Response preparation and inhibition: the role of the cortical sensorimotor beta rhythm

Aperiodic measures of neural excitability are associated with anticorrelated hemodynamic networks at rest: A combined EEG-fMRI study

The hallmark of resting EEG spectra are distinct rhythms emerging from a broadband, aperiodic background. This aperiodic neural signature accounts for most of total EEG power, although its significance and relation to functional neuroanatomy remains obscure. We hypothesized that aperiodic EEG reflects a significant metabolic expenditure and therefore might be associated with the default mode network while at rest. During eyes-open, resting-state recordings of simultaneous EEG-fMRI, we find that aperiodic and periodic components of EEG power are only minimally associated with activity in the default mode network. However, a whole-brain analysis identifies increases in aperiodic power correlated with hemodynamic activity in an auditory-salience-cerebellar network, and decreases in aperiodic power are correlated with hemodynamic activity in prefrontal regions. Desynchronization in residual alpha and beta power is associated with visual and sensorimotor hemodynamic activity, respectively. These findings suggest that resting-state EEG signals acquired in an fMRI scanner reflect a balance of top-down and bottom-up stimulus processing, even in the absence of an explicit task.

Asymmetric directed functional connectivity within the frontoparietal motor network during motor imagery and execution

Both imagery and execution of motor control consist of interactions within a neuronal network, including frontal motor-related and posterior parietal regions. To reveal neural representation in the frontoparietal motor network, two approaches have been proposed thus far: one is decoding of actions/modes related to motor control from the spatial pattern of brain activity; and the other is estimating directed functional connectivity (a directed association between two brain regions within motor areas). However, directed connectivity among multiple regions of the frontoparietal motor network during motor imagery (MI) or motor execution (ME) has not been investigated. Here, we attempted to characterize the directed functional connectivity representing the MI and ME conditions. We developed a delayed sequential movement and imagery task to evoke brain activity associated with ME and MI, which can be recorded by functional magnetic resonance imaging. We applied a causal discovery approach, a linear non-Gaussian acyclic causal model, to identify directed functional connectivity among the frontoparietal motor-related brain regions for each condition. We demonstrated higher directed functional connectivity from the contralateral dorsal premotor cortex (dPMC) to the primary motor cortex (M1) in ME than in MI. We further identified significant direct effects of the dPMC and ventral premotor cortex (vPMC) to the parietal regions. In particular, connectivity from the dPMC to the superior parietal lobule (SPL) in the same hemisphere showed significant positive effects across all conditions, while interlateral connectivities from the vPMC to the SPL showed significantly negative effects across all conditions. Finally, we found positive effects from A1 to M1, that is, the audio-motor pathway, in the same hemisphere. These results indicate that the sources of motor command originating in the d/vPMC influenced the M1 and parietal regions for achieving ME and MI. Additionally, sequential sounds may functionally facilitate temporal motor processes.

Motor Preparation and Execution for Performance Difficulty: Centroparietal Beta Activation during the Effort Expenditure for Rewards Task as a Function of Motivation

Debate exists as to the effects of anxiety in performance-based studies. However, no studies have examined the influence of motivation both in preparation of a motor movement and during movement performance. The present study measured beta activation in preparation for and during execution of the effort expenditure for rewards task (EEfRT), a button-pressing task consisting of easy and hard trials. Results indicated that motor preparation (i.e., reduced beta activation) was greater in preparation for hard trials than for easy trials. Additionally, motor preparation decreased (i.e., beta activation increased) over the course of hard trial execution. These results suggest that motor preparation is enhanced prior to more challenging tasks but that motor preparation declines as participants become closer to completing their goal in each challenging trial. These results provide insight into how beta activation facilitates effort expenditure for motor tasks varying in difficulty and motivation. The impact of these results on models of anxiety and performance is discussed.

EEG Neurofeedback for Anxiety Disorders and Post-Traumatic Stress Disorders: A Blueprint for a Promising Brain-Based Therapy

PURPOSE OF REVIEW

This review provides an overview of current knowledge and understanding of EEG neurofeedback for anxiety disorders and post-traumatic stress disorders.

RECENT FINDINGS

The manifestations of anxiety disorders and post-traumatic stress disorders (PTSD) are associated with dysfunctions of neurophysiological stress axes and brain arousal circuits, which are important dimensions of the research domain criteria (RDoC). Even if the pathophysiology of these disorders is complex, one of its defining signatures is behavioral and physiological over-arousal. Interestingly, arousal-related brain activity can be modulated by electroencephalogram-based neurofeedback (EEG NF), a non-pharmacological and non-invasive method that involves neurocognitive training through a brain-computer interface (BCI). EEG NF is characterized by a simultaneous learning process where both patient and computer are involved in modifying neuronal activity or connectivity, thereby improving associated symptoms of anxiety and/or over-arousal. Positive effects of EEG NF have been described for both anxiety disorders and PTSD, yet due to a number of methodological issues, it remains unclear whether symptom improvement is the direct result of neurophysiological changes targeted by EEG NF. Thus, in this work we sought to bridge current knowledge on brain mechanisms of arousal with past and present EEG NF therapies for anxiety and PTSD. In a nutshell, we discuss the neurophysiological mechanisms underlying the effects of EEG NF in anxiety disorder and PTSD, the methodological strengths/weaknesses of existing EEG NF randomized controlled trials for these disorders, and the neuropsychological factors that may impact NF training success.

Increasing and decreasing interregional brain coupling increases and decreases oscillatory activity in the human brain

The origins of oscillatory activity in the brain are currently debated, but common to many hypotheses is the notion that they reflect interactions between brain areas. Here, we examine this possibility by manipulating the strength of coupling between two human brain regions, ventral premotor cortex (PMv) and primary motor cortex (M1), and examine the impact on oscillatory activity in the motor system measurable in the electroencephalogram. We either increased or decreased the strength of coupling while holding the impact on each component area in the pathway constant. This was achieved by stimulating PMv and M1 with paired pulses of transcranial magnetic stimulation using two different patterns, only one of which increases the influence exerted by PMv over M1. While the stimulation protocols differed in their temporal patterning, they were comprised of identical numbers of pulses to M1 and PMv. We measured the impact on activity in alpha, beta, and theta bands during a motor task in which participants either made a preprepared action (Go) or withheld it (No-Go). Augmenting cortical connectivity between PMv and M1, by evoking synchronous pre- and postsynaptic activity in the PMv-M1 pathway, enhanced oscillatory beta and theta rhythms in Go and No-Go trials, respectively. Little change was observed in the alpha rhythm. By contrast, diminishing the influence of PMv over M1 decreased oscillatory beta and theta rhythms in Go and No-Go trials, respectively. This suggests that corticocortical communication frequencies in the PMv-M1 pathway can be manipulated following Hebbian spike-timing-dependent plasticity.

Volume of β-Bursts, But Not Their Rate, Predicts Successful Response Inhibition

In humans, impaired response inhibition is characteristic of a wide range of psychiatric diseases and of normal aging. It is hypothesized that the right inferior frontal cortex (rIFC) plays a key role by inhibiting the motor cortex via the basal ganglia. The electroencephalography (EEG)-derived β-rhythm (15-29 Hz) is thought to reflect communication within this network, with increased right frontal β-power often observed before successful response inhibition. Recent literature suggests that averaging spectral power obscures the transient, burst-like nature of β-activity. There is evidence that the rate of β-bursts following a Stop signal is higher when a motor response is successfully inhibited. However, other characteristics of β-burst events, and their topographical properties, have not yet been examined. Here, we used a large human (male and female) EEG Stop Signal task (SST) dataset (n = 218) to examine averaged normalized β-power, β-burst rate, and β-burst "volume" (which we defined as burst duration × frequency span × amplitude). We first sought to optimize the β-burst detection method. In order to find predictors across the whole scalp, and with high temporal precision, we then used machine learning to (1) classify successful versus failed stopping and to (2) predict individual stop signal reaction time (SSRT). β-burst volume was significantly more predictive of successful and fast stopping than β-burst rate and normalized β-power. The classification model generalized to an external dataset (n = 201). We suggest β-burst volume is a sensitive and reliable measure for investigation of human response inhibition.SIGNIFICANCE STATEMENT The electroencephalography (EEG)-derived β-rhythm (15-29 Hz) is associated with the ability to inhibit ongoing actions. In this study, we sought to identify the specific characteristics of β-activity that contribute to successful and fast inhibition. In order to search for the most relevant features of β-activity, across the whole scalp and with high temporal precision, we employed machine learning on two large datasets. Spatial and temporal features of β-burst "volume" (duration × frequency span × amplitude) predicted response inhibition outcomes in our data significantly better than β-burst rate and normalized β-power. These findings suggest that multidimensional measures of β-bursts, such as burst volume, can add to our understanding of human response inhibition.

Long-Lasting Event-Related Beta Synchronizations of Electroencephalographic Activity in Response to Support-Surface Perturbations During Upright Stance: A Pilot Study Associating Beta Rebound and Active Monitoring in the Intermittent Postural Control

Movement related beta band cortical oscillations, including beta rebound after execution and/or suppression of movement, have drawn attention in upper extremity motor control literature. However, fewer studies focused on beta band oscillations during postural control in upright stance. In this preliminary study, we examined beta rebound and other components of electroencephalogram (EEG) activity during perturbed upright stance to investigate supraspinal contributions to postural stabilization. Particularly, we aimed to clarify the timing and duration of beta rebound within a non-sustained, but long-lasting postural recovery process that occurs more slowly compared to upper extremities. To this end, EEG signals were acquired from nine healthy young adults in response to a brief support-surface perturbation, together with the center of pressure, the center of mass and electromyogram (EMG) activities of ankle muscles. Event-related potentials (ERPs) and event-related spectral perturbations were computed from EEG data using the perturbation-onset as a triggering event. After short-latency (<0.3 s) ERPs, our results showed a decrease in high-beta band oscillations (event-related desynchronization), which was followed by a significant increase (event-related synchronization) in the same band, as well as a decrease in theta band oscillations. Unlike during upper extremity motor tasks, the beta rebound in this case was initiated before the postural recovery was completed, and sustained for as long as 3 s with small EMG responses for the first half period, followed by no excessive EMG activities for the second half period. We speculate that those novel characteristics of beta rebound might be caused by slow postural dynamics along a stable manifold of the unstable saddle-type upright equilibrium of the postural control system without active feedback control, but with active monitoring of the postural state, in the framework of the intermittent control.

The Effects of Dynamic and Static Emotional Facial Expressions of Humans and Their Avatars on the EEG: An ERP and ERD/ERS Study

This study aimed to examine whether the cortical processing of emotional faces is modulated by the computerization of face stimuli ("avatars") in a group of 25 healthy participants. Subjects were passively viewing 128 static and dynamic facial expressions of female and male actors and their respective avatars in neutral or fearful conditions. Event-related potentials (ERPs), as well as alpha and theta event-related synchronization and desynchronization (ERD/ERS), were derived from the EEG that was recorded during the task. All ERP features, except for the very early N100, differed in their response to avatar and actor faces. Whereas the N170 showed differences only for the neutral avatar condition, later potentials (N300 and LPP) differed in both emotional conditions (neutral and fear) and the presented agents (actor and avatar). In addition, we found that the avatar faces elicited significantly stronger reactions than the actor face for theta and alpha oscillations. Especially theta EEG frequencies responded specifically to visual emotional stimulation and were revealed to be sensitive to the emotional content of the face, whereas alpha frequency was modulated by all the stimulus types. We can conclude that the computerized avatar faces affect both, ERP components and ERD/ERS and evoke neural effects that are different from the ones elicited by real faces. This was true, although the avatars were replicas of the human faces and contained similar characteristics in their expression.

Dynamical EEG Indices of Progressive Motor Inhibition and Error-Monitoring

Response inhibition has been widely explored using the stop signal paradigm in the laboratory setting. However, the mechanism that demarcates attentional capture from the motor inhibition process is still unclear. Error monitoring is also involved in the stop signal task. Error responses that do not complete, i.e., partial errors, may require different error monitoring mechanisms relative to an overt error. Thus, in this study, we included a “continue go” (Cont_Go) condition to the stop signal task to investigate the inhibitory control process. To establish the finer difference in error processing (partial vs. full unsuccessful stop (USST)), a grip-force device was used in tandem with electroencephalographic (EEG), and the time-frequency characteristics were computed with Hilbert–Huang transform (HHT). Relative to Cont_Go, HHT results reveal (1) an increased beta and low gamma power for successful stop trials, indicating an electrophysiological index of inhibitory control, (2) an enhanced theta and alpha power for full USST trials that may mirror error processing. Additionally, the higher theta and alpha power observed in partial over full USST trials around 100 ms before the response onset, indicating the early detection of error and the corresponding correction process. Together, this study extends our understanding of the finer motor inhibition control and its dynamic electrophysiological mechanisms.

Topographic distribution of the EEG ad hoc broad bands during sleep and wakefulness in the spider monkey (Ateles Geoffroyi)

There is evidence that research on sleep among New World monkeys may provide important knowledge related to the evolution of sleep more broadly in the primate order. Digital electroencephalographic (EEG) analyses provide essential knowledge on sleep in the spider monkey. Recently, specific EEG bands related to sleep in these animals have been obtained using principal component analysis, but the exact spatio-temporal distribution of these EEG bands in this species has not yet been analyzed. This study determined the topographic distribution of the EEG spectral power of ad hoc broad bands during rapid eye movement sleep, nonrapid eye movement sleep, and wakefulness. Superficial EEG activity was obtained from the occipital, frontal, and central areas of six young adult male monkeys housed in a laboratory. During wakefulness, occipital areas showed high absolute power in the 1-3, 3-12, and 11-30 Hz ranges, while during nonrapid eye movement 1 sleep the highest absolute power was in the 13-30 Hz range. During nonrapid eye movement 3 sleep, frontal and central areas showed a high absolute power in the 18-19 Hz range. Finally, the right central area showed a high absolute power in the 20-30 Hz range during rapid eye movement sleep. This topographic distribution of EEG bands could represent the brain organization required for arousal and mnemonic processing during sleep in the spider monkey.

Rat Locomotion Detection Based on Brain Functional Directed Connectivity from Implanted Electroencephalography Signals

Previous findings have suggested that the cortex involved in walking control in freely locomotion rats. Moreover, the spectral characteristics of cortical activity showed significant differences in different walking conditions. However, whether brain connectivity presents a significant difference during rats walking under different behavior conditions has yet to be verified. Similarly, whether brain connectivity can be used in locomotion detection remains unknown. To address those concerns, we recorded locomotion and implanted electroencephalography signals in freely moving rats performing two kinds of task conditions (upslope and downslope walking). The Granger causality method was used to determine brain functional directed connectivity in rats during these processes. Machine learning algorithms were then used to categorize the two walking states, based on functional directed connectivity. We found significant differences in brain functional directed connectivity varied between upslope and downslope walking. Moreover, locomotion detection based on brain connectivity achieved the highest accuracy (91.45%), sensitivity (90.93%), specificity (91.3%), and F1-score (91.43%). Specifically, the classification results indicated that connectivity features in the high gamma band contained the most discriminative information with respect to locomotion detection in rats, with the support vector machine classifier exhibiting the most efficient performance. Our study not only suggests that brain functional directed connectivity in rats showed significant differences in various behavioral contexts but also proposed a method for classifying the locomotion states of rat walking, based on brain functional directed connectivity. These findings elucidate the characteristics of neural information interaction between various cortical areas in freely walking rats.

Neural oscillatory responses to performance monitoring differ between high- and low-impulsive individuals, but are unaffected by TMS

Higher impulsivity may arise from neurophysiological deficits of cognitive control in the prefrontal cortex. Cognitive control can be assessed by time‐frequency decompositions of electrophysiological data. We aimed to clarify neuroelectric mechanisms of performance monitoring in connection with impulsiveness during a modified Eriksen flanker task in high‐ (n = 24) and low‐impulsive subjects (n = 21) and whether these are modulated by double‐blind, sham‐controlled intermittent theta burst stimulation (iTBS). We found a larger error‐specific peri‐response beta power decrease over fronto‐central sites in high‐impulsive compared to low‐impulsive participants, presumably indexing less effective motor execution processes. Lower parieto‐occipital theta intertrial phase coherence (ITPC) preceding correct responses predicted higher reaction time (RT) and higher RT variability, potentially reflecting efficacy of cognitive control or general attention. Single‐trial preresponse theta phase clustering was coupled to RT in correct trials (weighted ITPC), reflecting oscillatory dynamics that predict trial‐specific behavior. iTBS did not modulate behavior or EEG time‐frequency power. Performance monitoring was associated with time‐frequency patterns reflecting cognitive control (parieto‐occipital theta ITPC, theta weighted ITPC) as well as differential action planning/execution processes linked to trait impulsivity (frontal low beta power). Beyond that, results suggest no stimulation effect related to response‐locked time‐frequency dynamics with the current stimulation protocol. Neural oscillatory responses to performance monitoring differ between high‐ and low‐impulsive individuals, but are unaffected by iTBS.

Adjustments to Proactive Motor Inhibition without Effector-Specific Foreknowledge Are Reflected in a Bilateral Upregulation of Sensorimotor β-Burst Rates

Classic work using the stop-signal task has shown that humans can use inhibitory control to cancel already initiated movements. Subsequent work revealed that inhibitory control can be proactively recruited in anticipation of a potential stop-signal, thereby increasing the likelihood of successful movement cancellation. However, the exact neurophysiological effects of proactive inhibitory control on the motor system are still unclear. On the basis of classic views of sensorimotor β-band activity, as well as recent findings demonstrating the burst-like nature of this signal, we recently proposed that proactive inhibitory control is implemented by influencing the rate of sensorimotor β-bursts during movement initiation. Here, we directly tested this hypothesis using scalp EEG recordings of β-band activity in 41 healthy human adults during a bimanual RT task. By comparing motor responses made in two different contexts-during blocks with or without stop-signals-we found that premovement β-burst rates over both contralateral and ipsilateral sensorimotor areas were increased in stop-signal blocks compared to pure-go blocks. Moreover, the degree of this burst rate difference indexed the behavioral implementation of proactive inhibition (i.e., the degree of anticipatory response slowing in the stop-signal blocks). Finally, exploratory analyses showed that these condition differences were explained by a significant increase in β bursting that was already present during the premovement baseline period in stop blocks. Together, this suggests that the strategic deployment of proactive inhibitory motor control is implemented by upregulating the tonic inhibition of the motor system, signified by increased sensorimotor β-bursting both before and after signals to initiate a movement.

Dissociable neural oscillatory mechanisms underlying unconscious priming of externally and intentionally initiated inhibition

Externally and intentionally initiated inhibitory processes, which are fundamental for human action control, can be unconsciously launched. However, the neural oscillatory mechanisms underlying unconscious priming of externally and intentionally generated inhibition remain unclear. This study aimed to explore this issue by extracting oscillatory power dynamics from electroencephalographic data with participants performing an unconscious version of the Go/No-Go/Choose task involving subliminally presented primes. The participants presented prolonged response times upon being instructed or intentionally deciding to commit a "Go" response following a No-Go prime compared with those following a Go prime. This indicates that unconscious inhibitory processes can be externally and intentionally initiated. Time-frequency analysis indicated increased theta band oscillatory power on the forced Go response following a No-Go prime compared with that following a Go prime. Contrastingly, there was pronounced alpha/low-beta band oscillatory power on the free-choice Go response following a No-Go prime compared with that following a Go prime. Moreover, there was a positive correlation of theta and alpha/low-beta band oscillations with human behavior performance related to the two distinct unconscious inhibitory processes. Our findings delineate dissociable neural oscillatory mechanisms underlying the unconscious priming of externally and intentionally initiated inhibition. Moreover, they might provide complementary neural oscillatory evidence supporting the discrepancy between instructed and voluntary human action control.

EEG Correlates of Cognitive Functions and Neuropsychiatric Disorders: A Review of Oscillatory Activity and Neural Synchrony Abnormalities

Background:

A large body of evidence suggested that disruption of neural rhythms and synchronization of brain oscillations are correlated with a variety of cognitive and perceptual processes. Cognitive deficits are common features of psychiatric disorders that complicate treatment of the motivational, affective and emotional symptoms.

Objective:

Electrophysiological correlates of cognitive functions will contribute to understanding of neural circuits controlling cognition, the causes of their perturbation in psychiatric disorders and developing novel targets for the treatment of cognitive impairments.

Methods:

This review includes a description of brain oscillations in Alzheimer’s disease, bipolar disorder, attention-deficit/hyperactivity disorder, major depression, obsessive compulsive disorders, anxiety disorders, schizophrenia and autism.

Results:

The review clearly shows that the reviewed neuropsychiatric diseases are associated with fundamental changes in both spectral power and coherence of EEG oscillations.

Conclusion:

In this article, we examined the nature of brain oscillations, the association of brain rhythms with cognitive functions and the relationship between EEG oscillations and neuropsychiatric diseases. Accordingly, EEG oscillations can most likely be used as biomarkers in psychiatric disorders.

Dynamic pulvino-cortical interactions in the primate attention network

While research in previous decades demonstrated a link between the pulvinar nucleus of the thalamus and visual selective attention, the pulvinar's specific functional role has remained elusive. However, methodological advances in electrophysiological recordings in non-human primates, including simultaneous recordings in multiple brain regions, have recently begun to reveal the pulvinar's functional contributions to selective attention. These new findings suggest that the pulvinar is critical for the efficient transmission of sensory information within and between cortical regions, both synchronizing cortical activity across brain regions and controlling cortical excitability. These new findings further suggest that the pulvinar's influence on cortical processing is embedded in a dynamic selection process that balances sensory and motor functions within the large-scale network that directs selective attention.

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.

Don't stop me now: Hampered retrieval of action plans following interruptions

How can we retrieve action plans in working memory (WM) after being distracted or interrupted? The present EEG study investigated this question using a WM task in which a random sequence of single numbers (1-4 and 6-9) was presented. In a given trial, participants had to decide whether the number presented in the preceding trial was odd or even. Additionally, interfering stimuli were randomly presented in 25% of all trials, requiring the participants to either ignore a colored number (distraction) or respond to it (interruption) while maintaining the previously formed action plan in WM. Our results revealed a detrimental impact of interruptions on WM performance in trials after interrupting stimuli compared to trials without a preceding interference. This was reflected in decreased task accuracy and reduced stimulus- and response-locked P3b amplitudes potentially indicating a hampered reactivation of stimulus-response links. Moreover, decreased contralateral mu suppression prior to a given response highlighted an impaired response preparation following interruptions. Distractions, on the other hand, did not negatively affect task performance but were followed by faster responses in subsequent trials compared to trials without prior interference. This result pattern was supported by stronger contralateral mu suppression indicating a facilitated response preparation. Overall, these results suggest that action representations in WM are resistant to distractions but do suffer from interruptions that disrupt or interfere with their implementation. We thus propose that the possibility of adequately preparing for an upcoming response is essential for behavioral guidance in the presence of external interference.

Investigating the effects of pre-stimulus cortical oscillatory activity on behavior

Rhythmic brain activity may reflect a functional mechanism that facilitates cortical processing and dynamic interareal interactions and thereby give rise to complex behavior. Using magnetoencephalography (MEG), we investigated rhythmic brain activity in a brain-wide network and their relation to behavior, while human subjects executed a variant of the Simon task, a simple stimulus-response task with well-studied behavioral effects. We hypothesized that the faster reaction times (RT) on stimulus-response congruent versus incongruent trials are associated with oscillatory power changes, reflecting a change in local cortical activation. Additionally, we hypothesized that the faster reaction times for trials following instances with the same stimulus-response contingency (the so-called Gratton effect) is related to contingency-induced changes in the state of the network, as measured by differences in local spectral power and interareal phase coherence. This would be achieved by temporarily upregulating the connectivity strength between behaviorally relevant network nodes. We identified regions-of-interest that differed in local synchrony during the response phase of the Simon task. Within this network, spectral power in none of the nodes in either of the studied frequencies was significantly different in the pre-cue window of the subsequent trial. Nor was there a significant difference in coherence between the task-relevant nodes that could explain the superior behavioral performance after compatible consecutive trials.

Distinct Oscillatory Dynamics Underlie Different Components of Hierarchical Cognitive Control

Hierarchical cognitive control enables us to execute actions guided by abstract goals. Previous research has suggested that neuronal oscillations at different frequency bands are associated with top-down cognitive control; however, whether distinct neural oscillations have similar or different functions for cognitive control is not well understood. The aim of the current study was to investigate the oscillatory neuronal mechanisms underlying two distinct components of hierarchical cognitive control: the level of abstraction of a rule, and the number of rules that must be maintained (set-size). We collected EEG data in 31 men and women who performed a hierarchical cognitive control task that varied in levels of abstraction and set-size. Results from time-frequency analysis in frontal electrodes showed an increase in theta amplitude for increased set-size, whereas an increase in δ was associated with increased abstraction. Both theta and δ amplitude correlated with behavioral performance in the tasks but in an opposite manner: theta correlated with response time slowing when the number of rules increased, whereas δ correlated with response time when rules became more abstract. Phase-amplitude coupling analysis revealed that δ phase-coupled with β amplitude during conditions with a higher level of abstraction, whereby beta band may potentially represent motor output that was guided by the δ phase. These results suggest that distinct neural oscillatory mechanisms underlie different components of hierarchical cognitive control.SIGNIFICANCE STATEMENT Cognitive control allows us to perform immediate actions while maintaining more abstract, overarching goals in mind and to choose between competing actions. We found distinct oscillatory signatures that correspond to two different components of hierarchical control: the level of abstraction of a rule and the number of rules in competition. An increase in the level of abstraction was associated with δ oscillations, whereas theta oscillations were observed when the number of rules increased. Oscillatory amplitude correlated with behavioral performance in the task. Finally, the expression of β amplitude was coordinated via the phase of δ oscillations, and theta phase-coupled with γ amplitude. These results suggest that distinct neural oscillatory mechanisms underlie different components of hierarchical cognitive control.

Melatonin effects on EEG activity during non-rapid eye movement sleep in mild-to-moderate Alzheimer´s disease: a pilot study

INTRODUCTION

There is evidence to suggest that melatonin diminishes non-rapid eye movement sleep (NREMS) latency in patients with Alzheimer´s disease (AD). However, melatonin's effects on cortical activity during NREMS in AD have not been studied. The objective of this research was to analyze the effects of melatonin on cortical activity during the stages of NREMS in 8 mild-to-moderate AD patients that received 5-mg of fast-release melatonin.

METHODS

During a single-blind, placebo-controlled crossover study, polysomnographic recordings were obtained from C3-A1, C4-A2, F7-T3, F8-T4, F3-F4 and O1-O2. Also, the relative power (RP) and EEG coherences of the delta, theta, alpha1, alpha2, beta1, beta2 and gamma bands were calculated during NREMS-1, NREMS-2 and NREMS-3. These sleep latencies and all EEG data were then compared between the placebo and melatonin conditions.

RESULTS

During NREMS-2, a significant RP increase was observed in the theta band of the left-central hemisphere. During NREMS-3, significant RP decreases in the beta bands were recorded in the right-central hemisphere, compared to the placebo group. After melatonin administration, significant decreases of EEG coherences in the beta2, beta1 and gamma bands were observed in the right hemisphere during NREMS-3.

DISCUSSION

We conclude that short NREMS onset related to melatonin intake in AD patients is associated with a significant RP increase in the theta band and a decrease in RP and EEG coherences in the beta and gamma bands during NREMS-3. These results suggest that the GABAergic pathways are preserved in mild-to-moderate AD.

EEG Correlates of Involuntary Cognitions in the Reflexive Imagery Task

The Reflexive Imagery Task (RIT) reveals that the activation of sets can result in involuntary cognitions that are triggered by external stimuli. In the basic RIT, subjects are presented with an image of an object (e.g., CAT) and instructed to not think of the name of the object. Involuntary subvocalizations of the name (the RIT effect) arise on roughly 80% of the trials. We conducted an electroencephalography (EEG) study to explore the neural correlates of the RIT effect. Subjects were presented with one object at a time in one condition and two objects simultaneously in another condition. Five regions were defined by electrode sites: frontal (F3-F4), parietal (P3-P4), temporal (T3-T4), right hemisphere (F4-P4), and left hemisphere (F3-P3). We focused on the alpha (8-13 Hz), beta (13-30 Hz), delta (0.01-4 Hz), and theta (4-8 Hz) frequencies.

Spatiotemporal and spectral dynamics of multi-item working memory as revealed by the n-back task using MEG

Multi‐item working memory (WM) is a complex cognitive function thought to arise from specific frequency band oscillations and their interactions. While some theories and consistent findings have been established, there is still a lot of unclarity about the sources, temporal dynamics, and roles of event‐related fields (ERFs) and theta, alpha, and beta oscillations during WM activity. In this study, we performed an extensive whole‐brain ERF and time‐frequency analysis on n‐back magnetoencephalography data from 38 healthy controls. We identified the previously unknown sources of the n‐back M300, the right inferior temporal and parahippocampal gyrus and left inferior temporal gyrus, and frontal theta power increase, the orbitofrontal cortex. We shed new light on the role of the precuneus during n‐back activity, based on an early ERF and theta power increase, and suggest it to be a crucial link between lower‐level and higher‐level information processing. In addition, we provide strong evidence for the central role of the hippocampus in multi‐item WM behavior through the dynamics of theta and alpha oscillatory changes. Almost simultaneous alpha power decreases observed in the hippocampus and occipital fusiform gyri, regions known to be involved in letter processing, suggest that these regions together enable letter recognition, encoding and storage in WM. In summary, this study offers an extensive investigation into the spatial, temporal, and spectral characteristics of n‐back multi‐item WM activity.

Functional Specialization in the Attention Network

Spatial attention is comprised of neural mechanisms that boost sensory processing at a behaviorally relevant location while filtering out competing information. The present review examines functional specialization in the network of brain regions that directs such preferential processing. This attention network includes both cortical (e.g., frontal and parietal cortices) and subcortical (e.g., the superior colliculus and the pulvinar nucleus of the thalamus) structures. Here, we piece together existing evidence that these various nodes of the attention network have dissociable functional roles by synthesizing results from electrophysiology and neuroimaging studies. We describe functional specialization across several dimensions (e.g., at different processing stages and within different behavioral contexts), while focusing on spatial attention as a dynamic process that unfolds over time. Functional contributions from each node of the attention network can change on a moment-to-moment timescale, providing the necessary cognitive flexibility for sampling from highly dynamic environments.

An exploration of neural dynamics of motor imagery for people with amyotrophic lateral sclerosis

OBJECTIVE

Studies of the neuropathological effects of amyotrophic lateral sclerosis (ALS) on the underlying motor system have investigated abnormalities in the magnitude and timing of the event-related desynchronization (ERD) and synchronization (ERS) during motor execution (ME). However, the spatio-spectral-temporal dynamics of these sensorimotor oscillations during motor imagery (MI) have not been fully explored for these patients. This study explores the neural dynamics of sensorimotor oscillations for ALS patients during MI by quantifying ERD/ERS features in frequency, time, and space.

APPROACH

Electroencephalogram (EEG) data were recorded from six patients with ALS and 11 age-matched healthy controls (HC) while performing a MI task. ERD/ERS features were extracted using wavelet-based time-frequency analysis and compared between the two groups to quantify the abnormal neural dynamics of ALS in terms of both time and frequency. Topographic correlation analysis was conducted to compare the localization of MI activity between groups and to identify subject-specific frequencies in the µ and β frequency bands.

MAIN RESULTS

Overall, reduced and delayed ERD was observed for ALS patients, particularly during right-hand MI. ERD features were also correlated with ALS clinical scores, specifically disease duration, bulbar, and cognitive functions.

SIGNIFICANCE

The analyses in this study quantify abnormalities in the magnitude and timing of sensorimotor oscillations for ALS patients during MI tasks. Our findings reveal notable differences between MI and existing results on ME in ALS. The observed alterations are speculated to reflect disruptions in the underlying cortical networks involved in MI functions. Quantifying the neural dynamics of MI plays an important role in the study of EEG-based cortical markers for ALS.

Resting state oscillations suggest a motor component of Parkinson's Impulse Control Disorders

OBJECTIVES

Impulse control disorders (ICDs) in Parkinson's disease (PD) have been associated with cognitive impulsivity and dopaminergic dysfunction and treatment. The present study tests the neglected hypothesis that the neurofunctional networks involved in motor impulsivity might also be dysfunctional in PD-ICDs.

METHODS

We performed blind spectral analyses of resting state electroencephalographic (EEG) data in PD patients with and without ICDs to probe the functional integrity of all cortical networks. Analyses were performed directly at the source level after blind source separation. Discrete differences between groups were tested by comparing patients with and without ICDs. Gradual dysfunctions were assessed by means of correlations between power changes and clinical scores reflecting ICD severity (QUIP score).

RESULTS

Spectral signatures of ICDs were found in the medial prefrontal cortex, the dorsal anterior cingulate and the supplementary motor area, in the beta and gamma bands. Beta power changes in the supplementary motor area were found to predict ICDs severity.

CONCLUSION

ICDs are associated with abnormal activity within frequency bands and cortical circuits supporting the control of motor response inhibition.

SIGNIFICANCE

These results bring to the forefront the need to consider, in addition to the classical interpretation based on aberrant mesocorticolimbic reward processing, the issue of motor impulsivity in PD-ICDs and its potential implications for PD therapy.

Brain Inhibitory Mechanisms Are Involved in the Processing of Sentential Negation, Regardless of Its Content. Evidence From EEG Theta and Beta Rhythms

The two-step process account of negation understanding posits an initial representation of the negated events, followed by a representation of the actual state of events. On the other hand, behavioral and neurophysiological studies provided evidence that linguistic negation suppresses or reduces the activation of the negated events, contributing to shift attention to the actual state of events. However, the specific mechanism of this suppression is poorly known. Recently, based on the brain organization principle of neural reuse (Anderson, 2010), it has been proposed that understanding linguistic negation partially relies upon the neurophysiological mechanisms of response inhibition. Specifically, it was reported that negated action-related sentences modulate EEG signatures of response inhibition (de Vega et al., 2016; Beltrán et al., 2018). In the current EEG study, we ponder whether the reusing of response inhibition processes by negation is constrained to action-related contents or consists of a more general-purpose mechanism. To this end, we employed the same dual-task paradigm as in our prior study—a Go/NoGo task embedded into a sentence comprehension task—but this time including both action and non-action sentences. The results confirmed that the increase of theta power elicited by NoGo trials was modulated by negative sentences, compared to their affirmative counterparts, and this polarity effect was statistically similar for both action- and non-action-related sentences. Thus, a general-purpose inhibitory control mechanism, rather than one specific for action language, is likely operating in the comprehension of sentential negation to produce the transition between alternative representations.

A Dynamic Interplay within the Frontoparietal Network Underlies Rhythmic Spatial Attention

Classic studies of spatial attention assumed that its neural and behavioral effects were continuous over time. Recent behavioral studies have instead revealed that spatial attention leads to alternating periods of heightened or diminished perceptual sensitivity. Yet, the neural basis of these rhythmic fluctuations has remained largely unknown. We show that a dynamic interplay within the macaque frontoparietal network accounts for the rhythmic properties of spatial attention. Neural oscillations characterize functional interactions between the frontal eye fields (FEF) and the lateral intraparietal area (LIP), with theta phase (3-8 Hz) coordinating two rhythmically alternating states. The first is defined by FEF-dominated beta-band activity, associated with suppressed attentional shifts, and LIP-dominated gamma-band activity, associated with enhanced visual processing and better behavioral performance. The second is defined by LIP-specific alpha-band activity, associated with attenuated visual processing and worse behavioral performance. Our findings reveal how network-level interactions organize environmental sampling into rhythmic cycles.

Effortful verb retrieval from semantic memory drives beta suppression in mesial frontal regions involved in action initiation

The contribution of the motor cortex to the semantic retrieval of verbs remains a subject of debate in neuroscience. Here, we examined whether additional engagement of the cortical motor system was required when access to verbs semantics was hindered during a verb generation task. We asked participants to produce verbs related to presented noun cues that were either strongly associated with a single verb to prompt fast and effortless verb retrieval, or were weakly associated with multiple verbs and more difficult to respond to. Using power suppression of magnetoencephalography beta oscillations (15-30 Hz) as an index of cortical activation, we performed a whole-brain analysis in order to identify the cortical regions sensitive to the difficulty of verb semantic retrieval. Highly reliable suppression of beta oscillations occurred 250 ms after the noun cue presentation and was sustained until the onset of verbal response. This was localized to multiple cortical regions, mainly in the temporal and frontal lobes of the left hemisphere. Crucially, the only cortical regions where beta suppression was sensitive to the task difficulty, were the higher order motor areas on the medial and lateral surfaces of the frontal lobe. Stronger activation of the premotor cortex and supplementary motor area accompanied the effortful verb retrieval and preceded the preparation of verbal responses for more than 500 ms, thus, overlapping with the time window of verb retrieval from semantic memory. Our results suggest that reactivation of verb-related motor plans in higher order motor circuitry promotes the semantic retrieval of target verbs.

Attenuated NoGo-related beta desynchronisation and synchronisation in Parkinson's disease revealed by magnetoencephalographic recording

Parkinson’s disease (PD) is a neurodegenerative disorder characterised by motor abnormalities. Many non-demented patients with PD have cognitive impairment especially in executive functions. Using magnetoencephalographic (MEG) recording combined with event-related desynchronisation/synchronisation (ERD/ERS) analysis, we investigated cortical executive functions during a Go/NoGo task in PD patients and matched healthy subjects. PD patients had a longer reaction time in the Go condition and had a higher error ratio in both Go and NoGo conditions. The MEG analysis showed that the PD patients had a significant reduction in beta ERD during the NoGo condition and in beta ERS during both Go and NoGo conditions compared with the healthy subjects (all p < 0.05). Moreover, in the Go condition, the onsets of beta ERD and ERS were delayed in PD patients. Notably, NoGo ERS was negatively correlated with the Unified Parkinson’s Disease Rating Scale (UPDRS) score in PD patients. The present study demonstrated abnormalities in motor programming, response inhibition, and frontal inhibitory modulation in PD. Further extensive investigations are necessary to confirm the longitudinal treatment responses in PD.

Beta band oscillatory deficits during working memory encoding in adolescents with attention-deficit hyperactive disorder

Attention-deficit hyperactivity disorder (ADHD) is a neurobehavioural disorder, characterized by symptoms of inattention and/or hyperactivity/impulsivity, in addition to various cognitive deficits, including working memory impairments. This pathology arises from a complex constellation of genetic, structural and neurotransmission abnormalities, which give rise to the aberrant electrophysiological patterns evident in patients with ADHD. Among such, findings have consistently provided support in favour of weaker power across the beta frequency range. Evidence has also emerged that beta rhythmic decrements are linked to working memory encoding. The catecholaminergic modulation of both working memory and beta oscillations may suggest that the link between the two might be rooted at the neurotransmission level. Studies have consistently shown that ADHD involves significant catecholaminergic dysregulation, which is also supported by other clinical studies that demonstrate stimulant-induced amelioration of ADHD symptomology. In this study, we explore the possible ways that might relate ADHD, working memory, beta rhythms and catecholaminergic signalling altogether by investigating the integrity of encoding-relevant electroencephalographic beta rhythms in medication-naïve and stimulant-medicated adolescent patients. The aberrant parietal and frontal encoding-related beta rhythm revealed in the ADHD patients together with a working memory (WM) deficit as observed herein was reversed by methylphenidate in the latter case but not with regard to the beta rhythm. This finding per se raises the issue of the role played by beta rhythms in the WM deficits associated with ADHD.

A Parametric Time-Frequency Conditional Granger Causality Method Using Ultra-Regularized Orthogonal Least Squares and Multiwavelets for Dynamic Connectivity Analysis in EEGs

OBJECTIVE

This study proposes a new parametric time-frequency conditional Granger causality (TF-CGC) method for high-precision connectivity analysis over time and frequency domain in multivariate coupling nonstationary systems, and applies it to source electroencephalogram (EEG) signals to reveal dynamic interaction patterns in oscillatory neocortical sensorimotor networks.

METHODS

The Geweke's spectral measure is combined with the time-varying autoregressive with exogenous input (TVARX) modeling approach, which uses multiwavelet-based ultra-regularized orthogonal least squares (UROLS) algorithm, aided by adjustable prediction error sum of squares (APRESS), to obtain high-resolution time-varying CGC representations. The UROLS-APRESS algorithm, which adopts both the regularization technique and the ultra-least squares criterion to measure not only the signal themselves, but also the weak derivatives of them, is a novel powerful method in constructing time-varying models with good generalization performance, and can accurately track smooth and fast changing causalities. The generalized measurement based on CGC decomposition is able to eliminate indirect influences in multivariate systems.

RESULTS

The proposed method is validated on two simulations, and then applied to source level motor imagery (MI) EEGs, where the predicted distributions are well recovered with high TF precision, and the detected connectivity patterns of MI-EEGs are physiologically interpretable and yield new insights into the dynamical organization of oscillatory cortical networks.

CONCLUSION

Experimental results confirm the effectiveness of the TF-CGC method in tracking rapidly varying causalities of EEG-based oscillatory networks.

SIGNIFICANCE

The novel TF-CGC method is expected to provide important information of neural mechanisms of perception and cognition.

Distinct online and offline effects of alpha and beta transcranial alternating current stimulation (tACS) on continuous bimanual performance and task-set switching

In the present study we examined the effect of bihemispheric in-phase synchronization of motor cortical rhythms on complex bimanual coordination. Twenty young healthy volunteers received 10 Hz or 20 Hz tACS in a double-blind crossover design while performing a bimanual task-set switching paradigm. We used a bilateral high-density montage centred over the hand knob representation within the primary motor cortices to apply tACS time-locked to the switching events. Online tACS in either frequency led to faster but more erroneous switching transitions compared to trials without active stimulation. When comparing stimulation frequencies, 10 Hz stimulation resulted in higher error rates and slower switching transitions than 20 Hz stimulation. Furthermore, the stimulation frequencies showed distinct carry-over effects in trials following stimulation trains. Non-stimulated switching transitions were generally faster but continuous performance became more erroneous over time in the 20 Hz condition. We suggest that the behavioural effects of bifocal in-phase tACS are explained by online synchronization of long-range interhemispheric sensorimotor oscillations, which impacts on interhemispheric information flow and the top-down control required for flexible control of complex bimanual actions. Different stimulation frequencies may lead to distinct offline effects, which potentially accumulate over time and therefore need to be taken into account when evaluating subsequent performance.

Electrocorticographic changes in field potentials following natural somatosensory percepts in humans

OBJECTIVE

Restoration of somatosensory deficits in humans requires a clear understanding of the neural representations of percepts. To characterize the cortical response to naturalistic somatosensation, we examined field potentials in the primary somatosensory cortex of humans.

METHODS

Four patients with intractable epilepsy were implanted with subdural electrocorticography (ECoG) electrodes over the hand area of S1. Three types of stimuli were applied, soft-repetitive touch, light touch, and deep touch. Power in the alpha (8-15 Hz), beta (15-30 Hz), low-gamma (30-50 Hz), and high-gamma (50-125 Hz) frequency bands were evaluated for significance.

RESULTS

Seventy-seven percent of electrodes over the hand area of somatosensory cortex exhibited changes in these bands. High-gamma band power increased for all stimuli, with concurrent alpha and beta band power decreases. Earlier activity was seen in these bands in deep touch and light touch compared to soft touch.

CONCLUSIONS

These findings are consistent with prior literature and suggest a widespread response to focal touch, and a different encoding of deeper pressure touch than soft touch.

Estimation of Vector Autoregressive Parameters and Granger Causality From Noisy Multichannel Data

OBJECTIVE

The objective of this paper is to estimate the parameters of a multivariate autoregressive process from noisy multichannel data.

METHODS

Using a multivariate generalization of the Cadzow method, we propose a new method for estimating autoregressive parameters from noisy data: the nonlinear Cadzow method.

RESULTS

We show that our method outperforms existing multivariate methods such as higher order Yule-Walker method and Kalman EM method on simulated data. We apply our method to estimation of Granger causality from noisy data and again obtain superior results compared to previous methods. Finally, when applied to experimental local field potential data from monkey somatosensory and motor cortical areas, our method produces results consistent with cortical physiology.

CONCLUSION

The proposed nonlinear Cadzow method outperforms existing methods in obtaining denoised estimates of multivariate autoregressive parameters.

SIGNIFICANCE

Since multichannel recordings have become commonplace in biomedical applications ranging from discovering functional connectivity in the brain to speech data analysis and these recordings are inevitably contaminated by measurement noise, we believe our method has the potential for significant impact.

A Rhythmic Theory of Attention

Recent evidence has demonstrated that environmental sampling is a fundamentally rhythmic process. Both perceptual sensitivity during covert spatial attention and the probability of overt exploratory movements are tethered to theta-band activity (3-8Hz) in the attention network. The fronto-parietal part of this network is positioned at the nexus of sensory and motor functions, directing two tightly coupled processes related to environmental exploration: preferential routing of sensory input and saccadic eye movements. We propose that intrinsic theta rhythms temporally resolve potential functional conflicts by periodically reweighting functional connections between higher-order brain regions and either sensory or motor regions. This rhythmic reweighting alternately promotes either sampling at a behaviorally relevant location (i.e., sensory functions) or shifting to another location (i.e., motor functions).

Cortical beta power reflects decision dynamics and uncovers multiple facets of post-error adaptation

Adapting to errors quickly is essential for survival. Reaction slowing after errors is commonly observed but whether this slowing is adaptive or maladaptive is unclear. Here, we analyse a large dataset from a flanker task using two complementary approaches: a multistage drift-diffusion model, and the lateralisation of EEG beta power as a time-resolved index of choice formation. Fitted model parameters and their independently measured neuronal proxies in beta power convergently show a complex interplay of multiple mechanisms initiated after mistakes. Suppression of distracting evidence, response threshold increase, and reduction of evidence accumulation cause slow and accurate post-error responses. This data provides evidence for both adaptive control and maladaptive orienting after errors yielding an adaptive net effect – a decreased likelihood to repeat mistakes. Generally, lateralised beta power provides a non-invasive readout of action selection for the study of speeded cognitive control processes.

People slow down reactions after errors, yet it is debated whether the mechanisms behind this slowing are beneficial for future performance. Here, the authors show that EEG measures converge with model predictions supporting a complex but overall beneficial mechanism of post-error slowing.

Working Memory 2.0

Working memory is the fundamental function by which we break free from reflexive input-output reactions to gain control over our own thoughts. It has two types of mechanisms: online maintenance of information and its volitional or executive control. Classic models proposed persistent spiking for maintenance but have not explicitly addressed executive control. We review recent theoretical and empirical studies that suggest updates and additions to the classic model. Synaptic weight changes between sparse bursts of spiking strengthen working memory maintenance. Executive control acts via interplay between network oscillations in gamma (30-100 Hz) in superficial cortical layers (layers 2 and 3) and alpha and beta (10-30 Hz) in deep cortical layers (layers 5 and 6). Deep-layer alpha and beta are associated with top-down information and inhibition. It regulates the flow of bottom-up sensory information associated with superficial layer gamma. We propose that interactions between different rhythms in distinct cortical layers underlie working memory maintenance and its volitional control.

Modulating functional connectivity with non-invasive brain stimulation for the investigation and alleviation of age-associated declines in response inhibition: A narrative review

Response inhibition, the ability to withhold a dominant and prepotent response following a change in circumstance or sensory stimuli, declines with advancing age. While non-invasive brain stimulation (NiBS) has shown promise in alleviating some cognitive and motor functions in healthy older individuals, NiBS research focusing on response inhibition has mostly been conducted on younger adults. These extant studies have primarily focused on modulating the activity of distinct neural regions known to be critical for response inhibition, including the right inferior frontal gyrus (rIFG) and the pre-supplementary motor area (pre-SMA). However, given that changes in structural and functional connectivity have been associated with healthy aging, this review proposes that NiBS protocols aimed at modulating the functional connectivity between the rIFG and pre-SMA may be the most efficacious approach to investigate-and perhaps even alleviate-age-related deficits in inhibitory control.

Scalable and Robust Tensor Decomposition of Spontaneous Stereotactic EEG Data

OBJECTIVE

Identification of networks from resting brain signals is an important step in understanding the dynamics of spontaneous brain activity. We approach this problem using a tensor-based model.

METHODS

We develop a rank-recursive scalable and robust sequential canonical polyadic decomposition (SRSCPD) framework to decompose a tensor into several rank-1 components. Robustness and scalability are achieved using a warm start for each rank based on the results from the previous rank.

RESULTS

In simulations we show that SRSCPD consistently outperforms the multi-start alternating least square (ALS) algorithm over a range of ranks and signal-to-noise ratios (SNRs), with lower computation cost. When applying SRSCPD to resting in-vivo stereotactic EEG (SEEG) data from two subjects with epilepsy, we found components corresponding to default mode and motor networks in both subjects. These components were also highly consistent within subject between two sessions recorded several hours apart. Similar components were not obtained using the conventional ALS algorithm.

CONCLUSION

Consistent brain networks and their dynamic behaviors were identified from resting SEEG data using SRSCPD.

SIGNIFICANCE

SRSCPD is scalable to large datasets and therefore a promising tool for identification of brain networks in long recordings from single subjects.

Effect of somatosensory and neurofeedback training on balance in older healthy adults: a preliminary investigation

The aim of this study was to assess the effectiveness of balance training with somatosensory and neurofeedback training on dynamic and static balance in healthy, elderly adults. The sample group consisted of 45 healthy adults randomly assigned to one of the three test groups: somatosensory, neurofeedback, and a control. Individualization of the balance program started with pre-tests for static and dynamic balances. Each group had 15- and 30-min training sessions. All groups were tested for static (postural stability) and dynamic balances (Berg Balance Scale) in acquisition and transfer tests (fall risk of stability and timed up and go). Improvements in static and dynamic balances were assessed by somatosensory and neurofeedback groups and then compared with the control group. Results indicated significant improvements in static and dynamic balances in both test groups in the acquisition test. Results revealed a significant improvement in the transfer test in the neurofeedback and somatosensory groups, in static and dynamic conditions, respectively. The findings suggest that these methods of balance training had a significant influence on balance. Both the methods are appropriate to prevent falling in adults. Neurofeedback training helped the participants to learn static balance, while somatosensory training was effective on dynamic balance learning. Further research is needed to assess the effects of longer and discontinuous stimulation with somatosensory and neurofeedback training on balance in elderly adults.

Performance-informed EEG analysis reveals mixed evidence for EEG signatures unique to the processing of time

Certain EEG components (e.g., the contingent negative variation, CNV, or beta oscillations) have been linked to the perception of temporal magnitudes specifically. However, it is as of yet unclear whether these EEG components are really unique to time perception or reflect the perception of magnitudes in general. In the current study we recorded EEG while participants had to make judgments about duration (time condition) or numerosity (number condition) in a comparison task. This design allowed us to directly compare EEG signals between the processing of time and number. Stimuli consisted of a series of blue dots appearing and disappearing dynamically on a black screen. Each stimulus was characterized by its duration and the total number of dots that it consisted of. Because it is known that tasks like these elicit perceptual interference effects that we used a maximum-likelihood estimation (MLE) procedure to determine, for each participant and dimension separately, to what extent time and numerosity information were taken into account when making a judgement in an extensive post hoc analysis. This approach enabled us to capture individual differences in behavioral performance and, based on the MLE estimates, to select a subset of participants who suppressed task-irrelevant information. Even for this subset of participants, who showed no or only small interference effects and thus were thought to truly process temporal information in the time condition and numerosity information in the number condition, we found CNV patterns in the time-domain EEG signals for both tasks that was more pronounced in the time-task. We found no substantial evidence for differences between the processing of temporal and numerical information in the time–frequency domain.

Task-Relevant Information Modulates Primary Motor Cortex Activity Before Movement Onset

Monkey neurophysiology research supports the affordance competition hypothesis (ACH) proposing that cognitive information useful for action selection is integrated in sensorimotor areas. In this view, action selection would emerge from the simultaneous representation of competing action plans, in parallel biased by relevant task factors. This biased competition would take place up to primary motor cortex (M1). Although ACH is plausible in environments affording choices between actions, its relevance for human decision making is less clear. To address this issue, we designed an functional magnetic resonance imaging (fMRI) experiment modeled after monkey neurophysiology studies in which human participants processed cues conveying predictive information about upcoming button presses. Our results demonstrate that, as predicted by the ACH, predictive information (i.e., the relevant task factor) biases activity of primary motor regions. Specifically, first, activity before movement onset in contralateral M1 increases as the competition is biased in favor of a specific button press relative to activity in ipsilateral M1. Second, motor regions were more tightly coupled with fronto-parietal regions when competition between potential actions was high, again suggesting that motor regions are also part of the biased competition network. Our findings support the idea that action planning dynamics as proposed in the ACH are valid both in human and non-human primates.