Beyond the Status Quo: A Role for Beta Oscillations in Endogenous Content (Re)Activation

Pilot Study on Dose-Dependent Effects of Transcranial Photobiomodulation on Brain Electrical Oscillations: A Potential Therapeutic Target in Alzheimer's Disease

BACKGROUND

Transcranial photobiomodulation (tPBM) has recently emerged as a potential cognitive enhancement technique and clinical treatment for various neuropsychiatric and neurodegenerative disorders by delivering invisible near-infrared light to the scalp and increasing energy metabolism in the brain.

OBJECTIVE

We assessed whether transcranial photobiomodulation with near-infrared light modulates cerebral electrical activity through electroencephalogram (EEG) and cerebral blood flow (CBF).

METHODS

We conducted a single-blind, sham-controlled pilot study to test the effect of continuous (c-tPBM), pulse (p-tPBM), and sham (s-tPBM) transcranial photobiomodulation on EEG oscillations and CBF using diffuse correlation spectroscopy (DCS) in a sample of ten healthy subjects [6F/4 M; mean age 28.6±12.9 years]. c-tPBM near-infrared radiation (NIR) (830 nm; 54.8 mW/cm2; 65.8 J/cm2; 2.3 kJ) and p-tPBM (830 nm; 10 Hz; 54.8 mW/cm2; 33%; 21.7 J/cm2; 0.8 kJ) were delivered concurrently to the frontal areas by four LED clusters. EEG and DCS recordings were performed weekly before, during, and after each tPBM session.

RESULTS

c-tPBM significantly boosted gamma (t = 3.02, df = 7, p <  0.02) and beta (t = 2.91, df = 7, p <  0.03) EEG spectral powers in eyes-open recordings and gamma power (t = 3.61, df = 6, p <  0.015) in eyes-closed recordings, with a widespread increase over frontal-central scalp regions. There was no significant effect of tPBM on CBF compared to sham.

CONCLUSION

Our data suggest a dose-dependent effect of tPBM with NIR on cerebral gamma and beta neuronal activity. Altogether, our findings support the neuromodulatory effect of transcranial NIR.

Quantitative EEG measures in profoundly deaf and normal hearing individuals while performing a vibrotactile temporal discrimination task

Challenges in early oral language acquisition in profoundly deaf individuals have an impact on cognitive neurodevelopment. This has led to the exploration of alternative sound perception methods involving training of vibrotactile discrimination of sounds within the language spectrum. In particular, stimulus duration plays an important role in linguistic categorical perception. We comparatively evaluated vibrotactile temporal discrimination of sound and how specific training can modify the underlying electrical brain activity. Fifteen profoundly deaf (PD) and 15 normal-hearing (NH) subjects performed a vibrotactile oddball task with simultaneous EEG recording, before and after a short training period (5 one-hour sessions; in 2.5-3 weeks). The stimuli consisted of 700 Hz pure-tones with different duration (target: long 500 ms; non-target: short 250 ms). The sound-wave stimuli were delivered by a small device worn on the right index finger. A similar behavioral training effect was observed in both groups showing significant improvement in sound-duration discrimination. However, quantitative EEG measurements reveal distinct neurophysiological patterns characterized by higher and more diffuse delta band magnitudes in the PD group, together with a generalized decrement in absolute power in both groups that might reflect a facilitating process associated to learning. Furthermore, training-related changes were found in the beta-band in NH. Findings suggest PD have different cognitive adaptive mechanisms which are not a mere amplification effect due to greater cortical excitability.

Differential Contributions of Inhibitory Subnetwork to Visual Cortical Modulations Identified via Computational Model of Working Memory

Extrastriate visual neurons show no firing rate change during a working memory (WM) task in the absence of sensory input, but both αβ oscillations and spike phase locking are enhanced, as is the gain of sensory responses. This lack of change in firing rate is at odds with many models of WM, or attentional modulation of sensory networks. In this article we devised a computational model in which this constellation of results can be accounted for via selective activation of inhibitory subnetworks by a top-down working memory signal. We confirmed the model prediction of selective inhibitory activation by segmenting cells in the experimental neural data into putative excitatory and inhibitory cells. We further found that this inhibitory activation plays a dual role in influencing excitatory cells: it both modulates the inhibitory tone of the network, which underlies the enhanced sensory gain, and also produces strong spike-phase entrainment to emergent network oscillations. Using a phase oscillator model we were able to show that inhibitory tone is principally modulated through inhibitory network gain saturation, while the phase-dependent efficacy of inhibitory currents drives the phase locking modulation. The dual contributions of the inhibitory subnetwork to oscillatory and non-oscillatory modulations of neural activity provides two distinct ways for WM to recruit sensory areas, and has relevance to theories of cortical communication.

Local field potentials in Parkinson's disease: A frequency-based review

Deep brain stimulation (DBS) surgery offers a unique opportunity to record local field potentials (LFPs), the electrophysiological population activity of neurons surrounding the depth electrode in the target area. With direct access to the subcortical activity, LFP research has provided valuable insight into disease mechanisms and cognitive processes and inspired the advent of adaptive DBS for Parkinson's disease (PD). A frequency-based framework is usually employed to interpret the implications of LFP signatures in LFP studies on PD. This approach standardizes the methodology, simplifies the interpretation of LFP patterns, and makes the results comparable across studies. Importantly, previous works have found that activity patterns do not represent disease-specific activity but rather symptom-specific or task-specific neuronal signatures that relate to the current motor, cognitive or emotional state of the patient and the underlying disease. In the present review, we aim to highlight distinguishing features of frequency-specific activities, mainly within the motor domain, recorded from DBS electrodes in patients with PD. Associations of the commonly reported frequency bands (delta, theta, alpha, beta, gamma, and high-frequency oscillations) to motor signs are discussed with respect to band-related phenomena such as individual tremor and high/low beta frequency activity, as well as dynamic transients of beta bursts. We provide an overview on how electrophysiology research in DBS patients has revealed and will continuously reveal new information about pathophysiology, symptoms, and behavior, e.g., when combining deep LFP and surface electrocorticography recordings.

Sensor-Level Wavelet Analysis Reveals EEG Biomarkers of Perceptual Decision-Making

Perceptual decision-making requires transforming sensory information into decisions. An ambiguity of sensory input affects perceptual decisions inducing specific time-frequency patterns on EEG (electroencephalogram) signals. This paper uses a wavelet-based method to analyze how ambiguity affects EEG features during a perceptual decision-making task. We observe that parietal and temporal beta-band wavelet power monotonically increases throughout the perceptual process. Ambiguity induces high frontal beta-band power at 0.3–0.6 s post-stimulus onset. It may reflect the increasing reliance on the top-down mechanisms to facilitate accumulating decision-relevant sensory features. Finally, this study analyzes the perceptual process using mixed within-trial and within-subject design. First, we found significant percept-related changes in each subject and then test their significance at the group level. Thus, observed beta-band biomarkers are pronounced in single EEG trials and may serve as control commands for brain-computer interface (BCI).

Peripheral Electrical Stimulation Modulates Cortical Beta-Band Activity

Low-frequency peripheral electrical stimulation using a matrix electrode (PEMS) modulates spinal nociceptive pathways. However, the effects of this intervention on cortical oscillatory activity have not been assessed yet. The aim of this study was to investigate the effects of low-frequency PEMS (4 Hz) on cortical oscillatory activity in different brain states in healthy pain-free participants. In experiment 1, PEMS was compared to sham stimulation. In experiment 2, motor imagery (MI) was used to modulate the sensorimotor brain state. PEMS was applied either during MI-induced oscillatory desynchronization (concurrent PEMS) or after MI (delayed PEMS) in a cross-over design. For both experiments, PEMS was applied on the left forearm and resting-state electroencephalography (EEG) was recording before and after each stimulation condition. Experiment 1 showed a significant decrease of global resting-state beta power after PEMS compared to sham (p = 0.016), with a median change from baseline of −16% for PEMS and −0.54% for sham. A cluster-based permutation test showed a significant difference in resting-state beta power comparing pre- and post-PEMS (p = 0.018) that was most pronounced over bilateral central and left frontal sensors. Experiment 2 did not identify a significant difference in the change from baseline of global EEG power for concurrent PEMS compared to delayed PEMS. Two cluster-based permutation tests suggested that frontal beta power may be increased following both concurrent and delayed PEMS. This study provides novel evidence for supraspinal effects of low-frequency PEMS and an initial indication that the presence of a cognitive task such as MI may influence the effects of PEMS on beta activity. Chronic pain has been associated with changes in beta activity, in particular an increase of beta power in frontal regions. Thus, brain state-dependent PEMS may offer a novel approach to the treatment of chronic pain. However, further studies are warranted to investigate optimal stimulation conditions to achieve a reduction of pain.

Critical Dynamics in Spontaneous Resting-State Oscillations Are Associated With the Attention-Related P300 ERP in a Go/Nogo Task

Sustained attention is the ability to continually concentrate on task-relevant information, even in the presence of distraction. Understanding the neural mechanisms underlying this ability is critical for comprehending attentional processes as well as neuropsychiatric disorders characterized by attentional deficits, such as attention deficit hyperactivity disorder (ADHD). In this study, we aimed to investigate how trait-like critical oscillations during rest relate to the P300 evoked potential-a biomarker commonly used to assess attentional deficits. We measured long-range temporal correlations (LRTC) in resting-state EEG oscillations as index for criticality of the signal. In addition, the attentional performance of the subjects was assessed as reaction time variability (RTV) in a continuous performance task following an oddball paradigm. P300 amplitude and latencies were obtained from EEG recordings during this task. We found that, after controlling for individual variability in task performance, LRTC were positively associated with P300 amplitudes but not latencies. In line with previous findings, good performance in the sustained attention task was related to higher P300 amplitudes and earlier peak latencies. Unexpectedly, we observed a positive relationship between LRTC in ongoing oscillations during rest and RTV, indicating that greater criticality in brain oscillations during rest relates to worse task performance. In summary, our results show that resting-state neuronal activity, which operates near a critical state, relates to the generation of higher P300 amplitudes. Brain dynamics close to criticality potentially foster a computationally advantageous state which promotes the ability to generate higher event-related potential (ERP) amplitudes.

BCI learning induces core-periphery reorganization in M/EEG multiplex brain networks

Brain-computer interfaces (BCIs) constitute a promising tool for communication and control. However, mastering non-invasive closed-loop systems remains a learned skill that is difficult to develop for a non-negligible proportion of users. The involved learning process induces neural changes associated with a brain network reorganization that remains poorly understood. To address this inter-subject variability, we adopted a multilayer approach to integrate brain network properties from electroencephalographic (EEG) and magnetoencephalographic (MEG) data resulting from a four-session BCI training program followed by a group of healthy subjects. Our method gives access to the contribution of each layer to multilayer network that tends to be equal with time. We show that regardless the chosen modality, a progressive increase in the integration of somatosensory areas in the α band was paralleled by a decrease of the integration of visual processing and working memory areas in the β band. Notably, only brain network properties in multilayer network correlated with future BCI scores in the α2 band: positively in somatosensory and decision-making related areas and negatively in associative areas. Our findings cast new light on neural processes underlying BCI training. Integrating multimodal brain network properties provides new information that correlates with behavioral performance and could be considered as a potential marker of BCI learning.

Neurophysiological correlates of purchase decision-making

Economic decisions are characterized by their uncertainty and the lack of explicit feedback that indicates the correctness of decisions at the time they are made. Nevertheless, very little is known about the neural mechanisms involved in this process. Our study sought to identify the neurophysiological correlates of purchase decision-making in situations where the optimal purchase time is not known. EEG was recorded in 24 healthy subjects while they were performing a new experimental paradigm that simulates real economic decisions. At the time of price presentation, we found an increase in the P3 Event-Related Potential and induced theta and alpha oscillatory activity when participants chose to buy compared to when they decided to wait for a better price. These results reflect the engagement of attention and executive function in purchase decision-making and might help in the understanding of brain mechanisms underlying economic decisions in uncertain scenarios.

Memory Load Alters Perception-Related Neural Oscillations during Multisensory Integration

Integrating information across different senses is a central feature of human perception. Previous research suggests that multisensory integration is shaped by a context-dependent and largely adaptive interplay between stimulus-driven bottom-up and top-down endogenous influences. One critical question concerns the extent to which this interplay is sensitive to the amount of available cognitive resources. In the present study, we investigated the influence of limited cognitive resources on audiovisual integration by measuring high-density electroencephalography (EEG) in healthy participants performing the sound-induced flash illusion (SIFI) and a verbal n-back task (0-back, low load and 2-back, high load) in a dual-task design. In the SIFI, the integration of a flash with two rapid beeps can induce the illusory perception of two flashes. We found that high compared with low load increased illusion susceptibility and modulated neural oscillations underlying illusion-related crossmodal interactions. Illusion perception under high load was associated with reduced early β power (18-26 Hz, ∼70 ms) in auditory and motor areas, presumably reflecting an early mismatch signal and subsequent top-down influences including increased frontal θ power (7-9 Hz, ∼120 ms) in mid-anterior cingulate cortex (ACC) and a later β power suppression (13-22 Hz, ∼350 ms) in prefrontal and auditory cortex. Our study demonstrates that integrative crossmodal interactions underlying the SIFI are sensitive to the amount of available cognitive resources and that multisensory integration engages top-down θ and β oscillations when cognitive resources are scarce.SIGNIFICANCE STATEMENT The integration of information across multiple senses, a remarkable ability of our perceptual system, is influenced by multiple context-related factors, the role of which is highly debated. It is, for instance, poorly understood how available cognitive resources influence crossmodal interactions during multisensory integration. We addressed this question using the sound-induced flash illusion (SIFI), a phenomenon in which the integration of two rapid beeps together with a flash induces the illusion of a second flash. Replicating our previous work, we demonstrate that depletion of cognitive resources through a working memory (WM) task increases the perception of the illusion. With respect to the underlying neural processes, we show that when available resources are limited, multisensory integration engages top-down θ and β oscillations.

Enhanced gamma band mutual information is associated with impaired consciousness during temporal lobe seizures

Background

Epileptic seizures are characterized by aberrant synchronization. We hypothesized that higher synchronization across the seizure onset zone (SOZ) channels during a temporal lobe seizure contributes to impaired consciousness.

New method

All symmetric bivariate synchronization measures were extended to multivariate measure by a principal component analysis (PCA) based technique. A novel nonparametric method has been proposed to test the statistical significance between increased synchronization across the seizure onset zone (SOZ) channels and reduced consciousness.

Results

Increased synchronization in the gamma band towards seizure termination significantly contributes to impaired consciousness (p < 0.1). Synchronization reaches its peak in the extratemporal region (frontal lobe) ahead of the temporal region (p < 0.05). Synchronization is prominent in beta and gamma bands by most methods and it is more in the second half of seizure duration than in the first (p < 0.05).

Conclusions

Mutual information is the only synchronization measure out of the six that we studied, whose increase can be associated with the loss of consciousness in a statistically significant way.

EEG-Based Measures in At-Risk Mental State and Early Stages of Schizophrenia: A Systematic Review

Introduction: Electrophysiological (EEG) abnormalities in subjects with schizophrenia have been largely reported. In the last decades, research has shifted to the identification of electrophysiological alterations in the prodromal and early phases of the disorder, focusing on the prediction of clinical and functional outcome. The identification of neuronal aberrations in subjects with a first episode of psychosis (FEP) and in those at ultra high-risk (UHR) or clinical high-risk (CHR) to develop a psychosis is crucial to implement adequate interventions, reduce the rate of transition to psychosis, as well as the risk of irreversible functioning impairment. The aim of the review is to provide an up-to-date synthesis of the electrophysiological findings in the at-risk mental state and early stages of schizophrenia. Methods: A systematic review of English articles using Pubmed, Scopus, and PsychINFO was undertaken in July 2020. Additional studies were identified by hand-search. Electrophysiological studies that included at least one group of FEP or subjects at risk to develop psychosis, compared to healthy controls (HCs), were considered. The heterogeneity of the studies prevented a quantitative synthesis. Results: Out of 319 records screened, 133 studies were included in a final qualitative synthesis. Included studies were mainly carried out using frequency analysis, microstates and event-related potentials. The most common findings included an increase in delta and gamma power, an impairment in sensory gating assessed through P50 and N100 and a reduction of Mismatch Negativity and P300 amplitude in at-risk mental state and early stages of schizophrenia. Progressive changes in some of these electrophysiological measures were associated with transition to psychosis and disease course. Heterogeneous data have been reported for indices evaluating synchrony, connectivity, and evoked-responses in different frequency bands. Conclusions: Multiple EEG-indices were altered during at-risk mental state and early stages of schizophrenia, supporting the hypothesis that cerebral network dysfunctions appear already before the onset of the disorder. Some of these alterations demonstrated association with transition to psychosis or poor functional outcome. However, heterogeneity in subjects' inclusion criteria, clinical measures and electrophysiological methods prevents drawing solid conclusions. Large prospective studies are needed to consolidate findings concerning electrophysiological markers of clinical and functional outcome.

Abnormal organization of inhibitory control functional networks in future binge drinkers

BACKGROUND AND AIMS

Adolescent Binge drinking has become an increasing health and social concern, which cause several detrimental consequences for brain integrity. However, research on neurophysiological traits of vulnerability for binge drinking predisposition is limited at this time. In this work, we conducted a two-year longitudinal study with magnetoencephalography (MEG) over a cohort of initially alcohol-naive adolescents with the purpose of characterize inhibitory cortical networks' anomalies prior to alcohol consumption onset in those youths who will transit into binge drinkers years later.

METHODS

Sixty-seven participant's inhibitory functional networks, and dysexecutive/impulsivity traits were measured by means of inhibitory task (go/no-go) and questionnaires battery. After a follow-up period of two years, we evaluated their alcohol consumption habits, sub-dividing them in two groups according to their alcohol intake patterns: future binge drinkers (fBD): n = 22; future Light/non-drinkers (fLD): n = 17. We evaluated whole-brain and seed-based functional connectivity profiles, as well as its correlation with impulsive and dysexecutive behaviours, searching for early abnormalities before consumption onset.

RESULTS

For the first time, abnormalities in MEG functional networks and higher dysexecutive and impulsivity profiles were detected in alcohol-naïve adolescents who two years later became binge drinkers. Concretely, fBD exhibit a distinctive pattern of beta band hyperconnectivity among crucial regions of inhibitory control networks, positively correlated with behavioral traits and future alcohol intake rate.

CONCLUSIONS

These findings strongly support the idea of early neurobiological vulnerabilities for substances consumption initiation, with inhibitory functional networks' abnormalities as a relevant neurophysiological marker of subjects at risk- we hypothesize this profile is due to neurodevelopmental and neurobiological differences involving cognitive control networks and neurotransmission pathways.

Animal Models of Tinnitus Treatment: Cochlear and Brain Stimulation

Neuromodulation, via stimulation of a variety of peripheral and central structures, is used to suppress tinnitus. However, investigative limitations in humans due to ethical reasons have made it difficult to decipher the mechanisms underlying treatment-induced tinnitus relief, so a number of animal models have arisen to address these unknowns. This chapter reviews animal models of cochlear and brain stimulation and assesses their modulatory effects on behavioral evidence of tinnitus and its related neural correlates. When a structure is stimulated, localized modulation, often presenting as downregulation of spontaneous neuronal spike firing rate, bursting and neurosynchrony, occurs within the brain area. Through anatomical projections and transmitter pathways, the interventions activate both auditory- and non-auditory structures by taking bottom-up ascending and top-down descending modes to influence their target brain structures. Furthermore, it is the brain oscillations that cochlear or brain stimulation evoke and connect the prefrontal cortex, striatal systems, and other limbic structures to refresh neural networks and relieve auditory, attentive, conscious, as well as emotional reactive aspects of tinnitus. This oscillatory neural network connectivity is achieved via the thalamocorticothalamic circuitry including the lemniscal and non-lemniscal auditory brain structures. Beyond existing technologies, the review also reveals opportunities for developing advanced animal models using new modalities to achieve precision neuromodulation and tinnitus abatement, such as optogenetic cochlear and/or brain stimulation.

Sensory capability and information integration independently explain the cognitive status of healthy older adults

While there is evidence that sensory processing and multisensory integration change with age, links between these alterations and their relation to cognitive status remain unclear. In this study, we assessed sensory thresholds and performance of healthy younger and older adults in a visuotactile delayed match-to-sample task. Using Bayesian structural equation modelling (BSEM), we explored the factors explaining cognitive status in the group of older adults. Additionally, we applied transcranial alternating current stimulation (tACS) to a parieto-central network found to underlie visuotactile interactions and working memory matching in our previous work. Response times and signal detection measures indicated enhanced multisensory integration and enhanced benefit from successful working memory matching in older adults. Further, tACS caused a frequency-specific speeding (20 Hz) and delaying (70 Hz) of responses. Data exploration suggested distinct underlying factors for sensory acuity and sensitivity d’ on the one side, and multisensory and working memory enhancement on the other side. Finally, BSEM showed that these two factors labelled ‘sensory capability’ and ‘information integration’ independently explained cognitive status. We conclude that sensory decline and enhanced information integration might relate to distinct processes of ageing and discuss a potential role of the parietal cortex in mediating augmented integration in older adults.

EEG Correlates of Learning From Speech Presented in Environmental Noise

How the human brain retains relevant vocal information while suppressing irrelevant sounds is one of the ongoing challenges in cognitive neuroscience. Knowledge of the underlying mechanisms of this ability can be used to identify whether a person is distracted during listening to a target speech, especially in a learning context. This paper investigates the neural correlates of learning from the speech presented in a noisy environment using an ecologically valid learning context and electroencephalography (EEG). To this end, the following listening tasks were performed while 64-channel EEG signals were recorded: (1) attentive listening to the lectures in background sound, (2) attentive listening to the background sound presented alone, and (3) inattentive listening to the background sound. For the first task, 13 lectures of 5 min in length embedded in different types of realistic background noise were presented to participants who were asked to focus on the lectures. As background noise, multi-talker babble, continuous highway, and fluctuating traffic sounds were used. After the second task, a written exam was taken to quantify the amount of information that participants have acquired and retained from the lectures. In addition to various power spectrum-based EEG features in different frequency bands, the peak frequency and long-range temporal correlations (LRTC) of alpha-band activity were estimated. To reduce these dimensions, a principal component analysis (PCA) was applied to the different listening conditions resulting in the feature combinations that discriminate most between listening conditions and persons. Linear mixed-effect modeling was used to explain the origin of extracted principal components, showing their dependence on listening condition and type of background sound. Following this unsupervised step, a supervised analysis was performed to explain the link between the exam results and the EEG principal component scores using both linear fixed and mixed-effect modeling. Results suggest that the ability to learn from the speech presented in environmental noise can be predicted by the several components over the specific brain regions better than by knowing the background noise type. These components were linked to deterioration in attention, speech envelope following, decreased focusing during listening, cognitive prediction error, and specific inhibition mechanisms.

Vibration Alert to the Brain: Evoked and Induced MEG Responses to High-Frequency Vibrotactile Stimuli on the Index Finger of Dominant and Non-dominant Hand

Background: In recent years, vibrotactile haptic feedback technology has been widely used for user interfaces in the mobile devices. Although functional neuroimaging studies have investigated human brain responses to different types of tactile inputs, the neural mechanisms underlying high-frequency vibrotactile perception are still relatively unknown. Our aim was to investigate neuromagnetic brain responses to high-frequency vibrotactile stimulation, using magnetoencephalography (MEG).

Methods: We measured 152-channel whole-head MEG in 30 healthy, right-handed volunteers (aged 20–28 years, 15 females). A total of 300 vibrotactile stimuli were presented at the tip of either the left index finger or the right index finger in two separate sessions. Sinusoidal vibrations at 150 Hz for 200 ms were generated with random inter-stimulus intervals between 1.6 and 2.4 s. Both time-locked analysis and time-frequency analysis were performed to identify peak responses and oscillatory modulations elicited by high-frequency vibrations. The significance of the evoked and induced responses for dominant and non-dominant hand stimulation conditions was statistically tested, respectively. The difference in responses between stimulation conditions was also statistically evaluated.

Results: Prominent peak responses were observed at 56 ms (M50) and at 100 ms (M100) for both stimulation conditions. The M50 response revealed clear dipolar field patterns in the contralateral side with significant cortical activations in the contralateral primary sensorimotor area, whereas the M100 response was not as prominent as the M50. Vibrotactile stimulation induced significant suppression of both alpha (8–12 Hz) and beta (20–30 Hz) band activity during the mid-latency period (0.2–0.4 s), primarily in sensorimotor areas contralateral to the stimulation side. In addition, a significant alpha enhancement effect in posterior regions was accompanied with alpha suppressions in sensorimotor regions. The alpha suppression was observed in a broader distribution of cortical areas for the non-dominant hand stimulation.

Conclusion: Our data demonstrate that high-frequency tactile vibrations, which is known to primarily activate Pacinian corpuscles, elicit somatosensory M50 and M100 responses in the evoked fields and induce modulations of alpha and beta band oscillations during mid-latency periods. Our study is also consistent with that the primary sensorimotor area is significantly involved in the processing of high-frequency vibrotactile information with contralateral dominance.

Oscillations in the central brain of Drosophila are phase locked to attended visual features

Object-based attention describes the brain's capacity to prioritize one set of stimuli while ignoring others. Human research suggests that the binding of diverse stimuli into one attended percept requires phase-locked oscillatory activity in the brain. Even insects display oscillatory brain activity during visual attention tasks, but it is unclear if neural oscillations in insects are selectively correlated to different features of attended objects. We addressed this question by recording local field potentials in the Drosophila central complex, a brain structure involved in visual navigation and decision making. We found that attention selectively increased the neural gain of visual features associated with attended objects and that attention could be redirected to unattended objects by activation of a reward circuit. Attention was associated with increased beta (20- to 30-Hz) oscillations that selectively locked onto temporal features of the attended visual objects. Our results suggest a conserved function for the beta frequency range in regulating selective attention to salient visual features.

Cerebral Cortical Activity Following Non-invasive Cerebellar Stimulation-a Systematic Review of Combined TMS and EEG Studies

The cerebellum sends dense projections to both motor and non-motor regions of the cerebral cortex via the cerebellarthalamocortical tract. The integrity of this tract is crucial for healthy motor and cognitive function. This systematic review examines research using transcranial magnetic stimulation (TMS) and transcranial direct current stimulation (tDCS) to the cerebellum with combined cortical electroencephalography (EEG) to explore the temporal features of cerebellar-cortical connectivity. A detailed discussion of the outcomes and limitations of the studies meeting review criteria is presented. Databases were searched between 1 December 2017 and 6 December 2017, with Scopus alerts current as of 23 July 2019. Of the 407 studies initially identified, 10 met review criteria. Findings suggested that cerebellar-cortical assessment is suited to combined TMS and EEG, although work is required to ensure experimental procedures are optimal for eliciting a reliable cerebellar response from stimulation. A distinct variation in methodologies and outcome measures employed across studies, and small sample sizes limited the conclusions that could be drawn regarding the electrophysiological signatures of cerebellar-cortical communication. This review highlights the need for stringent protocols and methodologies for cerebellar-cortical assessments via combined TMS and EEG. With these in place, combined TMS and EEG will provide a valuable means for exploring cerebellar connectivity with a wide range of cortical sites. Assessments have the potential to aid in the understanding of motor and cognitive function in both healthy and clinical groups, and provide insights into long-range neural communication generally.

Cortical beta oscillations reflect the contextual gating of visual action feedback

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We decouple seen and felt hand postures during action via virtual reality.

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Vision of the hand is either task-relevant or a distractor.

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Task-relevance of vision is reflected by in- or decreases of occipital beta power.

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DCM suggests underlying changes in cortical (visual) excitability.

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Occipital beta may indicate the contextual gating of visual action feedback.

In sensorimotor integration, the brain needs to decide how its predictions should accommodate novel evidence by ‘gating’ sensory data depending on the current context. Here, we examined the oscillatory correlates of this process by recording magnetoencephalography (MEG) data during a new task requiring action under intersensory conflict. We used virtual reality to decouple visual (virtual) and proprioceptive (real) hand postures during a task in which the phase of grasping movements tracked a target (in either modality). Thus, we rendered visual information either task-relevant or a (to-be-ignored) distractor. Under visuo-proprioceptive incongruence, occipital beta power decreased (relative to congruence) when vision was task-relevant but increased when it had to be ignored. Dynamic causal modeling (DCM) revealed that this interaction was best explained by diametrical, task-dependent changes in visual gain. These results suggest a crucial role for beta oscillations in the contextual gating (i.e., gain or precision control) of visual vs proprioceptive action feedback, depending on current behavioral demands.

Neurophysiological Differences Between Women With Fibromyalgia and Healthy Controls During Dual Task: A Pilot Study

Background

Women with FM have a reduced ability to perform two simultaneous tasks. However, the impact of dual task (DT) on the neurophysiological response of women with FM has not been studied.

Objective

To explore both the neurophysiological response and physical performance of women with FM and healthy controls while performing a DT (motor–cognitive).

Design

Cross-sectional study.

Methods

A total of 17 women with FM and 19 age- and sex-matched healthy controls (1:1 ratio) were recruited. The electroencephalographic (EEG) activity was recorded while participants performed two simultaneous tasks: a motor (30 seconds arm-curl test) and a cognitive (remembering three unrelated words). Theta (4–7 Hz), alpha (8–12 Hz), and beta (13–30) frequency bands were analyzed by using EEGLAB.

Results

Significant differences were obtained in the healthy control group between single task (ST) and DT in the theta, alpha, and beta frequency bands (p-value < 0.05). Neurophysiological differences between ST and DT were not found in women with FM. In addition, between-group differences were found in the alpha and beta frequency bands between healthy and FM groups, with lower values of beta and alpha in the FM group. Therefore, significant group^∗condition interactions were detected in the alpha and beta frequency bands. Regarding physical condition performance, between groups, analyses showed that women with FM obtained significantly worse results in the arm curl test than healthy controls, in both ST and DT.

Conclusion

Women with FM showed the same electrical brain activity pattern during ST and DT conditions, whereas healthy controls seem to adapt their brain activity to task commitment. This is the first study that investigates the neurophysiological response of women with FM while simultaneously performing a motor and a cognitive task.

Crowdsourcing neuroscience: Inter-brain coupling during face-to-face interactions outside the laboratory

When we feel connected or engaged during social behavior, are our brains in fact "in sync" in a formal, quantifiable sense? Most studies addressing this question use highly controlled tasks with homogenous subject pools. In an effort to take a more naturalistic approach, we collaborated with art institutions to crowdsource neuroscience data: Over the course of 5 years, we collected electroencephalogram (EEG) data from thousands of museum and festival visitors who volunteered to engage in a 10-min face-to-face interaction. Pairs of participants with various levels of familiarity sat inside the Mutual Wave Machine-an artistic neurofeedback installation that translates real-time correlations of each pair's EEG activity into light patterns. Because such inter-participant EEG correlations are prone to noise contamination, in subsequent offline analyses we computed inter-brain coupling using Imaginary Coherence and Projected Power Correlations, two synchrony metrics that are largely immune to instantaneous, noise-driven correlations. When applying these methods to two subsets of recorded data with the most consistent protocols, we found that pairs' trait empathy, social closeness, engagement, and social behavior (joint action and eye contact) consistently predicted the extent to which their brain activity became synchronized, most prominently in low alpha (~7-10 Hz) and beta (~20-22 Hz) oscillations. These findings support an account where shared engagement and joint action drive coupled neural activity and behavior during dynamic, naturalistic social interactions. To our knowledge, this work constitutes a first demonstration that an interdisciplinary, real-world, crowdsourcing neuroscience approach may provide a promising method to collect large, rich datasets pertaining to real-life face-to-face interactions. Additionally, it is a demonstration of how the general public can participate and engage in the scientific process outside of the laboratory. Institutions such as museums, galleries, or any other organization where the public actively engages out of self-motivation, can help facilitate this type of citizen science research, and support the collection of large datasets under scientifically controlled experimental conditions. To further enhance the public interest for the out-of-the-lab experimental approach, the data and results of this study are disseminated through a website tailored to the general public (wp.nyu.edu/mutualwavemachine).

Anxious arousal alters prefrontal cortical control of stopping

Anxiety heightens vigilance and stimulus-driven attention to the environment, which may in turn disrupt cognitive control processes such as response inhibition. How this unfolds at the neural level is unclear. Previous evidence implicates the right inferior frontal gyrus (IFG) as an important cortical node in both stimulus-driven attention and inhibitory control. Here we used magnetoencephalography (MEG) to investigate the neural mechanisms involved in the relationship between threat-induced anxiety and stopping during a stop-signal task, where a visual go signal was occasionally followed by an auditory stop signal. Healthy individuals (N = 18) performed the task during the threat of unpredictable shocks and safety to modulate anxious arousal. Behaviorally, we observed that stopping was impaired during threat (i.e. slower estimated stop-signal reaction times), indicating that anxious arousal weakens inhibitory control. MEG source analyses revealed that bilateral IFG and right dorsal prefrontal cortex showed increased beta-band activity (14-30 Hz) to the stop signal that varied as a function of successful stopping during nonanxious (safe) conditions only. Moreover, peak beta-band responses from right IFG were inversely correlated with stopping efficiency during nonanxious conditions. These findings support theoretical claims that beta oscillations function to maintain the current sensorimotor state, and that the lack of differential beta-band activity in prefrontal cortices underlies anxiety-related deficits in inhibitory control. We specifically argue that altered right IFG functioning might directly link impaired cognitive control to heightened stimulus-driven responding in anxiety states.

Brain Activity during Different Throwing Games: EEG Exploratory Study

The purpose of this study is to explore the differences in brain activity in various types of throwing games by making encephalographic records. Three conditions of throwing games were compared looking for significant differences (simple throwing, throwing to a goal, and simultaneous throwing with another player). After signal processing, power spectral densities were compared through variance analysis (p ≤ 0.001). Significant differences were found especially in high-beta oscillations (22-30 Hz). "Goal" and "Simultaneous" throwing conditions show significantly higher values than those shown for throws without opponent. This can be explained by the higher demand for motor control and the higher arousal in competition situations. On the other hand, the high-beta records of the "Goal" condition are significantly higher than those of the "Simultaneous" throwing, which could be understood from the association of the beta waves with decision-making processes. These results support the difference in brain activity during similar games. This has several implications: opening up a path to study the effects of each specific game on brain activity and calling into question the transfer of research findings on animal play to all types of human play.

Nested oscillations and brain connectivity during sequential stages of feature-based attention

Brain mechanisms of visual selective attention involve both local and network-level activity changes at specific oscillatory rhythms, but their interplay remains poorly explored. Here, we investigate anticipatory and reactive effects of feature-based attention using separate fMRI and EEG recordings, while participants attended to one of two spatially overlapping visual features (motion and orientation). We focused on EEG source analysis of local neuronal rhythms and nested oscillations and on graph analysis of connectivity changes in a network of fMRI-defined regions of interest, and characterized a cascade of attentional effects at multiple spatial scales. We discuss how the results may reconcile several theories of selective attention, by showing how β rhythms support anticipatory information routing through increased network efficiency, while reactive α-band desynchronization patterns and increased α-γ coupling in task-specific sensory areas mediate stimulus-evoked processing of task-relevant signals.

Awakening after a sleeping pill: Restoring functional brain networks after severe brain injury

Some patients with severe brain injury show short-term neurological improvements, such as recovery of consciousness, motor function, or speech after administering zolpidem, a GABA receptor agonist. The working mechanism of this paradoxical phenomenon remains unknown. In this study, we used electroencephalography and magnetoencephalography to investigate a spectacular zolpidem-induced awakening, including the recovery of functional communication and the ability to walk in a patient with severe hypoxic-ischemic brain injury. We show that cognitive deficits, speech loss, and motor impairments after severe brain injury are associated with stronger beta band connectivity throughout the brain and suggest that neurological recovery after zolpidem occurs with the restoration of beta band connectivity. This exploratory work proposes an essential role for beta rhythms in goal-directed behavior and cognition. It advocates further fundamental and clinical research on the role of increased beta band connectivity in the development of neurological deficits after severe brain injury.

Temporal codes of visual working memory in the human cerebral cortex: Brain rhythms associated with high memory capacity

Visual working memory (vWM) is an important ability required for various cognitive tasks although its neural underpinnings remain unclear. While many studies have focused on theta (4-7 Hz) and gamma (> 30 Hz) rhythms as a substrate of vWM, here we show that temporal signals embedded in alpha (8-12 Hz) and beta (13-30 Hz) bands can be a good predictor of vWM capacity. Neural activity of healthy human participants was recorded with magnetoencephalography when they performed a classical vWM task (change detection). We analyzed changes in inter-peak intervals (IPIs) of oscillatory signals along with an increase in WM load (a number of to-be-memorized items, 1-6). Results showed a load-dependent reduction of IPIs in the parietal and frontal regions, indicating that alpha/beta rhythms became faster when multiple items were stored in vWM. Furthermore, this reduction in IPIs was positively correlated with individual vWM capacity, especially in the frontal cortex. Those results indicate that vWM is represented as a change in oscillation frequency in the human cerebral cortex.

Prior Practice Affects Movement-Related Beta Modulation and Quiet Wake Restores It to Baseline

Beta oscillations (13.5−25 Hz) over the sensorimotor areas are characterized by a power decrease during movement execution (event-related desynchronization, ERD) and a sharp rebound after the movement end (event-related synchronization, ERS). In previous studies, we demonstrated that movement-related beta modulation depth (peak ERS-ERD) during reaching increases within 1-h practice. This increase may represent plasticity processes within the sensorimotor network. If so, beta modulation during a reaching test should be affected by previous learning activity that engages the sensorimotor system but not by learning involving other systems. We thus recorded high-density EEG activity in a group of healthy subjects performing three 45-min blocks of motor adaptation task to a visually rotated display (ROT) and in another performing three blocks of visual sequence-learning (VSEQ). Each block of either ROT or VSEQ was followed by a simple reaching test (mov) without rotation. We found that beta modulation depth increased with practice across mov tests. However, such an increase was greater in the group performing ROT over both the left and frontal areas previously involved in ROT. Importantly, beta modulation values returned to baseline values after a 90-min of either nap or quiet wake. These results show that previous practice leaves a trace in movement-related beta modulation and therefore such increases are cumulative. Furthermore, as sleep is not necessary to bring beta modulation values to baseline, they could reflect local increases of neuronal activity and decrease of energy and supplies.

Investigating EEG theta and alpha oscillations as measures of value-directed strategic processing in cognitively normal younger and older adults

Value-directed strategic processing is an ability that appears to be relatively preserved with aging, but the neurophysiological mechanisms underlying strategic processing in older adults are not well understood. The current study examined age-related spectral power differences in EEG oscillations linked to processing of high-value versus low-value information in a value-directed strategic processing task in 24 younger adults (mean age: 22.4 ± 1.2 years) and 24 older adults (mean age: 63.2 ± 6.4 years). Both groups exhibited comparable strategic processing ability behaviorally with preferential recall of high- compared to low-value words. Both groups exhibited comparable theta band power with greater synchronization for low- compared to high-value words, but age-related differences in processing were noted in alpha band power. Older adults showed more prolonged alpha desynchronization for high- compared to low-value words relative to younger adults. This neurophysiological modulation in the alpha band in older adults might reflect a compensatory neural mechanism or increased effort linked to selective engagement of neural resources, allowing them to perform similarly to younger adults behaviorally on a value-directed strategic processing task.

A Compositional Neural Architecture for Language

Hierarchical structure and compositionality imbue human language with unparalleled expressive power and set it apart from other perception–action systems. However, neither formal nor neurobiological models account for how these defining computational properties might arise in a physiological system. I attempt to reconcile hierarchy and compositionality with principles from cell assembly computation in neuroscience; the result is an emerging theory of how the brain could convert distributed perceptual representations into hierarchical structures across multiple timescales while representing interpretable incremental stages of (de)compositional meaning. The model's architecture—a multidimensional coordinate system based on neurophysiological models of sensory processing—proposes that a manifold of neural trajectories encodes sensory, motor, and abstract linguistic states. Gain modulation, including inhibition, tunes the path in the manifold in accordance with behavior and is how latent structure is inferred. As a consequence, predictive information about upcoming sensory input during production and comprehension is available without a separate operation. The proposed processing mechanism is synthesized from current models of neural entrainment to speech, concepts from systems neuroscience and category theory, and a symbolic-connectionist computational model that uses time and rhythm to structure information. I build on evidence from cognitive neuroscience and computational modeling that suggests a formal and mechanistic alignment between structure building and neural oscillations, and moves toward unifying basic insights from linguistics and psycholinguistics with the currency of neural computation.

The neurophysiology of ketamine: an integrative review

The drug ketamine has been extensively studied due to its use in anaesthesia, as a model of psychosis and, most recently, its antidepressant properties. Understanding the physiology of ketamine is complex due to its rich pharmacology with multiple potential sites at clinically relevant doses. In this review of the neurophysiology of ketamine, we focus on the acute effects of ketamine in the resting brain. We ascend through spatial scales starting with a complete review of the pharmacology of ketamine and then cover its effects on in vitro and in vivo electrophysiology. We then summarise and critically evaluate studies using EEG/MEG and neuroimaging measures (MRI and PET), integrating across scales where possible. While a complicated and, at times, confusing picture of ketamine’s effects are revealed, we stress that much of this might be caused by use of different species, doses, and analytical methodologies and suggest strategies that future work could use to answer these problems.

Dissociating Cognitive Processes During Ambiguous Information Processing in Perceptual Decision-Making

Decision-making requires the accumulation of sensory evidence. However, in everyday life, sensory information is often ambiguous and contains decision-irrelevant features. This means that the brain must disambiguate sensory input and extract decision-relevant features. Sensory information processing and decision-making represent two subsequent stages of the perceptual decision-making process. While sensory processing relies on occipito-parietal neuronal activity during the earlier time window, decision-making lasts for a prolonged time, involving parietal and frontal areas. Although perceptual decision-making is being actively studied, its neuronal mechanisms under ambiguous sensory evidence lack detailed consideration. Here, we analyzed the brain activity of subjects accomplishing a perceptual decision-making task involving the classification of ambiguous stimuli. We demonstrated that ambiguity induced high frontal θ-band power for 0.15 s post-stimulus onset, indicating increased reliance on top-down processes, such as expectations and memory. Ambiguous processing also caused high occipito-parietal β-band power for 0.2 s and high fronto-parietal β-power for 0.35–0.42 s post-stimulus onset. We supposed that the former component reflected the disambiguation process while the latter reflected the decision-making phase. Our findings complemented existing knowledge about ambiguous perception by providing additional information regarding the temporal discrepancy between the different cognitive processes during perceptual decision-making.

Electrophysiological dynamics of false belief understanding and complementation syntax in school-aged children: Oscillatory brain activity and event-related potentials

A large body of research in developmental psychology has been devoted to the ongoing debate over which aspects of language are fundamental to false belief understanding (FBU). A key proposal from de Villiers and colleagues proposes the essential role of complementation syntax in FBU development. The current study, using scalp electroencephalography (EEG), addressed one opposing hypothesis purporting that complementation is redundant to FBU by characterizing the electrophysiological correlates of FBU and complementation syntax in school-age children. Time-frequency decomposition showed robust parieto-occipital low beta (12-16 Hz) power reduction in the belief versus complementation conditions. This divergence was also supported by event-related potentials (ERPs), with parieto-occipital late slow waves around 600 to 900 ms distinguishing belief and complementation conditions. The false belief condition generated the lowest behavioral response accuracy, suggesting that it is the most challenging condition. Together, the current findings provide evidence showing that complementation is not redundant to FBU.

Early Interactive Acoustic Experience with Non-speech Generalizes to Speech and Confers a Syllabic Processing Advantage at 9 Months

During early development, the infant brain is highly plastic and sensory experiences modulate emerging cortical maps, enhancing processing efficiency as infants set up key linguistic precursors. Early interactive acoustic experience (IAE) with spectrotemporally-modulated non-speech has been shown to facilitate optimal acoustic processing and generalizes to novel non-speech sounds at 7-months-of-age. Here we demonstrate that effects of non-speech IAE endure well beyond the immediate training period and robustly generalize to speech processing. Infants who received non-speech IAE differed at 9-months-of-age from both naïve controls and those with only passive acoustic exposure, demonstrating broad modulation of oscillatory dynamics. For the standard syllable, increased high-gamma (>70 Hz) power within auditory cortices indicates that IAE fosters native speech processing, facilitating establishment of phonemic representations. The higher left beta power seen may reflect increased linking of sensory information and corresponding articulatory patterns, while bilateral decreases in theta power suggest more mature automatized speech processing, as less neuronal resources were allocated to process syllabic information. For the deviant syllable, left-lateralized gamma (<70 Hz) enhancement suggests IAE promotes phonemic-related discrimination abilities. Theta power increases in right auditory cortex, known for favoring slow-rate decoding, implies IAE facilitates the more demanding processing of the sporadic deviant syllable.

Brain dynamics for confidence-weighted learning

Learning in a changing, uncertain environment is a difficult problem. A popular solution is to predict future observations and then use surprising outcomes to update those predictions. However, humans also have a sense of confidence that characterizes the precision of their predictions. Bayesian models use a confidence-weighting principle to regulate learning: for a given surprise, the update is smaller when the confidence about the prediction was higher. Prior behavioral evidence indicates that human learning adheres to this confidence-weighting principle. Here, we explored the human brain dynamics sub-tending the confidence-weighting of learning using magneto-encephalography (MEG). During our volatile probability learning task, subjects’ confidence reports conformed with Bayesian inference. MEG revealed several stimulus-evoked brain responses whose amplitude reflected surprise, and some of them were further shaped by confidence: surprise amplified the stimulus-evoked response whereas confidence dampened it. Confidence about predictions also modulated several aspects of the brain state: pupil-linked arousal and beta-range (15–30 Hz) oscillations. The brain state in turn modulated specific stimulus-evoked surprise responses following the confidence-weighting principle. Our results thus indicate that there exist, in the human brain, signals reflecting surprise that are dampened by confidence in a way that is appropriate for learning according to Bayesian inference. They also suggest a mechanism for confidence-weighted learning: confidence about predictions would modulate intrinsic properties of the brain state to amplify or dampen surprise responses evoked by discrepant observations.

Learning in a changing and uncertain world is difficult. In this context, facing a discrepancy between my current belief and new observations may reflect random fluctuations (e.g. my commute train is unexpectedly late, but it happens sometimes), if so, I should ignore this discrepancy and not change erratically my belief. However, this discrepancy could also denote a profound change (e.g. the train company changed and is less reliable), in this case, I should promptly revise my current belief. Human learning is adaptive: we change how much we learn from new observations, in particular, we promote flexibility when facing profound changes. A mathematical analysis of the problem shows that we should increase flexibility when the confidence about our current belief is low, which occurs when a change is suspected. Here, I show that human learners entertain rational confidence levels during the learning of changing probabilities. This confidence modulates intrinsic properties of the brain state (oscillatory activity and neuromodulation) which in turn amplifies or reduces, depending on whether confidence is low or high, the neural responses to discrepant observations. This confidence-weighting mechanism could underpin adaptive learning.

The 'Narcissus Effect': Top-down alpha-beta band modulation of face-related brain areas during self-face processing

Self-related information, such as one's own face, is prioritized by our cognitive system. Whilst recent theoretical developments suggest that this is achieved by an interplay between bottom-up and top-down attentional mechanisms, their underlying neural dynamics are still poorly understood. Furthermore, it is still matter of discussion as to whether these attentional mechanisms are truly self-specific or instead driven by face familiarity. To address these questions, we used EEG to record the brain activity of twenty-five healthy participants whilst identifying their own face, a friend's face and a stranger's face. Time-frequency analysis revealed a greater sustained power decrease in the alpha and beta frequency bands for the self-face, which emerged at late latencies and was maintained even when the face was no longer present. Critically, source analysis showed that this activity was generated in key brain regions for self-face recognition, such as the fusiform gyrus. As in the Myth of Narcissus, our results indicate that one's own face might have the potential to hijack attention. We suggest that this effect is specific to the self and driven by a top-down attentional control mechanism, which might facilitate further processing of personally relevant events.

Common and distinct lateralised patterns of neural coupling during focused attention, open monitoring and loving kindness meditation

Meditation has been integrated into different therapeutic interventions. To inform the evidence-based selection of specific meditation types it is crucial to understand the neural processes associated with different meditation practices. Here we explore commonalities and differences in electroencephalographic oscillatory spatial synchronisation patterns across three important meditation types. Highly experienced meditators engaged in focused attention, open monitoring, and loving kindness meditation. Improving on previous research, our approach avoids comparisons between groups that limited previous findings, while ensuring that the meditation states are reliably established. Employing a novel measure of neural coupling – the imaginary part of EEG coherence – the study revealed that all meditation conditions displayed a common connectivity pattern that is characterised by increased connectivity of (a) broadly distributed delta networks, (b) left-hemispheric theta networks with a local integrating posterior focus, and (c) right-hemispheric alpha networks, with a local integrating parieto-occipital focus. Furthermore, each meditation state also expressed specific synchronisation patterns differentially recruiting left- or right-lateralised beta networks. These observations provide evidence that in addition to global patterns, frequency-specific inter-hemispheric asymmetry is one major feature of meditation, and that mental processes specific to each meditation type are also supported by lateralised networks from fast-frequency bands.

Language and motor processing in reading and typing: Insights from beta-frequency band power modulations

Power modulations of the EEG activity within the beta-frequency band were investigated across silent-reading and copy-typing tasks featuring emotionally negative and neutral words in order to clarify the interplay between language and motor processing. In reading, a single desynchronization surfaced 200-600 ms after target presentation, with a stronger power-decrease in lower beta frequencies for neutral compared to negative words. The typing task revealed two distinct desynchronizations. A first one surfaced within spatio-temporal coordinates closely resembling those of the desynchronization observed in the reading task, thus pointing towards a common origin at the level of linguistic processing of the input word stimuli. Additionally, a second motor-related desynchronization surfaced during the typed response, from 700 to 2000 ms after stimulus onset. Here, words' emotional connotation affected the higher beta band. The comparison between tasks thus suggests that different beta desynchronizations reflect distinct EEG landmarks for language and motor processing. Further, the effect of emotional connotation on the motor-related desynchronization of the typing task suggests that language processing can propagate its influence onto the stage of motor response execution, pointing against a serial flow of information from language onto motor processing.

Modulation in phase and frequency of neural oscillations during epileptiform activity induced by neonatal Zika virus infection in mice

Modulation of brain activity is one of the main mechanisms capable of demonstrating the synchronization dynamics of neural oscillations. In epilepsy, modulation is a key concept since seizures essentially result from neural hypersynchronization and hyperexcitability. In this study, we have introduced a time-dependent index based on the Kullback-Leibler divergence to quantify the effects of phase and frequency modulations of neural oscillations in neonatal mice exhibiting epileptiform activity induced by Zika virus (ZIKV) infection. Through this index, we demonstrate that fast oscillations (gamma and beta 2) are the more susceptible modulated rhythms in terms of phase, during seizures, whereas slow waves (delta and theta) mainly undergo changes in frequency. The index also allowed detection of specific patterns associated with the interdependent modulation of phase and frequency in neural activity. Furthermore, by comparing ZIKV modulations with the general computational model Epileptors, we verify different signatures related to the brain rhythms modulation in phase and frequency. These findings instigate new studies on the effects of ZIKV infection on neuronal networks from electrophysiological activities, and how different mechanisms can trigger epilepsy.

Oscillations in the auditory system and their possible role

GOURÉVITCH, B., C. Martin, O. Postal, J.J. Eggermont. Oscillations in the auditory system, their possible role. NEUROSCI BIOBEHAV REV XXX XXX-XXX, 2020. - Neural oscillations are thought to have various roles in brain processing such as, attention modulation, neuronal communication, motor coordination, memory consolidation, decision-making, or feature binding. The role of oscillations in the auditory system is less clear, especially due to the large discrepancy between human and animal studies. Here we describe many methodological issues that confound the results of oscillation studies in the auditory field. Moreover, we discuss the relationship between neural entrainment and oscillations that remains unclear. Finally, we aim to identify which kind of oscillations could be specific or salient to the auditory areas and their processing. We suggest that the role of oscillations might dramatically differ between the primary auditory cortex and the more associative auditory areas. Despite the moderate presence of intrinsic low frequency oscillations in the primary auditory cortex, rhythmic components in the input seem crucial for auditory processing. This allows the phase entrainment between the oscillatory phase and rhythmic input, which is an integral part of stimulus selection within the auditory system.

Electrocorticography reveals continuous auditory and visual speech tracking in temporal and occipital cortex

During natural speech perception, humans must parse temporally continuous auditory and visual speech signals into sequences of words. However, most studies of speech perception present only single words or syllables. We used electrocorticography (subdural electrodes implanted on the brains of epileptic patients) to investigate the neural mechanisms for processing continuous audiovisual speech signals consisting of individual sentences. Using partial correlation analysis, we found that posterior superior temporal gyrus (pSTG) and medial occipital cortex tracked both the auditory and the visual speech envelopes. These same regions, as well as inferior temporal cortex, responded more strongly to a dynamic video of a talking face compared to auditory speech paired with a static face. Occipital cortex and pSTG carry temporal information about both auditory and visual speech dynamics. Visual speech tracking in pSTG may be a mechanism for enhancing perception of degraded auditory speech.

Action information contributes to metacognitive decision-making

Metacognitive abilities allow us to adjust ongoing behavior and modify future decisions in the absence of external feedback. Although metacognition is critical in many daily life settings, it remains unclear what information is actually being monitored and what kind of information is being used for metacognitive decisions. In the present study, we investigated whether response information connected to perceptual events contribute to metacognitive decision-making. Therefore, we recorded EEG signals during a perceptual color discrimination task while participants were asked to provide an estimate about the quality of their decision on each trial. Critically, the moment participants provided their confidence judgments varied across conditions, thereby changing the amount of action information (e.g., response competition or response fluency) available for metacognitive decisions. Results from three experiments demonstrate that metacognitive performance improved when first-order action information was available at the moment metacognitive decisions about the perceptual task had to be provided. This behavioral effect was accompanied by enhanced functional connectivity (beta phase synchrony) between motor areas and prefrontal regions, exclusively observed during metacognitive decision-making. Our findings demonstrate that action information contributes to metacognitive decision-making, thereby painting a picture of metacognition as a process that integrates sensory evidence and information about our interactions with the world.

Characterization of the dynamic behavior of neural activity in Alzheimer's disease: exploring the non-stationarity and recurrence structure of EEG resting-state activity

OBJECTIVE

Mild cognitive impairment (MCI) and dementia due to Alzheimer's disease (AD) have been shown to induce perturbations to normal neuronal behavior and disrupt neuronal networks. Recent work suggests that the dynamic properties of resting-state neuronal activity could be affected by MCI and AD-induced neurodegeneration. The aim of the study was to characterize these properties from different perspectives: (i) using the Kullback-Leibler divergence (KLD), a measure of non-stationarity derived from the continuous wavelet transform; and (ii) using the entropy of the recurrence point density ([Formula: see text]) and the median of the recurrence point density ([Formula: see text]), two novel metrics based on recurrence quantification analysis.

APPROACH

KLD, [Formula: see text] and [Formula: see text] were computed for 49 patients with dementia due to AD, 66 patients with MCI due to AD and 43 cognitively healthy controls from 60 s electroencephalographic (EEG) recordings with a 10 s sliding window with no overlap. Afterwards, we tested whether the measures reflected alterations to normal neuronal activity induced by MCI and AD.

MAIN RESULTS

Our results showed that frequency-dependent alterations to normal dynamic behavior can be found in patients with MCI and AD, both in non-stationarity and recurrence structure. Patients with MCI showed signs of patterns of abnormal state recurrence in the theta (4-8 Hz) and beta (13-30 Hz) frequency bands that became more marked in AD. Moreover, abnormal non-stationarity patterns were found in MCI patients, but not in patients with AD in delta (1-4 Hz), alpha (8-13 Hz), and gamma (30-70 Hz).

SIGNIFICANCE

The alterations in normal levels of non-stationarity in patients with MCI suggest an initial increase in cortical activity during the development of AD. This increase could possibly be due to an impairment in neuronal inhibition that is not present during later stages. MCI and AD induce alterations to the recurrence structure of cortical activity, suggesting that normal state switching during rest may be affected by these pathologies.