EEG spectral and microstate analysis originating residual inhibition of tinnitus induced by tailor-made notched music training

Tailor-made notched music training (TMNMT) is a promising therapy for tinnitus. Residual inhibition (RI) is one of the few interventions that can temporarily inhibit tinnitus, which is a useful technique that can be applied to tinnitus research and explore tinnitus mechanisms. In this study, RI effect of TMNMT in tinnitus was investigated mainly using behavioral tests, EEG spectral and microstate analysis. To our knowledge, this study is the first to investigate RI effect of TMNMT. A total of 44 participants with tinnitus were divided into TMNMT group (22 participants; ECnm, NMnm, RInm represent that EEG recordings with eyes closed stimuli-pre, stimuli-ing, stimuli-post by TMNMT music, respectively) and Placebo control group (22 participants; ECpb, PBpb, RIpb represent that EEG recordings with eyes closed stimuli-pre, stimuli-ing, stimuli-post by Placebo music, respectively) in a single-blind manner. Behavioral tests, EEG spectral analysis (covering delta, theta, alpha, beta, gamma frequency bands) and microstate analysis (involving four microstate classes, A to D) were employed to evaluate RI effect of TMNMT. The results of the study showed that TMNMT had a stronger inhibition ability and longer inhibition time according to the behavioral tests compared to Placebo. Spectral analysis showed that RI effect of TMNMT increased significantly the power spectral density (PSD) of delta, theta bands and decreased significantly the PSD of alpha2 band, and microstate analysis showed that RI effect of TMNMT had shorter duration (microstate B, microstate C), higher Occurrence (microstate A, microstate C, microstate D), Coverage (microstate A) and transition probabilities (microstate A to microstate B, microstate A to microstate D and microstate D to microstate A). Meanwhile, RI effect of Placebo decreased significantly the PSD of alpha2 band, and microstate analysis showed that RI effect of Placebo had shorter duration (microstate C, microstate D), higher occurrence (microstate B, microstate C), lower coverage (microstate C, microstate D), higher transition probabilities (microstate A to microstate B, microstate B to microstate A). It was also found that the intensity of tinnitus symptoms was significant positively correlated with the duration of microstate B in five subgroups (ECnm, NMnm, RInm, ECpb, PBpb). Our study provided valuable experimental evidence and practical applications for the effectiveness of TMNMT as a novel music therapy for tinnitus. The observed stronger residual inhibition (RI) ability of TMNMT supported its potential applications in tinnitus treatment. Furthermore, the temporal dynamics of EEG microstates serve as novel functional and trait markers of synchronous brain activity that contribute to a deep understanding of the neural mechanism underlying TMNMT treatment for tinnitus.

Cardiorespiratory fitness modulates prestimulus EEG microstates during a sustained attention task

Higher cardiorespiratory fitness is associated with an increased ability to perform sustained attention tasks and detect rare and unpredictable signals over prolonged periods. The electrocortical dynamics underlying this relationship were mainly investigated after visual stimulus onset in sustained attention tasks. Prestimulus electrocortical activity supporting differences in sustained attention performance according to the level of cardiorespiratory fitness have yet to be examined. Consequently, this study aimed to investigate EEG microstates 2 seconds before the stimulus onset in 65 healthy individuals aged 18-37, differing in cardiorespiratory fitness, while performing a psychomotor vigilance task. The analyses showed that a lower duration of the microstate A and a higher occurrence of the microstate D correlated with higher cardiorespiratory fitness in the prestimulus periods. In addition, increased global field power and occurrence of microstate A were associated with slower response times in the psychomotor vigilance task, while greater global explained variance, coverage, and occurrence of microstate D were linked to faster response times. Our collective findings showed that individuals with higher cardiorespiratory fitness exhibit typical electrocortical dynamics that allow them to allocate their attentional resources more efficiently when engaged in sustained attention tasks.

Spontaneous Necker-cube reversals may not be that spontaneous

Introduction

During observation of the ambiguous Necker cube, our perception suddenly reverses between two about equally possible 3D interpretations. During passive observation, perceptual reversals seem to be sudden and spontaneous. A number of theoretical approaches postulate destabilization of neural representations as a pre-condition for reversals of ambiguous figures. In the current study, we focused on possible Electroencephalogram (EEG) correlates of perceptual destabilization, that may allow prediction of an upcoming perceptual reversal.

Methods

We presented ambiguous Necker cube stimuli in an onset-paradigm and investigated the neural processes underlying endogenous reversals as compared to perceptual stability across two consecutive stimulus presentations. In a separate experimental condition, disambiguated cube variants were alternated randomly, to exogenously induce perceptual reversals. We compared the EEG immediately before and during endogenous Necker cube reversals with corresponding time windows during exogenously induced perceptual reversals of disambiguated cube variants.

Results

For the ambiguous Necker cube stimuli, we found the earliest differences in the EEG between reversal trials and stability trials already 1 s before a reversal occurred, at bilateral parietal electrodes. The traces remained similar until approximately 1100 ms before a perceived reversal, became maximally different at around 890 ms (p = 7.59 × 10^-6, Cohen's d = 1.35) and remained different until shortly before offset of the stimulus preceding the reversal. No such patterns were found in the case of disambiguated cube variants.

Discussion

The identified EEG effects may reflect destabilized states of neural representations, related to destabilized perceptual states preceding a perceptual reversal. They further indicate that spontaneous Necker cube reversals are most probably not as spontaneous as generally thought. Rather, the destabilization may occur over a longer time scale, at least 1 s before a reversal event, despite the reversal event as such being perceived as spontaneous by the viewer.

Conscious interpretation: A distinct aspect for the neural markers of the contents of consciousness

Progress in the science of consciousness depends on the experimental paradigms and varieties of contrastive analysis available to researchers. Here we highlight paradigms where the object is represented in consciousness as a set of its features but the interpretation of this set alternates in consciousness. We group experimental paradigms with this property under the label "conscious interpretation". We compare the paradigms studying conscious interpretation of the already consciously perceived objects with other types of experimental paradigms. We review previous and recent studies investigating this interpretative aspect of consciousness and propose future directions. We put forward the hypothesis that there are types of stimuli with a hierarchy of interpretations for which the rule applies: conscious experience is drawn towards higher-level interpretation and reverting back to the lower level of interpretation is impossible. We discuss how theories of consciousness might incorporate knowledge and constraints arising from the characteristics of conscious interpretation.

Spontaneous neuronal avalanches as a correlate of access consciousness

Decades of research have advanced our understanding of the biophysical mechanisms underlying consciousness. However, an overarching framework bridging between models of consciousness and the large-scale organization of spontaneous brain activity is still missing. Based on the observation that spontaneous brain activity dynamically switches between epochs of segregation and large-scale integration of information, we hypothesize a brain-state dependence of conscious access, whereby the presence of either segregated or integrated states marks distinct modes of information processing. We first review influential works on the neuronal correlates of consciousness, spontaneous resting-state brain activity and dynamical system theory. Then, we propose a test experiment to validate our hypothesis that conscious access occurs in aperiodic cycles, alternating windows where new incoming information is collected but not experienced, to punctuated short-lived integration events, where conscious access to previously collected content occurs. In particular, we suggest that the integration events correspond to neuronal avalanches, which are collective bursts of neuronal activity ubiquitously observed in electrophysiological recordings. If confirmed, the proposed framework would link the physics of spontaneous cortical dynamics, to the concept of ignition within the global neuronal workspace theory, whereby conscious access manifest itself as a burst of neuronal activity.

Change not State: Perceptual coupling in multistable displays reflects transient bias induced by perceptual change

We investigated how changes in dynamic spatial context influence visual perception. Specifically, we reexamined the perceptual coupling phenomenon when two multistable displays viewed simultaneously tend to be in the same dominant state and switch in accord. Current models assume this interaction reflecting mutual bias produced by a dominant perceptual state. In contrast, we demonstrate that influence of spatial context is strongest when perception changes. First, we replicated earlier work using bistable kinetic-depth effect displays, then extended it by employing asynchronous presentation to show that perceptual coupling cannot be accounted for by the static context provided by perceptually dominant states. Next, we demonstrated that perceptual coupling reflects transient bias induced by perceptual change, both in ambiguous and disambiguated displays. We used a hierarchical Bayesian model to characterize its timing, demonstrating that the transient bias is induced 50-70 ms after the exogenous trigger event and decays within ~200-300 ms. Both endogenous and exogenous switches led to quantitatively and qualitatively similar perceptual consequences, activating similar perceptual reevaluation mechanisms within a spatial surround. We explain how they can be understood within a transient selective visual attention framework or using local lateral connections within sensory representations. We suggest that observed perceptual effects reflect general mechanisms of perceptual inference for dynamic visual scene perception.

Bi-Stable Perception: Self-Coordinating Brain Regions to Make-Up the Mind

Bi-stable perception is a strong instance of cognitive self-organization, providing a research model for how ‘the brain makes up its mind.’ The complexity of perceptual bistability prevents a simple attribution of functions to areas, because many cognitive processes, recruiting multiple brain regions, are simultaneously involved. The functional magnetic resonance imaging (fMRI) evidence suggests the activation of a large network of distant brain areas. Concurrently, electroencephalographic and magnetoencephalographic (MEEG) literature shows sub second oscillatory activity and phase synchrony on several frequency bands. Strongly represented are beta and gamma bands, often associated with neural/cognitive integration processes. The spatial extension and short duration of brain activities suggests the need for a fast, large-scale neural coordination mechanism. To address the range of temporo-spatial scales involved, we systematize the current knowledge from mathematical models, cognitive sciences and neuroscience at large, from single-cell- to system-level research, including evidence from human and non-human primates. Surprisingly, despite evidence spanning through different organization levels, models, and experimental approaches, the scarcity of integrative studies is evident. In a final section of the review we dwell on the reasons behind such scarcity and on the need of integration in order to achieve a real understanding of the complexities underlying bi-stable perception processes.

Acute alcohol intoxication modulates the temporal dynamics of resting electroencephalography networks

This study aimed to provide a currently missing link between general intoxication-induced changes in overall brain activity and the multiple cognitive control deficits typically observed during acute alcohol intoxication. For that purpose, we analyzed the effects of acute alcohol intoxication (1.1‰) on the four archetypal electroencephalography (EEG) resting networks (i.e., microstates A-D) and their temporal dynamics (e.g., coverage and transitions from one microstate to another), as well as on self-reported resting-state cognition in n = 22 healthy young males using a counterbalanced within-subject design. Our microstate analyses indicated that alcohol increased the coverage of the visual processing-related microstate B at the expense of the autonomic processing-related microstate C. Add-on exploratory analyses revealed that alcohol increased transitions from microstate C to microstate B and decreased bidirectional transitions between microstate C and the attention-related microstate D. In line with the observed alcohol-induced decrease of the autonomic processing-related microstate C, participants reported decreases of their somatic awareness during intoxication, which were positively associated with more transitions from microstate C to microstate B. In sum, the observed effects provide mechanistic insights into how alcohol might hamper cognitive processing by generally prioritizing the bottom-up processing of visual stimuli over top-down internal information processing. The fact that this was found during the resting state further proves that alcohol-induced changes in brain activity are continuously present and do not only emerge during demanding situations or tasks.

Long-term priors influence visual perception through recruitment of long-range feedback

Perception results from the interplay of sensory input and prior knowledge. Despite behavioral evidence that long-term priors powerfully shape perception, the neural mechanisms underlying these interactions remain poorly understood. We obtained direct cortical recordings in neurosurgical patients as they viewed ambiguous images that elicit constant perceptual switching. We observe top-down influences from the temporal to occipital cortex, during the preferred percept that is congruent with the long-term prior. By contrast, stronger feedforward drive is observed during the non-preferred percept, consistent with a prediction error signal. A computational model based on hierarchical predictive coding and attractor networks reproduces all key experimental findings. These results suggest a pattern of large-scale information flow change underlying long-term priors' influence on perception and provide constraints on theories about long-term priors' influence on perception.

Early visual processing relevant to the reduction of adaptation-induced perceptual bias

Visual perception is biased by the preceding visual environment. A well-known perceptual bias is the negative bias where a current percept is biased away from the preceding image (adaptor). The preceding adaptor induces augmentation of early visual evoked potential (the P1 enhancement) of the following test image; the adaptor may invoke certain visual processing for the subsequent test image. However, the visual mechanism underlying P1 enhancement remains unclear. The present study assessed what the P1 alteration reflects in relation to the occurrence of the negative bias. In terms of inter-individual differences, we report that the P1 enhancement of the Necker lattice significantly correlated with the reduction of the reverse-bias effect. Further analyses revealed that the P1 enhancement was insusceptible to neural adaptation to the adaptor at the level of perceptual configuration. The present study suggests that prolonged exposure to a visual image induces modulatory visual processing for the subsequent image (reflected in the P1 enhancement), which is relevant to counteraction of the negative bias.

Neural correlates of nonjudgmental perception induced through meditation

Ambiguous sensory stimuli provide insight into the dynamics of the human mind. When viewing substantially different images in the two eyes (i.e., binocular rivalry (BR)), perception spontaneously fluctuates between the two images along with patch-like mixtures of the two, with limited ability to control such fluctuations. Previous studies have shown that long-term meditation training can enable a more stable perception by reducing such fluctuations. Using electroencephalography, we investigated the neural bases of perceptual stabilization in long-term meditators (LTMs) and age-matched meditation-naive control participants. We measured BR alternations before and after participants practiced meditation. We expected that perceptual stabilization through meditation could occur via one of two neurocognitive mechanisms: (1) a more engaged/effortful attention reflected by increased long-range phase synchronization between early visual sensory and higher-level brain regions, or (2) a disengaged/nonevaluative form of attention reflected by decreased phase synchronization. We found that compared with control participants, LTMs were in a significantly longer mixed perceptual state following concentrative meditation practice. The increase in mixed percepts across individuals was strongly correlated with reduced parietal-occipital gamma-band (30-50 Hz) phase synchrony. These findings suggest that concentrative meditation enables a nonevaluative perceptual stance supported by reduced communication between hierarchical visual brain regions.

Relationship between Dynamic Blood-Oxygen-Level-Dependent Activity and Functional Network Connectivity: Characterization of Schizophrenia Subgroups

Aim: In this work, we propose the novel use of adaptively constrained independent vector analysis (acIVA) to effectively capture the temporal and spatial properties of dynamic blood-oxygen-level-dependent (BOLD) activity (dBA), and we efficiently quantify the spatial property of dBA (sdBA). We also propose to incorporate dBA into the study of brain dynamics to gain insight into activity-connectivity co-evolution patterns. Introduction: Studies of the dynamics of the human brain using functional magnetic resonance imaging (fMRI) have enabled the identification of unique functional network connectivity (FNC) states and provided new insights into mental disorders. There is evidence showing that both BOLD activity, which is captured by fMRI, and FNC are related to mental and cognitive processes. However, a few studies have evaluated the inter-relationships of these two domains of function. Moreover, the identification of subgroups of schizophrenia has gained significant clinical importance due to a need to study the heterogeneity of schizophrenia. Methods: We design a simulation study to verify the effectiveness of acIVA and apply acIVA to the dynamic study of resting-state fMRI data collected from individuals with schizophrenia and healthy controls (HCs) to investigate the relationship between dBA and dynamic FNC (dFNC). Results: The simulation study demonstrates that acIVA accurately captures the spatial variability and provides an efficient quantification of sdBA. The fMRI analysis yields synchronized sdBA-temporal property of dBA (tdBA) patterns and shows that the dBA and dFNC are significantly correlated in the spatial domain. Using these dynamic features, we identify schizophrenia subgroups with significant differences in terms of their clinical symptoms. Conclusion: We find that brain function is abnormally organized in schizophrenia compared with HCs since there are less synchronized sdBA-tdBA patterns in schizophrenia and schizophrenia prefers a component that merges multiple brain regions. Identification of schizophrenia subgroups using dynamic features inspires the use of neuroimaging in studying the heterogeneity of disorders. Impact statement This work introduces the use of joint blind source separation for the study of brain dynamics to enable efficient quantification of the spatial property of dynamic blood-oxygen-level-dependent (BOLD) activity to provide insight into the relationship of dynamic BOLD activity and dynamic functional network connectivity. The identification of subgroups of schizophrenia using dynamic features allows the study of heterogeneity of schizophrenia, emphasizing the importance of functional magnetic resonance imaging analysis in the study of brain activity and functional connectivity to gain a better understanding of the human brain, especially the brain with a mental disorder.

The metastable brain associated with autistic-like traits of typically developing individuals

Metastability in the brain is thought to be a mechanism involved in the dynamic organization of cognitive and behavioral functions across multiple spatiotemporal scales. However, it is not clear how such organization is realized in underlying neural oscillations in a high-dimensional state space. It was shown that macroscopic oscillations often form phase-phase coupling (PPC) and phase-amplitude coupling (PAC), which result in synchronization and amplitude modulation, respectively, even without external stimuli. These oscillations can also make spontaneous transitions across synchronous states at rest. Using resting-state electroencephalographic signals and the autism-spectrum quotient scores acquired from healthy humans, we show experimental evidence that the PAC combined with PPC allows amplitude modulation to be transient, and that the metastable dynamics with this transient modulation is associated with autistic-like traits. In individuals with a longer attention span, such dynamics tended to show fewer transitions between states by forming delta-alpha PAC. We identified these states as two-dimensional metastable states that could share consistent patterns across individuals. Our findings suggest that the human brain dynamically organizes inter-individual differences in a hierarchy of macroscopic oscillations with multiple timescales by utilizing metastability.

The human brain organizes cognitive and behavioral functions dynamically. For decades, the dynamic organization of underlying neural oscillations has been a fundamental topic in neuroscience research. Even without external stimuli, macroscopic oscillations often form phase-phase coupling and phase-amplitude coupling (PAC) that result in synchronization and amplitude modulation, respectively, and can make spontaneous transitions across synchronous states at rest. Using resting-state electroencephalography signals acquired from healthy humans, we show evidence that these two neural couplings enable amplitude modulation to be transient, and that this transient modulation can be viewed as the transition among oscillatory states with different PAC strengths. We also demonstrate that such transition dynamics are associated with the ability to maintain attention to detail and to switch attention, as measured by autism-spectrum quotient scores. These individual dynamics were visualized as a trajectory among states with attracting tendencies, and involved consistent brain states across individuals. Our findings have significant implications for unraveling the variability in the individual brains showing typical and atypical development.

Alteration in Resting-State EEG Microstates Following 24 Hours of Total Sleep Deprivation in Healthy Young Male Subjects

Purpose: The cognitive effects of total sleep deprivation (TSD) on the brain remain poorly understood. Electroencephalography (EEG) is a very useful tool for detecting spontaneous brain activity in the resting state. Quasi-stable electrical distributions, known as microstates, carry useful information about the dynamics of large-scale brain networks. In this study, microstate analysis was used to study changes in brain activity after 24 h of total sleep deprivation.

Participants and Methods: Twenty-seven healthy volunteers were recruited and underwent EEG scans before and after 24 h of TSD. Microstate analysis was applied, and six microstate classes (A–F) were identified. Topographies and temporal parameters of the microstates were compared between the rested wakefulness (RW) and TSD conditions.

Results: Microstate class A (a right-anterior to left-posterior orientation of the mapped field) showed lower global explained variance (GEV), frequency of occurrence, and time coverage in TSD than RW, whereas microstate class D (a fronto-central extreme location of the mapped field) displayed higher GEV, frequency of occurrence, and time coverage in TSD compared to RW. Moreover, subjective sleepiness was significantly negatively correlated with the microstate parameters of class A and positively correlated with the microstate parameters of class D. Transition analysis revealed that class B exhibited a higher probability of transition than did classes D and F in TSD compared to RW.

Conclusion: The observation suggests alterations of the dynamic brain-state properties of TSD in healthy young male subjects, which may serve as system-level neural underpinnings for cognitive declines in sleep-deprived subjects.

In your phase: neural phase synchronisation underlies visual imagery of faces

Mental imagery is the process through which we retrieve and recombine information from our memory to elicit the subjective impression of “seeing with the mind’s eye”. In the social domain, we imagine other individuals while recalling our encounters with them or modelling alternative social interactions in future. Many studies using imaging and neurophysiological techniques have shown several similarities in brain activity between visual imagery and visual perception, and have identified frontoparietal, occipital and temporal neural components of visual imagery. However, the neural connectivity between these regions during visual imagery of socially relevant stimuli has not been studied. Here we used electroencephalography to investigate neural connectivity and its dynamics between frontal, parietal, occipital and temporal electrodes during visual imagery of faces. We found that voluntary visual imagery of faces is associated with long-range phase synchronisation in the gamma frequency range between frontoparietal electrode pairs and between occipitoparietal electrode pairs. In contrast, no effect of imagery was observed in the connectivity between occipitotemporal electrode pairs. Gamma range synchronisation between occipitoparietal electrode pairs predicted subjective ratings of the contour definition of imagined faces. Furthermore, we found that visual imagery of faces is associated with an increase of short-range frontal synchronisation in the theta frequency range, which temporally preceded the long-range increase in the gamma synchronisation. We speculate that the local frontal synchrony in the theta frequency range might be associated with an effortful top-down mnemonic reactivation of faces. In contrast, the long-range connectivity in the gamma frequency range along the fronto-parieto-occipital axis might be related to the endogenous binding and subjective clarity of facial visual features.

Noisy network attractor models for transitions between EEG microstates

The brain is intrinsically organized into large-scale networks that constantly re-organize on multiple timescales, even when the brain is at rest. The timing of these dynamics is crucial for sensation, perception, cognition, and ultimately consciousness, but the underlying dynamics governing the constant reorganization and switching between networks are not yet well understood. Electroencephalogram (EEG) microstates are brief periods of stable scalp topography that have been identified as the electrophysiological correlate of functional magnetic resonance imaging defined resting-state networks. Spatiotemporal microstate sequences maintain high temporal resolution and have been shown to be scale-free with long-range temporal correlations. Previous attempts to model EEG microstate sequences have failed to capture this crucial property and so cannot fully capture the dynamics; this paper answers the call for more sophisticated modeling approaches. We present a dynamical model that exhibits a noisy network attractor between nodes that represent the microstates. Using an excitable network between four nodes, we can reproduce the transition probabilities between microstates but not the heavy tailed residence time distributions. We present two extensions to this model: first, an additional hidden node at each state; second, an additional layer that controls the switching frequency in the original network. Introducing either extension to the network gives the flexibility to capture these heavy tails. We compare the model generated sequences to microstate sequences from EEG data collected from healthy subjects at rest. For the first extension, we show that the hidden nodes 'trap' the trajectories allowing the control of residence times at each node. For the second extension, we show that two nodes in the controlling layer are sufficient to model the long residence times. Finally, we show that in addition to capturing the residence time distributions and transition probabilities of the sequences, these two models capture additional properties of the sequences including having interspersed long and short residence times and long range temporal correlations in line with the data as measured by the Hurst exponent.

Psychotic disorders, dopaminergic agents and EEG/MEG resting-state functional connectivity: A systematic review

Both dysconnectivity and dopamine hypotheses are two well researched pathophysiological models of psychosis. However, little is known about the association of dopamine dysregulation with brain functional connectivity in psychotic disorders, specifically through the administration of antipsychotic medication. In this systematic review, we summarize the existing evidence on the association of dopaminergic effects with electro- and magnetoencephalographic (EEG/MEG) resting-state brain functional connectivity assessed by sensor- as well as source-level measures. A wide heterogeneity of results was found amongst the 20 included studies with increased and decreased functional connectivity in medicated psychosis patients vs. healthy controls in widespread brain areas across all frequency bands. No systematic difference in results was seen between studies with medicated and those with unmedicated psychosis patients and very few studies directly investigated the effect of dopamine agents with a pre-post design. The reported evidence clearly calls for longitudinal EEG and MEG studies with large participant samples to directly explore the association of antipsychotic medication effects with neural network changes over time during illness progression and to ultimately support the development of new treatment strategies.

Self-reported Mind Wandering and Response Time Variability Differentiate Prestimulus Electroencephalogram Microstate Dynamics during a Sustained Attention Task

Brain activity continuously and spontaneously fluctuates during tasks of sustained attention. This spontaneous activity reflects the intrinsic dynamics of neurocognitive networks, which have been suggested to differentiate moments of externally directed task focus from episodes of mind wandering. However, the contribution of specific electrophysiological brain states and their millisecond dynamics to the experience of mind wandering is still unclear. In this study, we investigated the association between electroencephalogram microstate temporal dynamics and self-reported mind wandering. Thirty-six participants completed a sustained attention to response task in which they were asked to respond to frequently occurring upright faces (nontargets) and withhold responses to rare inverted faces (targets). Intermittently, experience sampling probes assessed whether participants were focused on the task or whether they were mind wandering (i.e., off-task). Broadband electroencephalography was recorded and segmented into a time series of brain electric microstates based on data-driven clustering of topographic voltage patterns. The strength, prevalence, and rate of occurrence of specific microstates differentiated on- versus off-task moments in the prestimulus epochs of trials preceding probes. Similar associations were also evident between microstates and variability in response times. Together, these findings demonstrate that distinct microstates and their millisecond dynamics are sensitive to the experience of mind wandering.

Response dependence of reversal-related ERP components in perception of ambiguous figures

Perceptual multi-stability is characterized by alternating interpretations of an unchanging stimulus input. The reversal negativity (RN) and reversal positivity (RP) ERP components show differences in electrophysiological responses between trials on which participants experience a perceptual reversal of a multi-stable stimulus versus trials without a reversal (i.e., stable). However, it is unclear to what extent these two ERP components reflect reversal-related perceptual processing rather than task and response processes. To address this, we varied task and response requirements while measuring the RN and RP. In the standard reversal task, participants indicated whether they saw a perceptual reversal on each trial. In contrast, in the identity task participants reported perceived identity of the stimulus (e.g., face or vase) without any reference to reversals. In some blocks, reversal trials required a response whereas in other blocks stable trials required a response. We found that the RN appeared independently of task and response style. However, the early latency RP component was only present when participants responded manually. For non-response trials, a component was found during the same latency as the RP but with inverted polarity. Our results suggest that the early RP component is dependent on response-related processes rather than being a pure neural signature of perceptual processes related to endogenous perceptual reversals.

Neuromodulation Management of Chronic Neuropathic Pain in The Central Nervous system

Neuromodulation is becoming one of the clinical tools for treating chronic neuropathic pain by transmitting controlled physical energy to the pre-identified neural targets in the central nervous system. Its nature of drug-free, non-addictive and improved targeting have attracted increasing attention among neuroscience research and clinical practices. This article provides a brief overview of the neuropathic pain and pharmacological routines for treatment, summarizes both the invasive and non-invasive neuromodulation modalities for pain management, and highlights an emerging brain stimulation technology, transcranial focused ultrasound (tFUS) with a focus on ultrasound transducer devices and the achieved neuromodulation effects and applications on pain management. Practical considerations of spatial guidance for tFUS are discussed for clinical applications. The safety of transcranial ultrasound neuromodulation and its future prospectives on pain management are also discussed.

Age-related changes in the association of resting-state fMRI signal variability and global functional connectivity in non-demented healthy people

Research suggests that the aging relates to variability of resting-state fMRI (rs-fMRI) signal and the functional connectivity. However, the association between the spatial and temporal activity of resting-state fMRI signal was less documented. We recruited 477 healthy Han Chinese participants, who were separated into young, middle and old groups to investigate the relationship between the variability and global functional connectivity (gFC) in different age ranges using standard deviation (SD) of time series and gFC, respectively. Our analysis revealed the changing patterns during healthy aging: 1) 17 brain regions(Olfactory_L, Orbital_L etc.) were identified to have significant association of age with both SD and gFC respectively by linear regression analysis; 2) Two typical associations could be observed between SD and gFC: positive and negative correlations; 3) The variation ratio of SD to gFC was changing with age at the voxel level by using unsupervised clustering method. It is the first time to combine voxel-wise variability and gFC together for the study of age-related changes with rs-fMRI signal. This study may provide a new clue for understanding the synchronization of human brain based on SD and gFC due to the effect of aging.

Temporal dynamics of resting EEG networks are associated with prosociality

As prosociality is key to facing many of our societies' global challenges (such as fighting a global pandemic), we need to better understand why some individuals are more prosocial than others. The present study takes a neural trait approach, examining whether the temporal dynamics of resting EEG networks are associated with inter-individual differences in prosociality. In two experimental sessions, we collected 55 healthy males' resting EEG, their self-reported prosocial concern and values, and their incentivized prosocial behavior across different reward domains (money, time) and social contexts (collective, individual). By means of EEG microstate analysis we identified the temporal coverage of four canonical resting networks (microstates A, B, C, and D) and their mutual communication in order to examine their association with an aggregated index of prosociality. Participants with a higher coverage of microstate A and more transitions from microstate C to A were more prosocial. Our study demonstrates that temporal dynamics of intrinsic brain networks can be linked to complex social behavior. On the basis of previous findings on links of microstate A with sensory processing, our findings suggest that participants with a tendency to engage in bottom-up processing during rest behave more prosocially than others.

Temporal dynamics of the flash-induced bouncing effect

Two identical visual disks moving toward each other on a two‐dimensional (2D) display are more likely to be perceived as “streaming through” than “bouncing off” each other after their coincidence. However, either a brief auditory tone or visual flash presented at the coincident moment of the disks can strikingly increase the incidence of the bouncing percept. Despite the neural substrates underlying the sound‐induced bouncing effect have been widely investigated, little is known about the neural mechanisms underlying the flash‐induced bouncing effect. The present study used event‐related potential recordings to explore the temporal dynamics of the flash‐induced bouncing effect. The results showed that the amplitude of the postcoincidence parietooccipital P2 component (190–230 ms after coincidence) elicited by the visual motion was significantly smaller on bouncing relative to streaming trials only when the flash was presented but not when absent. In addition, the parietal P3 component (330–430 ms) was found to be larger on bouncing than streaming trials when the flash was presented, but the opposite was true when no flash was presented. These electrophysiological findings suggest that the flash‐induced bouncing effect may occur at both perceptual and postperceptual stages of processing.

Disrupted brain network dynamics and cognitive functions in methamphetamine use disorder: insights from EEG microstates

BACKGROUND

Dysfunction in brain network dynamics has been found to correlate with many psychiatric disorders. However, there is limited research regarding resting electroencephalogram (EEG) brain network and its association with cognitive process for patients with methamphetamine use disorder (MUD). This study aimed at using EEG microstate analysis to determine whether brain network dynamics in patients with MUD differ from those of healthy controls (HC).

METHODS

A total of 55 MUD patients and 27 matched healthy controls were included for analysis. The resting brain activity was recorded by 64-channel electroencephalography. EEG microstate parameters and intracerebral current sources of each EEG microstate were compared between the two groups. Generalized linear regression model was used to explore the correlation between significant microstates with drug history and cognitive functions.

RESULTS

MUD patients showed lower mean durations of the microstate classes A and B, and a higher global explained variance of the microstate class C. Besides, MUD patients presented with different current density power in microstates A, B, and C relative to the HC. The generalized linear model showed that MA use frequency is negatively correlated with the MMD of class A. Further, the generalized linear model showed that MA use frequency, scores of Two-back task, and the error rate of MA word are correlated with the MMD and GEV of class B, respectively.

CONCLUSIONS

Intracranial current source densities of resting EEG microstates are disrupted in MUD patients, hence causing temporal changes in microstate topographies, which are correlated with attention bias and history of drug use.

Pre-stimulus EEG Microstates Correlate With Anticipatory Alpha Desynchronization

In the last decades, several electrophysiological markers have been investigated to better understand how humans precede a signaled event. Among others, the pre-stimulus microstates’ topography, representing the whole brain activity, has been proposed as a promising index of the anticipatory period in several cognitive tasks. However, to date, a clear relationship between the metrics of the pre-stimulus microstates [i.e., the global explained variance (GEV) and the frequency of occurrence (FOO)] and well-known electroencephalography marker of the anticipation (i.e., the alpha power reduction) has not been investigated. Here, after extracting the microstates during the expectancy of the semantic memory task, we investigate the correlations between the microstate features and the anticipatory alpha (8–12 Hz) power reduction (i.e., the event-related de-synchronization of the alpha rhythms; ERD) that is widely interpreted as a functional correlate of brain activation. We report a positive correlation between the occurrence of the dominant, but not non-dominant, microstate and both the mean amplitude of high-alpha ERD and the magnitude of the alpha ERD peak so that the stronger the decrease (percentage) in the alpha power, the higher the FOO of the dominant microstate. Moreover, we find a positive correlation between the occurrence of the dominant microstate and the latency of the alpha ERD peak, suggesting that subjects with higher FOO present the stronger alpha ERD closely to the target. These correlations are not significant between the GEV and all anticipatory alpha ERD indices. Our results suggest that only the occurrence of the dominant, but not non-dominant, microstate should be considered as a useful electrophysiological correlate of the cortical activation.

EEG microstates are correlated with brain functional networks during slow-wave sleep

Electroencephalography (EEG) microstates have been extensively studied in wakefulness and have been described as the "atoms of thought". Previous studies of EEG have found four microstates, i.e., microstates A, B, C and D, that are consistent among participants across the lifespan during the resting state. Studies using simultaneous EEG and functional magnetic resonance imaging (fMRI) have provided evidence for correlations between EEG microstates and fMRI networks during the resting state. Microstates have also been found during non-rapid eye movement (NREM) sleep. Slow-wave sleep (SWS) is considered the most restorative sleep stage and has been associated with the maintenance of sleep. However, the relationship between EEG microstates and brain functional networks during SWS has not yet been investigated. In this study, simultaneous EEG-fMRI data were collected during SWS to test the correspondence between EEG microstates and fMRI networks. EEG microstate-informed fMRI analysis revealed that three out of the four microstates showed significant correlations with fMRI data: 1) fMRI fluctuations in the insula and posterior temporal gyrus positively correlated with microstate B, 2) fMRI signals in the middle temporal gyrus and fusiform gyrus negatively correlated with microstate C, and 3) fMRI fluctuations in the occipital lobe negatively correlated with microstate D, while fMRI signals in the anterior cingulate and cingulate gyrus positively correlated with this microstate. Functional brain networks were then assessed using group independent component analysis based on the fMRI data. The group-level spatial correlation analysis showed that the fMRI auditory network overlapped the fMRI activation map of microstate B, the executive control network overlapped the fMRI deactivation of microstate C, and the visual and salience networks overlapped the fMRI deactivation and activation maps of microstate D. In addition, the subject-level spatial correlations between the general linear model (GLM) beta map of each microstate and the individual maps of each component yielded by dual regression also showed that EEG microstates were closely associated with brain functional networks measured using fMRI during SWS. Overall, the results showed that EEG microstates were closely related to brain functional networks during SWS, which suggested that EEG microstates provide an important electrophysiological basis underlying brain functional networks.

Ensemble modeling of auditory streaming reveals potential sources of bistability across the perceptual hierarchy

Perceptual bistability-the spontaneous, irregular fluctuation of perception between two interpretations of a stimulus-occurs when observing a large variety of ambiguous stimulus configurations. This phenomenon has the potential to serve as a tool for, among other things, understanding how function varies across individuals due to the large individual differences that manifest during perceptual bistability. Yet it remains difficult to interpret the functional processes at work, without knowing where bistability arises during perception. In this study we explore the hypothesis that bistability originates from multiple sources distributed across the perceptual hierarchy. We develop a hierarchical model of auditory processing comprised of three distinct levels: a Peripheral, tonotopic analysis, a Central analysis computing features found more centrally in the auditory system, and an Object analysis, where sounds are segmented into different streams. We model bistable perception within this system by applying adaptation, inhibition and noise into one or all of the three levels of the hierarchy. We evaluate a large ensemble of variations of this hierarchical model, where each model has a different configuration of adaptation, inhibition and noise. This approach avoids the assumption that a single configuration must be invoked to explain the data. Each model is evaluated based on its ability to replicate two hallmarks of bistability during auditory streaming: the selectivity of bistability to specific stimulus configurations, and the characteristic log-normal pattern of perceptual switches. Consistent with a distributed origin, a broad range of model parameters across this hierarchy lead to a plausible form of perceptual bistability.

Everything is subjective under water surface, too: visual illusions in fish

The study of visual illusions has captured the attention of comparative psychologists since the last century, given the unquestionable advantage of investigating complex perceptual mechanisms with relatively simple visual patterns. To date, the observation of animal behavior in the presence of visual illusions has been largely confined to mammal and bird studies. Recently, there has been increasing interest in investigating fish, too. The attention has been particularly focused on guppies, redtail splitfin and bamboo sharks. Overall, the tested species were shown to experience a human-like perception of different illusory phenomena involving size, number, motion, brightness estimation and illusory contours. However, in some cases, no illusory effects, or evidence for a reverse illusion, were also reported. Here, we review the current state of the art in this field. We conclude that a wider investigation of visual illusions in fish is fundamental to form a broader comprehension of perceptual systems of vertebrates. Furthermore, we believe that this type of investigation could help us to address general important issues in perceptual studies, such as the role of ecology in shaping perceptual systems, the existence of interindividual variability in the visual perception of nonhuman species and the role of cortical activity in the emergence of visual illusions.

Parietal tACS at beta frequency improves vision in a crowding regime

Visual crowding is the inability to discriminate objects when presented with nearby flankers and sets a fundamental limit for conscious perception. Beta oscillations in the parietal cortex were found to be associated to crowding, with higher beta amplitude related to better crowding resilience. An open question is whether beta activity directly and selectively modulates crowding. We employed Transcranial Alternating Current Stimulation (tACS) in the beta band (18-Hz), in the alpha band (10-Hz) or in a sham regime, asking whether 18-Hz tACS would selectively improve the perception of crowded stimuli by increasing parietal beta activity. Resting-state electroencephalography (EEG) was measured before and after stimulation to test the influence of tACS on endogenous oscillations. Consistently with our predictions, we found that 18-Hz tACS, as compared to 10-Hz tACS and sham stimulation, reduced crowding. This improvement was found specifically in the contralateral visual hemifield and was accompanied by an increased amplitude of EEG beta oscillations, confirming an effect on endogenous brain rhythms. These results support a causal relationship between parietal beta oscillations and visual crowding and provide new insights into the precise oscillatory mechanisms involved in human vision.

Assessing Field Dependence-Independence Cognitive Abilities Through EEG-Based Bistable Perception Processing

Field Dependence–Independence (FDI) is a widely studied dimension of cognitive styles designed to measure an individual’s ability to identify embedded parts of an organized visual field as entities separate from that given field. The research aims to determine whether the brain activity features that are considered to be perceptual switching indicators could serve as robust features, differentiating Field-Dependent (FD) from Field-Independent (FI) participants. Previous research suggests that various features derived from event related potentials (ERP) and frequency features are associated with the perceptual reversal occurring during the observation of a bistable image. In this study, we combined these features in the context of a different experimental scheme using ambiguous and unambiguous stimuli during participants’ perceptual observations. We assessed the participants’ FD-I classification with the use of the Hidden Figures Test (HFT). Results show that the peak amplitude of the frontoparietal positivity, the late positive deflection in frontal and parietal areas, is higher for the FD group at specific locations of the left lobe, whereas it occurs later for the FD group at the central and occipital electrodes. Additionally, the FD group exhibits higher levels of gamma power before stimulus onset at channel TP10 and higher gamma power during reversal at the right centroparietal electrodes (T8, CP6, and TP10). The peak amplitude of the reversal positivity, the positive deflection during the reversal, is higher for the FD group at the rear right lobe (P4).

What happens in the brain of meditators when perception changes but not the stimulus?

During the observation of an ambiguous figure our perception alternates between mutually exclusive interpretations, although the stimulus itself remains unchanged. The rate of these endogenous reversals has been discussed as reflecting basic aspects of endogenous brain dynamics. Recent evidence indicates that extensive meditation practice evokes long-term functional and anatomic changes in the brain, also affecting the endogenous brain dynamics. As one of several consequences the rate of perceptual reversals during ambiguous figure perception decreases. In the present study we compared EEG-correlates of endogenous reversals of ambiguous figures between meditators and non-meditating controls in order to better understand timing and brain locations of this altered endogenous brain dynamics. A well-established EEG paradigm was used to measure the neural processes underlying endogenous perceptual reversals of ambiguous figures with high temporal precision. We compared reversal-related ERPs between experienced meditators and non-meditating controls. For both groups we found highly similar chains of reversal-related ERPs, starting early in visual areas, therewith replicating previous findings from the literature. Meditators, however, showed an additional frontal ERP signature already 160 ms after stimulus onset (Frontal Negativity). We interpret the additional, meditation-specific ERP results as evidence that extensive meditation practice provides control of frontal brain areas over early sensory processing steps. This may allow meditators to overcome phylogenetically evolved perceptual and attentional processing automatisms.

Oxytocin modulates the temporal dynamics of resting EEG networks

Oxytocin is a key modulator of social interaction, but we possess little knowledge of its underlying effects on neuropsychological processes. We used a spatio-temporal EEG microstates analysis to reveal oxytocin's effects on the temporal dynamics of intrinsically generated activity in neural networks. Given oxytocin's known anxiolytic effects, we hypothesized that it increases the temporal stability of the four archetypal EEG resting networks. Eighty-six male participants had received oxytocin or placebo intranasally before we recorded their resting EEG. As hypothesized, oxytocin globally increased the average duration of the four archetypal resting networks and specifically decreased the occurrence and coverage of an autonomic processing-related network to benefit greater coverage of an attention-related network. Moreover, these neurophysiological changes were more pronounced in participants with high anxiety levels and strong subjectively experienced effects of the oxytocin administration. In sum, our study shows that oxytocin reduces rapid switching among neural resting networks by increasing their temporal stability. Specifically, it seems to reduce the brain's need for preparing the internally-oriented processing of autonomic information, thus enabling the externally-oriented processing of social information. Changes in the temporal dynamics of resting networks might underlie oxytocin's anxiolytic effects - potentially informing innovative psychobiological treatment strategies.

Pre-trial and pre-response EEG microstates in schizophrenia: An endophenotypic marker

Cognitive deficits in Schizophrenia interfere with everyday functioning and social functioning. Strong familial associations in schizophrenia might serve to establish cognitive impairments as endophenotypic markers. Therefore, visuo-spatial working memory simulating day-to-day activities at high memory load was assessed in patients with schizophrenia, their first-degree relatives and healthy controls to explore pre-trial and pre-response EEG microstates and their intracranial generators. Twenty-eight patients with schizophrenia, first-degree relatives and matched healthy controls participated in the study. Brain activity during visuo-spatial working memory task was recorded using 128-channel electroencephalography. Pre-trial and pre-response microstate maps of correct and error trials were clustered across groups according to their topography. Microstate map parameters and underlying cortical sources were compared among groups. Pre-trial (correct) microstate Map 1 was significantly different between controls and patients which could qualify it as a state marker with its intracranial generator localized to right inferior frontal gyrus (rIFG). Pre-response (correct) microstate map was significantly different between controls and first-degree relatives which could be considered an endophenotypic marker for schizophrenia. No significant differences were observed for error trials between groups. rIFG which is involved in the execution of multi-component behaviour and selective inhibitory control could distinguish patients with schizophrenia from their first-degree relatives and healthy controls. Further, microstate based biomarkers have the potential to facilitate diagnosis of schizophrenia at a preclinical stage resulting in efficient diagnosis and better prognosis.

Transcranial Magnetic Stimulation of Posterior Parietal Cortex Modulates Line-Length Estimation but Not Illusory Depth Perception

Transcranial Magnetic Stimulation (TMS) may affect attentional processing when applied to the right posterior parietal cortex (PPC) of healthy participants in line with neuropsychological and neuroimaging evidence on the neural bases of this cognitive function. Specifically, the application of TMS to right PPC induces a rightward attentional bias on line length estimation in healthy participants (i.e., neglect-like bias), mimicking the rightward bias shown by patients with unilateral spatial neglect after damage of the right PPC. With the present study, we investigated whether right PPC might play a crucial role in attentional processing of illusory depth perception, given the evidence that a rightward bias may be observed in patients with neglect during perception of the Necker Cube (NC). To this end, we investigated the effects of low-frequency rTMS applied to the right or left PPC on attentional disambiguation of the NC in two groups of healthy participants. To control for the effectiveness of TMS on visuospatial attention, rTMS effects were also assessed on a frequently used line length estimation (i.e., the Landmark Task or LT). Both groups also received sham stimulation. RTMS of the right or left PPC did not affect NC perception. On the other hand, rTMS of the right PPC (but not left PPC) induces neglect-like bias on the LT, in line with previous studies. These findings confirm that right PPC is involved in deployment of spatial attention on line length estimation. Interestingly, they suggest that this brain region does not critically contribute to deployment of visuospatial attention during attentional disambiguation of the Necker Cube. Future investigations, targeting different areas of fronto-parietal circuits, are necessary to further explore the neuro-functional bases of attentional contribution to illusory depth perception.

Semantic Knowledge Enhances Conscious Awareness of Visual Objects

It is becoming increasingly established that information from long-term memory can influence early perceptual processing, a finding that is in line with recent theoretical approaches to cognition such as the predictive coding framework. Notwithstanding, the impact of semantic knowledge on conscious perception and the temporal dynamics of such an influence remain unclear. To address this question, we presented pictures of novel objects to participants as the second of two targets in an attentional blink paradigm. We found that associating newly acquired semantic knowledge to objects increased overall conscious detection in comparison to objects associated with minimal knowledge while controlling for object familiarity. Additionally, event-related brain potentials revealed a corresponding modulation beginning 100 msec after stimulus presentation in the P1 component. Furthermore, the size of this modulation was correlated with participant's subjective reports of conscious perception. These findings suggest that semantic knowledge can shape the contents of consciousness by affecting early stages of perceptual processing.

Tinnitus and neuropathic pain share a common neural substrate in the form of specific brain connectivity and microstate profiles

Tinnitus and neuropathic pain share similar pathophysiological, clinical, and treatment characteristics. In this EEG study, a group of tinnitus (n = 100) and neuropathic pain (n = 100) patients are compared to each other and to a healthy control group (n = 100). Spectral analysis demonstrates gamma band activity within the primary auditory and somatosensory cortices in patients with tinnitus and neuropathic pain, respectively. A conjunction analysis further demonstrates an overlap of tinnitus and pain related activity in the anterior and posterior cingulate cortex as well as in the dorsolateral prefrontal cortex in comparison to healthy controls. Further analysis reveals that similar states characterize tinnitus and neuropathic pain patients, two of which differ from the healthy group and two of which are shared. Both pain and tinnitus patients spend half of the time in one specific microstate. Seed-based functional connectivity with the source within the predominant microstate shows delta, alpha1, and gamma lagged phase synchronization overlap with multiple brain areas between pain and tinnitus. These data suggest that auditory and somatosensory phantom perceptions share an overlapping brain network with common activation and connectivity patterns and are differentiated by specific sensory cortex gamma activation.

Transient Topographical Dynamics of the Electroencephalogram Predict Brain Connectivity and Behavioural Responsiveness During Drowsiness

As we fall sleep, our brain traverses a series of gradual changes at physiological, behavioural and cognitive levels, which are not yet fully understood. The loss of responsiveness is a critical event in the transition from wakefulness to sleep. Here we seek to understand the electrophysiological signatures that reflect the loss of capacity to respond to external stimuli during drowsiness using two complementary methods: spectral connectivity and EEG microstates. Furthermore, we integrate these two methods for the first time by investigating the connectivity patterns captured during individual microstate lifetimes. While participants performed an auditory semantic classification task, we allowed them to become drowsy and unresponsive. As they stopped responding to the stimuli, we report the breakdown of alpha networks and the emergence of theta connectivity. Further, we show that the temporal dynamics of all canonical EEG microstates slow down during unresponsiveness. We identify a specific microstate (D) whose occurrence and duration are prominently increased during this period. Employing machine learning, we show that the temporal properties of microstate D, particularly its prolonged duration, predicts the response likelihood to individual stimuli. Finally, we find a novel relationship between microstates and brain networks as we show that microstate D uniquely indexes significantly stronger theta connectivity during unresponsiveness. Our findings demonstrate that the transition to unconsciousness is not linear, but rather consists of an interplay between transient brain networks reflecting different degrees of sleep depth.

Inhibition-excitation balance in the parietal cortex modulates volitional control for auditory and visual multistability

Perceptual organisation must select one interpretation from several alternatives to guide behaviour. Computational models suggest that this could be achieved through an interplay between inhibition and excitation across competing types of neural population coding for each interpretation. Here, to test for such models, we used magnetic resonance spectroscopy to measure non-invasively the concentrations of inhibitory γ-aminobutyric acid (GABA) and excitatory glutamate-glutamine (Glx) in several brain regions. Human participants first performed auditory and visual multistability tasks that produced spontaneous switching between percepts. Then, we observed that longer percept durations during behaviour were associated with higher GABA/Glx ratios in the sensory area coding for each modality. When participants were asked to voluntarily modulate their perception, a common factor across modalities emerged: the GABA/Glx ratio in the posterior parietal cortex tended to be positively correlated with the amount of effective volitional control. Our results provide direct evidence implicating that the balance between neural inhibition and excitation within sensory regions resolves perceptual competition. This powerful computational principle appears to be leveraged by both audition and vision, implemented independently across modalities, but modulated by an integrated control process.

Stimulus rivalry and binocular rivalry share a common neural substrate

When two incompatible images are shown separately to each eye, a perceptual process known as binocular rivalry occurs by which the two images compete for awareness. The site of competition for binocular rivalry has been a topic of debate, and recent theories are that it may occur either at low levels of the visual system where the inputs from the two eyes are combined or at high levels of the visual system where the two images are processed. One of the major pieces of evidence for a high-level image account of rivalry is a phenomenon known as stimulus rivalry, in which two competing stimuli are swapped between the eyes at 3 Hz. However, there is little available neurophysiological evidence for a neural substrate for this high-level competition. Here, we used frequency tagging of two competing stimuli in binocular rivalry and stimulus rivalry in humans to evaluate whether the steady-state visually evoked potentials (SSVEPs) show similar signatures of neural competition for both conditions. We found that flickering the stimuli generates spectral power at the tagged frequencies in both types of rivalry in the early visual cortex. We then quantified dynamic signatures of competition by tracking amplitude changes in the frequency tags, which showed that both types of rivalry colocalized in occipital regions of the cortex. Thus, contrary to our hypothesis that stimulus rivalry was being mediated by high-level competition between the images, we find that neural competition measured by the SSVEP instead suggests that the sites of competition for stimulus rivalry and binocular rivalry may similarly include the occipital pole and middle temporal gyrus (hMT+/V5) of the visual system, consistent with a low-level, binocular interpretation.

The Dynamic EEG Microstates in Mental Rotation

Mental rotation is generally analyzed based on event-related potential (ERP) in a time domain with several characteristic electrodes, but neglects the whole spatial-temporal brain pattern in the cognitive process which may reflect the underlying cognitive mechanism. In this paper, we mainly proposed an approach based on microstates to examine the encoding of mental rotation from the spatial-temporal changes of EEG signals. In particular, we collected EEG data from 11 healthy subjects in a mental rotation cognitive task using 12 different stimulus pictures representing left and right hands at various rotational angles. We applied the microstate method to investigate the microstates conveyed by the event-related potential extracted from EEG data during mental rotation, and obtained four microstate modes (referred to as modes A, B, C, D, respectively). Subsequently, we defined several measures, including microstate sequences, topographical map, hemispheric lateralization, and duration of microstate, to characterize the dynamics of microstates during mental rotation. We observed that (1) the microstates sequence had a specified progressing mode, i.e., A→B→A; (2) the activation of the right parietal occipital region was stronger than that of the left parietal occipital region according to the hemispheric lateralization of the microstates mode A; and (3) the duration of the second microstates mode A showed the shorter duration in the vertical stimuli, named “angle effect”.

Steady-state evoked potentials distinguish brain mechanisms of self-paced versus synchronization finger tapping

Sensorimotor synchronization (SMS) requires aligning motor actions to external events and represents a core part of both musical and dance performances. In the current study, to isolate the brain mechanisms involved in synchronizing finger tapping with a musical beat, we compared SMS to pure self-paced finger tapping and listen-only conditions at different tempi. We analyzed EEG data using frequency domain steady-state evoked potentials (SSEPs) to identify sustained electrophysiological brain activity during repetitive tasks. Behavioral results revealed different timing modes between SMS and self-paced finger tapping, associated with distinct scalp topographies, thus suggesting different underlying brain sources. After subtraction of the listen-only brain activity, SMS was compared to self-paced finger tapping. Resulting source estimations showed stronger activation of the left inferior frontal gyrus during SMS, and stronger activation of the bilateral inferior parietal lobule during self-paced finger tapping. These results point to the left inferior frontal gyrus as a pivot for perception-action coupling. We discuss our findings in the context of the ongoing debate about SSEPs interpretation given the variety of brain events contributing to SSEPs and similar EEG frequency responses.

Long-Range Temporal Correlations in Alpha Oscillations Stabilize Perception of Ambiguous Visual Stimuli

Ongoing brain dynamics have been proposed as a type of “neuronal noise” that can trigger perceptual switches when viewing an ambiguous, bistable stimulus. However, no prior study has directly quantified how such neuronal noise relates to the rate of percept reversals. Specifically, it has remained unknown whether individual differences in complexity of resting-state oscillations—as reflected in long-range temporal correlations (LRTC)—are associated with perceptual stability. We hypothesized that participants with stronger resting-state LRTC in the alpha band experience more stable percepts, and thereby fewer perceptual switches. Furthermore, we expected that participants who report less discontinuous thoughts during rest, experience less switches. To test this, we recorded electroencephalography (EEG) in 65 healthy volunteers during 5 min Eyes-Closed Rest (ECR), after which they filled in the Amsterdam Resting-State Questionnaire (ARSQ). This was followed by three conditions where participants attended an ambiguous structure-from-motion stimulus—Neutral (passively observe the stimulus), Hold (the percept for as long as possible), and Switch (as often as possible). LRTC of resting-state alpha oscillations predicted the number of switches only in the Hold condition, with stronger LRTC associated with less switches. Contrary to our expectations, there was no association between resting-state Discontinuity of Mind and percept stability. Participants were capable of controlling switching according to task goals, and this was accompanied by increased alpha power during Hold and decreased power during Switch. Fewer switches were associated with stronger task-related alpha LRTC in all conditions. Together, our data suggest that bistable visual perception is to some extent under voluntary control and influenced by LRTC of alpha oscillations.

Neural dynamics of breaking continuous flash suppression

Sensory input to the human visual system often becomes accessible to cognition and overt report during processing. We investigated neural precursors of conscious vision using EEG recordings and the popular breaking continuous flash suppression (bCFS) paradigm. In this technique, a mask consisting of high-contrast dynamic patterns is presented to one eye, predominating over a target stimulus presented to the other eye. The time needed for the target stimulus to overcome the suppression is thought to reflect the transition from unconscious to conscious perception. In bCFS trials with slow responses, indicative of potent suppression, a time-frequency analysis showed reduced occipital gamma power (33-38 Hz) contralaterally to the visual hemifield where the target was presented 0.27 to 0.21 s prior to the behavioral response. This neural activity was concurrent with a local phase reset and enhanced long-range phase synchronization in the theta band (7 Hz). Such a pattern did not arise in a control condition in which suppression was not induced. Thus, the theta phase reset and synchronization in bCFS trials precede a break from suppression, likely initiating a re-routing of information such that the neural representation of the target is updated more efficiently than that of the competing mask. Overall, these findings mark the emergence of a binocularly integrated percept that can be consciously selected for a behavioral response.

Updating impairments and the failure to explore new hypotheses following right brain damage

We have shown recently that damage to the right hemisphere impairs the ability to update mental models when evidence suggests an old model is no longer appropriate. We argue that this deficit is generic in the sense that it crosses multiple cognitive and perceptual domains. Here, we examined the nature of this updating impairment to determine more precisely the underlying mechanisms. We had right (RBD, N = 12) and left brain damaged (LBD, N = 10) patients perform versions of our picture-morphing task in which pictures gradually morph from one object (e.g., shark) to another (e.g., plane). Performance was contrasted against two groups of healthy older controls, one matched on age (HCO-age-matched, N = 9) and another matched on general level of cognitive ability (HCO-cognitively-matched, N = 9). We replicated our earlier findings showing that RBD patients took longer than LBD patients and HCOs to report seeing the second object in a sequence of morphing images. The groups did not differ when exposed to a morphing sequence a second time, or when responding to ambiguous images outside the morphing context. This indicates that RBD patients have little difficulty alternating between known representations or labeling ambiguous images. Instead, the difficulty lies in generating alternate hypotheses for ambiguous information. Lesion overlay analyses, although speculative given the sample size, are consistent with our fMRI work in healthy individuals in implicating the anterior insular cortex as critical for updating mental models.

Do early neural correlates of visual consciousness show the oblique effect? A binocular rivalry and event-related potential study

When dissimilar images are presented one to each eye, we do not see both images; rather, we see one at a time, alternating unpredictably. This is called binocular rivalry, and it has recently been used to study brain processes that correlate with visual consciousness, because perception changes without any change in the sensory input. Such studies have used various types of images, but the most popular have been gratings: sets of bright and dark lines of orthogonal orientations presented one to each eye. We studied whether using cardinal rival gratings (vertical, 0°, and horizontal, 90°) versus oblique rival gratings (left-oblique, -45°, and right-oblique, 45°) influences early neural correlates of visual consciousness, because of the oblique effect: the tendency for visual performance to be greater for cardinal gratings than for oblique gratings. Participants viewed rival gratings and pressed keys indicating which of the two gratings they perceived, was dominant. Next, we changed one of the gratings to match the grating shown to the other eye, yielding binocular fusion. Participants perceived the rivalry-to-fusion change to the dominant grating and not to the other, suppressed grating. Using event-related potentials (ERPs), we found neural correlates of visual consciousness at the P1 for both sets of gratings, as well as at the P1-N1 for oblique gratings, and we found a neural correlate of the oblique effect at the N1, but only for perceived changes. These results show that the P1 is the earliest neural activity associated with visual consciousness and that visual consciousness might be necessary to elicit the oblique effect.

Electrical Neuroimaging of Music Processing Reveals Mid-Latency Changes with Level of Musical Expertise

This original research focused on the effect of musical training intensity on cerebral and behavioral processing of complex music using high-density event-related potential (ERP) approaches. Recently we have been able to show progressive changes with training in gray and white matter, and higher order brain functioning using (f)MRI [(functional) Magnetic Resonance Imaging], as well as changes in musical and general cognitive functioning. The current study investigated the same population of non-musicians, amateur pianists and expert pianists using spatio-temporal ERP analysis, by means of microstate analysis, and ERP source imaging. The stimuli consisted of complex musical compositions containing three levels of transgression of musical syntax at closure that participants appraised. ERP waveforms, microstates and underlying brain sources revealed gradual differences according to musical expertise in a 300–500 ms window after the onset of the terminal chords of the pieces. Within this time-window, processing seemed to concern context-based memory updating, indicated by a P3b-like component or microstate for which underlying sources were localized in the right middle temporal gyrus, anterior cingulate and right parahippocampal areas. Given that the 3 expertise groups were carefully matched for demographic factors, these results provide evidence of the progressive impact of training on brain and behavior.

Characterizing dynamic amplitude of low-frequency fluctuation and its relationship with dynamic functional connectivity: An application to schizophrenia

The human brain is a highly dynamic system with non-stationary neural activity and rapidly-changing neural interaction. Resting-state dynamic functional connectivity (dFC) has been widely studied during recent years, and the emerging aberrant dFC patterns have been identified as important features of many mental disorders such as schizophrenia (SZ). However, only focusing on the time-varying patterns in FC is not enough, since the local neural activity itself (in contrast to the inter-connectivity) is also found to be highly fluctuating from research using high-temporal-resolution imaging techniques. Exploring the time-varying patterns in brain activity and their relationships with time-varying brain connectivity is important for advancing our understanding of the co-evolutionary property of brain network and the underlying mechanism of brain dynamics. In this study, we introduced a framework for characterizing time-varying brain activity and exploring its associations with time-varying brain connectivity, and applied this framework to a resting-state fMRI dataset including 151 SZ patients and 163 age- and gender matched healthy controls (HCs). In this framework, 48 brain regions were first identified as intrinsic connectivity networks (ICNs) using group independent component analysis (GICA). A sliding window approach was then adopted for the estimation of dynamic amplitude of low-frequency fluctuation (dALFF) and dFC, which were used to measure time-varying brain activity and time-varying brain connectivity respectively. The dALFF was further clustered into six reoccurring states by the k-means clustering method and the group difference in occurrences of dALFF states was explored. Lastly, correlation coefficients between dALFF and dFC were calculated and the group difference in these dALFF-dFC correlations was explored. Our results suggested that 1) ALFF of brain regions was highly fluctuating during the resting-state and such dynamic patterns are altered in SZ, 2) dALFF and dFC were correlated in time and their correlations are altered in SZ. The overall results support and expand prior work on abnormalities of brain activity, static FC (sFC) and dFC in SZ, and provide new evidence on aberrant time-varying brain activity and its associations with brain connectivity in SZ, which might underscore the disrupted brain cognitive functions in this mental disorder.