression, physical and perceptual similarity of facial form and motion. Our data show that evoked responses manifest physical and perceptual form similarity that distinguishes facial identities. Low-frequency induced oscillations (< 20Hz) manifested more general similarity structure, which was not limited to identity, and spanned physical and perceived form and motion. A supplementary fMRI-constrained source reconstruction implicated fusiform gyrus and V5 in this similarity-based representation. These findings introduce a potential link between "face space" encoding and oscillatory network communication, which generates new hypotheses about the potential oscillation-mediated mechanisms that might encode facial dimensions.

Rapid gamma oscillations in the inferior occipital gyrus in response to eyes

Eyes are an indispensable communication medium for human social interactions. Although previous neuroscientific evidence suggests the activation of the inferior occipital gyrus (IOG) during eye processing, the temporal profile of this activation remains unclear. To investigate this issue, we analyzed intracranial electroencephalograms of the IOG during the presentation of eyes and mosaics, in either averted or straight directions. Time–frequency statistical parametric mapping analyses revealed greater gamma-band activation in the right IOG beginning at 114 ms in response to eyes relative to mosaics, irrespective of their averted or straight direction. These results suggest that gamma oscillations in the right IOG are involved in the early stages of eye processing, such as eye detection.