Ongoing neural oscillations influence behavior and sensory representations by suppressing neuronal excitability

Neural activity is modulated by spontaneous and volitionally controlled breathing

Recent studies have provided evidence regarding respiration-brain coupling, but our understanding of how continuously varying dynamics of breathing modulate neural activity remains incomplete. We examined whether the neural state differs between spontaneous and volitionally controlled breathing and across the phases of breathing, inspiration and expiration. Magnetoencephalography (MEG) with a respiratory belt was used to record cortical oscillatory activity during spontaneous, deep, and square breathing (n = 33). Additionally, self-report measures of mood and arousal were applied to assess changes in the psychological state during the breathing techniques. Alpha power was suppressed during inspiration and increased during expiration (p < .01) indicating dynamically fluctuating neural states across the respiratory cycle. This effect was observed in the sensorimotor areas during both spontaneous and volitionally controlled deep breathing. Compared to spontaneous and volitionally controlled square breathing, alpha power increased during deep breathing (p < .01) within a cortical network extending to frontal and temporal areas. We also observed a steeper aperiodic slope and a broadband shift in the power spectrum in the left superior frontal gyrus during square breathing in comparison with spontaneous breathing suggesting that not only oscillatory activity but also the more general spectral characteristics of ongoing neural activity are modulated by the rate, depth, and pattern of breathing. Self-reported mood and arousal did not differ across the breathing techniques. Altogether, we demonstrate that neural activity is modulated by the phases of breathing and can also be volitionally influenced by varying the rate, depth, and pattern of breathing.

Distinct Alpha Networks Modulate Different Aspects of Perceptual Decision-Making

Why do we sometimes perceive a faint stimulus but miss it at other times? One explanation is that conscious perception fluctuates with the brain's internal state, influencing how external stimuli are processed. Ongoing brain oscillations in the alpha band (8-13 Hz), thought to reflect neuronal excitability levels1-5 and play a role in functional inhibition6,7, have been shown as a key contributor to such perceptual variability8,9. Under high alpha conditions, faint stimuli are more likely to be missed8. Some studies suggested alpha oscillations modulate perceptual criterion ( c ) 10-14, shifting the threshold for interpreting sensory information; while others (including our prior work15) suggested alpha modulates sensitivityd ' 15-19, changing the precision of sensory encoding. Few studies observed modulations in both metrics, making these results appear mutually exclusive. Most studies have focused solely on overall alpha activity-whether within a region of interest or across the whole brain-and overlooked the coexistence of multiple distinct alpha networks20-26, which fluctuate in terms of predominance20,27,28 and adapt to behavioural demands29,30. Hence, it remained unclear whether different networks' contributions to perception vary with their momentary state. Here, aiming to characterize how different alpha networks influence perceptual decision-making, we analyzed magnetoencephalography (MEG) data recorded while participants performed a visual detection task with threshold-level stimuli. We found that while the visual alpha network modulates perceptual sensitivity, the sensorimotor alpha network modulates criterion in perceptual decision-making. These findings reconcile previous conflicting results and highlight the functional diversity of alpha networks in shaping perception.

High-Frequency rTMS Improves Visual Working Memory in Patients With aMCI: A Cognitive Neural Mechanism Study

BACKGROUND

Visual working memory (VWM), which is an essential component of higher cognitive processes, declines with age and is associated with the progression from amnestic mild cognitive impairment (aMCI) to Alzheimer's disease (AD). Cognitive impairment, particularly in VWM, is prominent in aMCI and may indicate disease progression. This study investigates the cognitive neural mechanisms responsible for VWM impairment in aMCI, with a focus on identifying the VWM processing stages affected. The study targets the dorsolateral prefrontal cortex (DLPFC) for repetitive transcranial magnetic stimulation (rTMS) to investigate its influence on VWM in aMCI patients. The role of the DLPFC in the top-down control of VWM processing is central to understanding rTMS effects on the stages of information processing in aMCI-related VWM impairments.

METHODS

A 7-day rTMS intervention was performed in 25 aMCI patients and 15 healthy elderly controls to investigate its effects on VWM and cognitive functions. Tasks included VWM change detection, digital symbol transformation, and the Stroop task for attention and executive functions. EEG analyses consisting of ERP, ERSP, and functional connectivity (wPLI) were integrated. The first part of the study addressed the cognitive neural mechanism of VWM impairment in aMCI and differentiated the processing stages using EEG. The second part investigated the effects of rTMS on EEG processing at different VWM stages and revealed cognitive neural mechanisms that improve visual working memory in aMCI.

RESULTS

The results indicated a significant deterioration of VWM tasks in aMCI, especially in accuracy and memory capacity, with prolonged reaction time and increased duration of the Stroop task. In the VWM memory encoding phase, N2pc amplitude, α-oscillation in the parieto-occipital region, and θ-band synchronization in the frontoparietal connectivity decreased. Conversely, rTMS improved N2pc amplitude, α-oscillation, and θ-band synchronization, which correlated with improved frontoparietal connectivity, parieto-occipital α-oscillation, and attentional capacity.

CONCLUSIONS

Patients with aMCI experience significant deterioration in VWM function, particularly during the encoding phase. This deterioration manifests in reduced accuracy and capacity of memory performance, accompanied by a significant decrease in N2pc amplitude, alpha oscillations, and theta-band connectivity in frontoparietal and fronto-occipital brain regions. rTMS proves to be a promising intervention that improves VWM, attention, and executive functions. In particular, it supports attention during target selection by increasing N2pc amplitude during encoding, enhancing alpha oscillations for better suppression of irrelevant information, and increasing synchronization in frontoparietal and occipital functional connectivity, which ultimately improves visual working memory.

Functional segregation of rostral and caudal hippocampus in associative memory

Introduction

The hippocampus plays a crucial role in episodic memory. Given its complexity, the hippocampus participates in multiple aspects of higher cognitive functions, among which are semantics-based encoding and retrieval. However, the "where," "when" and "how" of distinct aspects of memory processing in the hippocampus are still under debate.

Methods

Here, we employed a visual associative memory task that involved encoding three levels of subjective congruence to delineate the differential involvement of the rostral and caudal portions (also referred as anterior/posterior portions) of the human hippocampus during memory encoding, recognition and associative recall.

Results

Through stereo-EEG recordings in epilepsy patients we show that associative memory is reflected by rostral hippocampal activity during encoding, and caudal hippocampal activity during retrieval. In contrast, recognition memory encoding selectively activates the rostral hippocampus. The temporal dynamics of memory processing are manifested by gamma power increase, which partially overlaps with low-frequency power decrease during encoding and retrieval. Congruence levels modulate low-frequency activity prominently in the caudal hippocampus.

Discussion

These findings highlight an anatomical segregation in the hippocampus in accordance with the contributions of its partitions to associative and recognition memory.

Cognitive and neural underpinnings of friend-prioritization in a perceptual matching task

Previous findings of better behavioral responses to self- over other-related stimuli suggest prioritized cognitive processes of self-related information. However, it is unclear whether the processing of information related to important others (e.g.friends) may be prioritized over that related to the self in certain subpopulations and, if yes, whether friend-prioritization and self-prioritization engage distinct cognitive and neural mechanisms. We collected behavioral and electroencephalography (EEG) data from a large sample (N = 1006) during learning associations between shapes and person labels (self or a friend). Analyses of response times and sensitivities revealed two subpopulations who performed better to friend-shape or self-shape associations, respectively (N = 216 for each group). Drift diffusion model (DDM) analyses unraveled faster information acquisition for friend-shape (vs. self-shape) associations in the friend-prioritization group but an opposite pattern in the self-prioritization group. Trial-by-trial regression analyses of EEG data showed that the greater amplitudes of a frontal/central activity at 180-240 ms poststimulus were correlated with faster information acquisition from friend-shape associations in the friend-prioritization group but from self-shape associations in the self-prioritization group. However, the frontal/central neural oscillations at 8-18 Hz during perceptual learning were specifically associated with speed of information acquisition from friend-shape associations in the friend-prioritization-group. Our findings provide evidence for friend-prioritization in perceptual learning in a subpopulation of adults and clarify the underlying cognitive and neural mechanisms.

Oscillatory Brain Activity in the Canonical Alpha-Band Conceals Distinct Mechanisms in Attention

Brain oscillations in the alpha-band (8-14 Hz) have been linked to specific processes in attention and perception. In particular, decreases in posterior alpha-amplitude are thought to reflect activation of perceptually relevant brain areas for target engagement, while alpha-amplitude increases have been associated with inhibition for distractor suppression. Traditionally, these alpha-changes have been viewed as two facets of the same process. However, recent evidence calls for revisiting this interpretation. Here, we recorded MEG/EEG in 32 participants (19 females) during covert visuospatial attention shifts (spatial cues) and two control conditions (neutral cue, no-attention cue), while tracking fixational eye movements. In disagreement with a single, perceptually relevant alpha-process, we found the typical alpha-modulations contra- and ipsilateral to the attention focus to be triple dissociated in their timing, topography, and spectral features: Ipsilateral alpha-increases occurred early, over occipital sensors, at a high alpha-frequency (10-14 Hz) and were expressed during spatial attention (alpha spatial cue > neutral cue). In contrast, contralateral alpha-decreases occurred later, over parietal sensors, at a lower alpha-frequency (7-10 Hz) and were associated with attention deployment in general (alpha spatial and neutral cue < no-attention cue). Additionally, the lateralized early alpha-increases but not alpha-decreases during spatial attention coincided in time with directionally biased microsaccades. Overall, this suggests that the attention-related early alpha-increases and late alpha-decreases reflect distinct, likely reflexive versus endogenously controlled attention mechanisms. We conclude that there is more than one perceptually relevant posterior alpha-oscillation, which need to be dissociated for a detailed account of their roles in perception and attention.

Spontaneous slow cortical potentials and brain oscillations independently influence conscious visual perception

Perceptual awareness results from an intricate interaction between external sensory input and the brain's spontaneous activity. Pre-stimulus ongoing activity influencing conscious perception includes both brain oscillations in the alpha (7 to 14 Hz) and beta (14 to 30 Hz) frequency ranges and aperiodic activity in the slow cortical potential (SCP, <5 Hz) range. However, whether brain oscillations and SCPs independently influence conscious perception or do so through shared mechanisms remains unknown. Here, we addressed this question in 2 independent magnetoencephalography (MEG) data sets involving near-threshold visual perception tasks in humans using low-level (Gabor patches) and high-level (objects, faces, houses, animals) stimuli, respectively. We found that oscillatory power and large-scale SCP activity influence conscious perception through independent mechanisms that do not have shared variance. In addition, through mediation analysis, we show that pre-stimulus oscillatory power and SCP activity have different relations to pupil size-an index of arousal-in their influences on conscious perception. Together, these findings suggest that oscillatory power and SCPs independently contribute to perceptual awareness, with distinct relations to pupil-linked arousal.

Flexibility of intrinsic neural timescales during distinct behavioral states

Recent neuroimaging studies demonstrate a heterogeneity of timescales prevalent in the brain's ongoing spontaneous activity, labeled intrinsic neural timescales (INT). At the same time, neural timescales also reflect stimulus- or task-related activity. The relationship of the INT during the brain's spontaneous activity with their involvement in task states including behavior remains unclear. To address this question, we combined calcium imaging data of spontaneously behaving mice and human electroencephalography (EEG) during rest and task states with computational modeling. We obtained four primary findings: (i) the distinct behavioral states can be accurately predicted from INT, (ii) INT become longer during behavioral states compared to rest, (iii) INT change from rest to task is correlated negatively with the variability of INT during rest, (iv) neural mass modeling shows a key role of recurrent connections in mediating the rest-task change of INT. Extending current findings, our results show the dynamic nature of the brain's INT in reflecting continuous behavior through their flexible rest-task modulation possibly mediated by recurrent connections.

Enhanced Correlation between Arousal and Infra-Slow Brain Activity in Experienced Meditators

BACKGROUND/OBJECTIVES

Meditation induces changes in the nervous system, which presumably underpin positive psychological and physiological effects. Such neural changes include alterations in the arousal fluctuation, as well as in infraslow brain activity (ISA, <0.1 Hz). Furthermore, it is known that fluctuations of arousal over time correlate with the oscillatory phase of ISA. However, whether this arousal-ISA correlation changes after meditation practices remains unanswered.; Methods: The present study aims to address this question by analyzing a publicly available electroencephalogram (EEG) dataset recorded during meditation sessions in the groups of experienced meditators and novices. The arousal fluctuation is measured by galvanic skin responses (GSR), and arousal-ISA correlations are measured by phase synchronization between GSR and EEG ISAs.; Results: While both groups exhibit arousal-ISA correlations, experienced meditators display higher correlations than novices. These increased arousal-ISA correlations in experienced meditators manifest more clearly when oscillatory phase differences between GSR and EEG ISAs are either 0 or π radians. As such, we further investigate the characteristics of these phase differences with respect to spatial distribution over the brain. We found that brain regions with the phase difference of either 0 or π radians form distinct spatial clusters, and that these clusters are spatially correlated with functional organization estimated by the principal gradient, based on functional connectivity.; Conclusions: Since increased arousal-ISA correlations reflect enhanced global organization of the central and autonomic nervous systems, our findings imply that the positive effects of meditation might be mediated by enhanced global organization of the nervous system.

Oscillations in an artificial neural network convert competing inputs into a temporal code

The field of computer vision has long drawn inspiration from neuroscientific studies of the human and non-human primate visual system. The development of convolutional neural networks (CNNs), for example, was informed by the properties of simple and complex cells in early visual cortex. However, the computational relevance of oscillatory dynamics experimentally observed in the visual system are typically not considered in artificial neural networks (ANNs). Computational models of neocortical dynamics, on the other hand, rarely take inspiration from computer vision. Here, we combine methods from computational neuroscience and machine learning to implement multiplexing in a simple ANN using oscillatory dynamics. We first trained the network to classify individually presented letters. Post-training, we added temporal dynamics to the hidden layer, introducing refraction in the hidden units as well as pulsed inhibition mimicking neuronal alpha oscillations. Without these dynamics, the trained network correctly classified individual letters but produced a mixed output when presented with two letters simultaneously, indicating a bottleneck problem. When introducing refraction and oscillatory inhibition, the output nodes corresponding to the two stimuli activate sequentially, ordered along the phase of the inhibitory oscillations. Our model implements the idea that inhibitory oscillations segregate competing inputs in time. The results of our simulations pave the way for applications in deeper network architectures and more complicated machine learning problems.

Auditory-motor entrainment and listening experience shape the perceptual learning of concurrent speech

Background

Plasticity from auditory experience shapes the brain's encoding and perception of sound. Though prior research demonstrates that neural entrainment (i.e., brain-to-acoustic synchronization) aids speech perception, how long- and short-term plasticity influence entrainment to concurrent speech has not been investigated. Here, we explored neural entrainment mechanisms and the interplay between short- and long-term neuroplasticity for rapid auditory perceptual learning of concurrent speech sounds in young, normal-hearing musicians and nonmusicians.

Method

Participants learned to identify double-vowel mixtures during ∼45 min training sessions with concurrent high-density EEG recordings. We examined the degree to which brain responses entrained to the speech-stimulus train (∼9 Hz) to investigate whether entrainment to speech prior to behavioral decision predicted task performance. Source and directed functional connectivity analyses of the EEG probed whether behavior was driven by group differences auditory-motor coupling.

Results

Both musicians and nonmusicians showed rapid perceptual learning in accuracy with training. Interestingly, listeners' neural entrainment strength prior to target speech mixtures predicted behavioral identification performance; stronger neural synchronization was observed preceding incorrect compared to correct trial responses. We also found stark hemispheric biases in auditory-motor coupling during speech entrainment, with greater auditory-motor connectivity in the right compared to left hemisphere for musicians (R>L) but not in nonmusicians (R=L).

Conclusions

Our findings confirm stronger neuroacoustic synchronization and auditory-motor coupling during speech processing in musicians. Stronger neural entrainment to rapid stimulus trains preceding incorrect behavioral responses supports the notion that alpha-band (∼10 Hz) arousal/suppression in brain activity is an important modulator of trial-by-trial success in perceptual processing.

State-Dependent tACS Effects Reveal the Potential Causal Role of Prestimulus Alpha Traveling Waves in Visual Contrast Detection

The intricate relationship between prestimulus alpha oscillations and visual contrast detection variability has been the focus of numerous studies. However, the causal impact of prestimulus alpha traveling waves on visual contrast detection remains largely unexplored. In our research, we sought to discern the causal link between prestimulus alpha traveling waves and visual contrast detection across different levels of mental fatigue. Using electroencephalography alongside a visual detection task with 30 healthy adults (13 females; 17 males), we identified a robust negative correlation between prestimulus alpha forward traveling waves (FTWs) and visual contrast threshold (VCT). Inspired by this correlation, we utilized 45/-45° phase-shifted transcranial alternating current stimulation (tACS) in a sham-controlled, double-blind, within-subject experiment with 33 healthy adults (23 females; 10 males) to directly modulate these alpha traveling waves. After the application of 45° phase-shifted tACS, we observed a substantial decrease in FTW and an increase in backward traveling waves, along with a concurrent increase in VCT, compared with the sham condition. These changes were particularly pronounced under a low fatigue state. The findings of state-dependent tACS effects reveal the potential causal role of prestimulus alpha traveling waves in visual contrast detection. Moreover, our study highlights the potential of 45/-45° phase-shifted tACS in cognitive modulation and therapeutic applications.

Beyond task response-Pre-stimulus activity modulates contents of consciousness

The current discussion on the neural correlates of the contents of consciousness (NCCc) focuses mainly on the post-stimulus period of task-related activity. This neglects the substantial impact of the spontaneous or ongoing activity of the brain as manifest in pre-stimulus activity. Does the interaction of pre- and post-stimulus activity shape the contents of consciousness? Addressing this gap in our knowledge, we review and converge two recent lines of findings, that is, pre-stimulus alpha power and pre- and post-stimulus alpha trial-to-trial variability (TTV). The data show that pre-stimulus alpha power modulates post-stimulus activity including specifically the subjective features of conscious contents like confidence and vividness. At the same time, alpha pre-stimulus variability shapes post-stimulus TTV reduction including the associated contents of consciousness. We propose that non-additive rather than merely additive interaction of the internal pre-stimulus activity with the external stimulus in the alpha band is key for contents to become conscious. This is mediated by mechanisms on different levels including neurophysiological, neurocomputational, neurodynamic, neuropsychological and neurophenomenal levels. Overall, considering the interplay of pre-stimulus intrinsic and post-stimulus extrinsic activity across wider timescales, not just evoked responses in the post-stimulus period, is critical for identifying neural correlates of consciousness. This is well in line with both processing and especially the Temporo-spatial theory of consciousness (TTC).

Meditation-type specific reduction in infra-slow activity of electroencephalogram

Purpose

Meditation is renowned for its positive effects on cognitive abilities and stress reduction. It has been reported that the amplitude of electroencephalographic (EEG) infra-slow activity (ISA, < 0.1 Hz) is reduced as the stress level decreases. Consequently, we aimed to determine if EEG ISA amplitude decreases as a result of meditation practice across various traditions.

Methods

To this end, we analyzed an open dataset comprising EEG data acquired during meditation sessions from experienced practitioners in the Vipassana tradition-which integrates elements of focused attention and open monitoring, akin to mindfulness meditation-and in the Himalayan Yoga and Isha Shoonya traditions, which emphasize focused attention and open monitoring, respectively.

Results

A general trend was observed where EEG ISA amplitude tended to decrease in experienced meditators from these traditions compared to novices, particularly significant in the 0.03-0.08 Hz band for Vipassana meditators. Therefore, our analysis focused on this ISA frequency band. Specifically, a notable decrease in EEG ISA amplitude was observed in Vipassana meditators, predominantly in the left-frontal region. This reduction in EEG ISA amplitude was also accompanied by a decrease in phase-amplitude coupling (PAC) between the ISA phase and alpha band (8-12 Hz) amplitude, which implied decreased neural excitability fluctuations.

Conclusion

Our findings suggest that not only does EEG ISA amplitude decrease in experienced meditators from traditions that incorporate both focused attention and open monitoring, but this decrease may also signify a diminished influence of neural excitability fluctuations attributed to ISA.

Temporal-Posterior Alpha Power in Resting-State Electroencephalography as a Potential Marker of Complex Childhood Trauma in Institutionalized Adolescents

The present study explored whether, given the association of temporal alpha with fear circuitry (learning and conditioning), exposure to complex childhood trauma (CCT) is reflected in the temporal-posterior alpha power in resting-state electroencephalography (EEG) in complex trauma-exposed adolescents in a sample of 25 adolescents and similar controls aged 12-17 years. Both trauma and psychopathology were screened or assessed, and resting-state EEG was recorded following a preregistered protocol for data collection. Temporal-posterior alpha power, corresponding to the T5 and T6 electrode locations (international 10-20 system), was extracted from resting-state EEG in both eyes-open and eyes-closed conditions. We found that in the eyes-open condition, temporal-posterior alpha was significantly lower in adolescents exposed to CCT relative to healthy controls, suggesting that childhood trauma exposure may have a measurable impact on alpha oscillatory patterns. Our study highlights the importance of considering potential neural markers, such as temporal-posterior alpha power, to understanding the long-term consequences of CCT exposure in developmental samples, with possible important clinical implications in guiding neuroregulation interventions.

Double Dissociation of Spontaneous Alpha-Band Activity and Pupil-Linked Arousal on Additive and Multiplicative Perceptual Gain

Perception is a probabilistic process dependent on external stimulus properties and one's internal state. However, which internal states influence perception and via what mechanisms remain debated. We studied how spontaneous alpha-band activity (8-13 Hz) and pupil fluctuations impact visual detection and confidence across stimulus contrast levels (i.e., the contrast response function, CRF). In human subjects of both sexes, we found that low prestimulus alpha power induced an "additive" shift in the CRF, whereby stimuli were reported present more frequently at all contrast levels, including contrast of zero (i.e., false alarms). Conversely, prestimulus pupil size had a "multiplicative" effect on detection such that stimuli occurring during large pupil states (putatively corresponding to higher arousal) were perceived more frequently as contrast increased. Signal detection modeling reveals that alpha power changes detection criteria equally across the CRF but not detection sensitivity (d'), whereas pupil-linked arousal modulated sensitivity, particularly for higher contrasts. Interestingly, pupil size and alpha power were positively correlated, meaning that some of the effect of alpha on detection may be mediated by pupil fluctuations. However, pupil-independent alpha still induced an additive shift in the CRF corresponding to a criterion effect. Our data imply that low alpha boosts detection and confidence by an additive factor, rather than by a multiplicative scaling of contrast responses, a profile which captures the effect of pupil-linked arousal. We suggest that alpha power and arousal fluctuations have dissociable effects on behavior. Alpha reflects the baseline level of visual excitability, which can vary independent of arousal.

Distractor inhibition by alpha oscillations is controlled by an indirect mechanism governed by goal-relevant information

The role of alpha oscillations (8-13 Hz) in cognition is intensively investigated. While intracranial animal recordings demonstrate that alpha oscillations are associated with decreased neuronal excitability, it is been questioned whether alpha oscillations are under direct control from frontoparietal areas to suppress visual distractors. We here point to a revised mechanism in which alpha oscillations are controlled by an indirect mechanism governed by the load of goal-relevant information - a view compatible with perceptual load theory. We will outline how this framework can be further tested and discuss the consequences for network dynamics and resource allocation in the working brain.

Inhibitory control in WM gate-opening: Insights from alpha desynchronization and norepinephrine activity under atDCS stimulation

Our everyday activities require the maintenance and continuous updating of information in working memory (WM). To control this dynamic, WM gating mechanisms have been suggested to be in place, but the neurophysiological mechanisms behind these processes are far from being understood. This is especially the case when it comes to the role of oscillatory neural activity. In the current study we combined EEG recordings, and anodal transcranial direct current stimulation (atDCS) and pupil diameter recordings to triangulate neurophysiology, functional neuroanatomy and neurobiology. The results revealed that atDCS, compared to sham stimulation, affected the WM gate opening mechanism, but not the WM gate closing mechanism. The altered behavioral performance was associated with specific changes in alpha band activities (reflected by alpha desynchronization), indicating a role for inhibitory control during WM gate opening. Functionally, the left superior and inferior parietal cortices, were associated with these processes. The findings are the first to show a causal relevance of alpha desynchronization processes in WM gating processes. Notably, pupil diameter recordings as an indirect index of the norepinephrine (NE) system activity revealed that individuals with stronger inhibitory control (as indexed through alpha desynchronization) showed less pupil dilation, suggesting they needed less NE activity to support WM gate opening. However, when atDCS was applied, this connection disappeared. The study suggests a close link between inhibitory controlled WM gating in parietal cortices, alpha band dynamics and the NE system.

Alpha-band Brain Dynamics and Temporal Processing: An Introduction to the Special Focus

For decades, the intriguing connection between the human alpha rhythm (an 8- to 13-Hz oscillation maximal over posterior cortex) and temporal processes in perception has furnished a rich landscape of proposals. The past decade, however, has seen a surge in interest in the topic, bringing new theoretical, analytic, and methodological developments alongside fresh controversies. This Special Focus on alpha-band dynamics and temporal processing provides an up-to-date snapshot of the playing field, with contributions from leading researchers in the field spanning original perspectives, new evidence, comprehensive reviews and meta-analyses, as well as discussion of ongoing controversies and paths forward. We hope that the perspectives captured here will help catalyze future research and shape the pathways toward a theoretically grounded and mechanistic account of the link between alpha dynamics and temporal properties of perception.

Alpha and Beta Oscillations Differentially Support Word Production in a Rule-Switching Task

Research into the role of brain oscillations in basic perceptual and cognitive functions has suggested that the alpha rhythm reflects functional inhibition while the beta rhythm reflects neural ensemble (re)activation. However, little is known regarding the generalization of these proposed fundamental operations to linguistic processes, such as speech comprehension and production. Here, we recorded magnetoencephalography in participants performing a novel rule-switching paradigm. Specifically, Dutch native speakers had to produce an alternative exemplar from the same category or a feature of a given target word embedded in spoken sentences (e.g., for the word "tuna", an exemplar from the same category-"seafood"-would be "shrimp", and a feature would be "pink"). A cue indicated the task rule-exemplar or feature-either before (pre-cue) or after (retro-cue) listening to the sentence. Alpha power during the working memory delay was lower for retro-cue compared with that for pre-cue in the left hemispheric language-related regions. Critically, alpha power negatively correlated with reaction times, suggestive of alpha facilitating task performance by regulating inhibition in regions linked to lexical retrieval. Furthermore, we observed a different spatiotemporal pattern of beta activity for exemplars versus features in the right temporoparietal regions, in line with the proposed role of beta in recruiting neural networks for the encoding of distinct categories. Overall, our study provides evidence for the generalizability of the role of alpha and beta oscillations from perceptual to more "complex, linguistic processes" and offers a novel task to investigate links between rule-switching, working memory, and word production.

Improving Neuroplasticity through Robotic Verticalization Training in Patients with Minimally Conscious State: A Retrospective Study

In disorders of consciousness, verticalization is considered an effective type of treatment to improve motor and cognitive recovery. Our purpose is to investigate neurophysiological effects of robotic verticalization training (RVT) in patients with minimally conscious state (MCS). Thirty subjects affected by MCS due to traumatic or vascular brain injury, attending the intensive Neurorehabilitation Unit of the IRCCS Neurolesi (Messina, Italy), were included in this retrospective study. They were equally divided into two groups: the control group (CG) received traditional verticalization with a static bed and the experimental group (EG) received advanced robotic verticalization using the Erigo device. Each patient was evaluated using both clinical scales, including Levels of Cognitive Functioning (LCF) and Functional Independence Measure (FIM), and quantitative EEG pre (T0) and post each treatment (T1). The treatment lasted for eight consecutive weeks, and sessions were held three times a week, in addition to standard neurorehabilitation. In addition to a notable improvement in clinical parameters, such as functional (FIM) (p < 0.01) and cognitive (LCF) (p < 0.01) outcomes, our findings showed a significant modification in alpha and beta bands post-intervention, underscoring the promising effect of the Erigo device to influence neural plasticity and indicating a noteworthy difference between pre-post intervention. This was not observed in the CG. The observed changes in alpha and beta bands underscore the potential of the Erigo device to induce neural plasticity. The device's custom features and programming, tailored to individual patient needs, may contribute to its unique impact on brain responses.

A disinhibitory circuit mechanism explains a general principle of peak performance during mid-level arousal

Perceptual decision-making is highly dependent on the momentary arousal state of the brain, which fluctuates over time on a scale of hours, minutes, and even seconds. The textbook relationship between momentary arousal and task performance is captured by an inverted U-shape, as put forward in the Yerkes-Dodson law. This law suggests optimal performance at moderate levels of arousal and impaired performance at low or high arousal levels. However, despite its popularity, the evidence for this relationship in humans is mixed at best. Here, we use pupil-indexed arousal and performance data from various perceptual decision-making tasks to provide converging evidence for the inverted U-shaped relationship between spontaneous arousal fluctuations and performance across different decision types (discrimination, detection) and sensory modalities (visual, auditory). To further understand this relationship, we built a neurobiologically plausible mechanistic model and show that it is possible to reproduce our findings by incorporating two types of interneurons that are both modulated by an arousal signal. The model architecture produces two dynamical regimes under the influence of arousal: one regime in which performance increases with arousal and another regime in which performance decreases with arousal, together forming an inverted U-shaped arousal-performance relationship. We conclude that the inverted U-shaped arousal-performance relationship is a general and robust property of sensory processing. It might be brought about by the influence of arousal on two types of interneurons that together act as a disinhibitory pathway for the neural populations that encode the available sensory evidence used for the decision.

Catecholaminergic neuromodulation and selective attention jointly shape perceptual decision-making

Perceptual decisions about sensory input are influenced by fluctuations in ongoing neural activity, most prominently driven by attention and neuromodulator systems. It is currently unknown if neuromodulator activity and attention differentially modulate perceptual decision-making and/or whether neuromodulatory systems in fact control attentional processes. To investigate the effects of two distinct neuromodulatory systems and spatial attention on perceptual decisions, we pharmacologically elevated cholinergic (through donepezil) and catecholaminergic (through atomoxetine) levels in humans performing a visuo-spatial attention task, while we measured electroencephalography (EEG). Both attention and catecholaminergic enhancement improved decision-making at the behavioral and algorithmic level, as reflected in increased perceptual sensitivity and the modulation of the drift rate parameter derived from drift diffusion modeling. Univariate analyses of EEG data time-locked to the attentional cue, the target stimulus, and the motor response further revealed that attention and catecholaminergic enhancement both modulated pre-stimulus cortical excitability, cue- and stimulus-evoked sensory activity, as well as parietal evidence accumulation signals. Interestingly, we observed both similar, unique, and interactive effects of attention and catecholaminergic neuromodulation on these behavioral, algorithmic, and neural markers of the decision-making process. Thereby, this study reveals an intricate relationship between attentional and catecholaminergic systems and advances our understanding about how these systems jointly shape various stages of perceptual decision-making.

Mapping information flow between the inferotemporal and prefrontal cortices via neural oscillations in memory retrieval and maintenance

Interaction between the inferotemporal (ITC) and prefrontal (PFC) cortices is critical for retrieving information from memory and maintaining it in working memory. Neural oscillations provide a mechanism for communication between brain regions. However, it remains unknown how information flow via neural oscillations is functionally organized in these cortices during these processes. In this study, we apply Granger causality analysis to electrocorticographic signals from both cortices of monkeys performing visual association tasks to map information flow. Our results reveal regions within the ITC where information flow to and from the PFC increases via specific frequency oscillations to form clusters during memory retrieval and maintenance. Theta-band information flow in both directions increases in similar regions in both cortices, suggesting reciprocal information exchange in those regions. These findings suggest that specific subregions function as nodes in the memory information-processing network between the ITC and the PFC.

Sensory processing of native and non-native phonotactic patterns in the alpha and beta frequency bands

The phonotactic patterns of one's native language are established within cortical network processing during development. Sensory processing of native language phonotactic patterns established in memory may be modulated by top-down signals within the alpha and beta frequency bands. To explore sensory processing of phonotactic patterns in the alpha and beta frequency bands, electroencephalograms (EEGs) were recorded from native Polish and native English-speaking adults as they listened to spoken nonwords within same and different nonword pairs. The nonwords contained three phonological sequence onsets that occur in the Polish and English languages (/pət/, /st/, /sət/) and one onset sequence /pt/, which occurs in Polish but not in English onsets. Source localization modeling was used to transform 64-channel EEGs into brain source-level channels. Spectral power values in the low frequencies (2-29 Hz) were analyzed in response to the first nonword in nonword pairs within the context of counterbalanced listening-task conditions, which were presented on separate testing days. For the with-task listening condition, participants performed a behavioral task to the second nonword in the pairs. For the without-task condition participants were only instructed to listen to the stimuli. Thus, in the with-task condition, the first nonword served as a cue for the second nonword, the target stimulus. The results revealed decreased spectral power in the beta frequency band for the with-task condition compared to the without-task condition in response to native language phonotactic patterns. In contrast, the task-related suppression effects in response to the non-native phonotactic pattern /pt/ for the English listeners extended into the alpha frequency band. These effects were localized to source channels in left auditory cortex, the left anterior temporal cortex and the occipital pole. This exploratory study revealed a pattern of results that, if replicated, suggests that native language speech perception is supported by modulations in the alpha and beta frequency bands.

The Influence of Prestimulus 1/f-Like versus Alpha-Band Activity on Subjective Awareness of Auditory and Visual Stimuli

Alpha rhythmic activity is often suggested to exert an inhibitory influence on information processing. However, relatively little is known about how reported alpha-related effects are influenced by a potential confounding element of the neural signal, power-law scaling. In the current study, we systematically examine the effect of accounting for 1/f activity on the relation between prestimulus alpha power and human behavior during both auditory and visual detection (N = 27; 19 female, 6 male, 2 nonbinary). The results suggest that, at least in the scalp-recorded EEG signal, the difference in alpha power often reported before visual hits versus misses is probably best thought of as a combination of narrowband alpha and broadband shifts. That is, changes in broadband parameters (exponent and offset of 1/f-like activity) also appear to be strong predictors of the subsequent awareness of visual stimuli. Neither changes in posterior alpha power nor changes in 1/f-like activity reliably predicted detection of auditory stimuli. These results appear consistent with suggestions that broadband changes in the scalp-recorded EEG signal may account for a portion of prior results linking alpha band dynamics to visuospatial attention and behavior, and suggest that systematic re-examination of existing data may be warranted.Significance Statement Fluctuations in alpha band (∼8-12 Hz) activity systematically follow the allocation of attention across space and sensory modality. Increases in alpha amplitude, which often precede failures to report awareness of threshold visual stimuli, are suggested to exert an inhibitory influence on information processing. However, fluctuations in alpha activity are often confounded with changes in the broadband 1/f-like pattern of the neural signal. When both factors are considered, we find that changes in broadband activity are as effective as narrowband alpha activity as predictors of subsequent visual detection. These results are consistent with emerging understanding of the potential functional importance of broadband changes in the neural signal and may have significant consequences for our understanding of alpha rhythmic activity.

Pre-stimulus alpha activity modulates long-lasting unconscious feature integration

Pre-stimulus alpha (α) activity can influence perception of shortly presented, low-contrast stimuli. The underlying mechanisms are often thought to affect perception exactly at the time of presentation. In addition, it is suggested that α cycles determine temporal windows of integration. However, in everyday situations, stimuli are usually presented for periods longer than ∼100 ms and perception is often an integration of information across space and time. Moving objects are just one example. Hence, the question is whether α activity plays a role also in temporal integration, especially when stimuli are integrated over several α cycles. Using electroencephalography (EEG), we investigated the relationship between pre-stimulus brain activity and long-lasting integration in the sequential metacontrast paradigm (SQM), where two opposite vernier offsets, embedded in a stream of lines, are unconsciously integrated into a single percept. We show that increases in α power, even 300 ms before the stimulus, affected the probability of reporting the first offset, shown at the very beginning of the SQM. This effect was mediated by the systematic slowing of the α rhythm that followed the peak in α power. No phase effects were found. Together, our results demonstrate a cascade of neural changes, following spontaneous bursts of α activity and extending beyond a single moment, which influences the sensory representation of visual features for hundreds of milliseconds. Crucially, as feature integration in the SQM occurs before a conscious percept is elicited, this also provides evidence that α activity is linked to mechanisms regulating unconscious processing.

EEG Phase Can Be Predicted with Similar Accuracy across Cognitive States after Accounting for Power and Signal-to-Noise Ratio

EEG phase is increasingly used in cognitive neuroscience, brain-computer interfaces, and closed-loop stimulation devices. However, it is unknown how accurate EEG phase prediction is across cognitive states. We determined the EEG phase prediction accuracy of parieto-occipital alpha waves across rest and task states in 484 participants over 11 public datasets. We were able to track EEG phase accurately across various cognitive conditions and datasets, especially during periods of high instantaneous alpha power and signal-to-noise ratio (SNR). Although resting states generally have higher accuracies than task states, absolute accuracy differences were small, with most of these differences attributable to EEG power and SNR. These results suggest that experiments and technologies using EEG phase should focus more on minimizing external noise and waiting for periods of high power rather than inducing a particular cognitive state.

Bias in Prestimulus Motor Cortical Activity Determines Decision-making Error in Rodents

Decision-making is a complex process that involves the integration and interpretation of sensory information to guide actions. The rodent motor cortex, which is generally involved in motor planning and execution, also plays a critical role in decision-making processes. In perceptual delayed-response tasks, the rodent motor cortex can represent sensory cues, as well as the decision of where to move. However, it remains unclear whether erroneous decisions arise from incorrect encoding of sensory information or improper utilization of the collected sensory information in the motor cortex. In this study, we analyzed the rodent anterior lateral motor cortex (ALM) while the mice performed perceptual delayed-response tasks. We divided population activities into sensory and choice signals to separately examine the encoding and utilization of sensory information. We found that the encoding of sensory information in the error trials was similar to that in the hit trials, whereas choice signals evolved differently between the error and hit trials. In error trials, choice signals displayed an offset in the opposite direction of instructed licking even before stimulus presentation, and this tendency gradually increased after stimulus onset, leading to incorrect licking. These findings suggest that decision errors are caused by biases in choice-related activities rather than by incorrect sensory encoding. Our study elaborates on the understanding of decision-making processes by providing neural substrates for erroneous decisions.

Using occipital ⍺-bursts to modulate behavior in real-time

Pre-stimulus endogenous neural activity can influence the processing of upcoming sensory input and subsequent behavioral reactions. Despite it is known that spontaneous oscillatory activity mostly appears in stochastic bursts, typical approaches based on trial averaging fail to capture this. We aimed at relating spontaneous oscillatory bursts in the alpha band (8-13 Hz) to visual detection behavior, via an electroencephalography-based brain-computer interface (BCI) that allowed for burst-triggered stimulus presentation in real-time. According to alpha theories, we hypothesized that visual targets presented during alpha-bursts should lead to slower responses and higher miss rates, whereas targets presented in the absence of bursts (low alpha activity) should lead to faster responses and higher false alarm rates. Our findings support the role of bursts of alpha oscillations in visual perception and exemplify how real-time BCI systems can be used as a test bench for brain-behavioral theories.

Novel multivariate methods to track frequency shifts of neural oscillations in EEG/MEG recordings

Instantaneous and peak frequency changes in neural oscillations have been linked to many perceptual, motor, and cognitive processes. Yet, the majority of such studies have been performed in sensor space and only occasionally in source space. Furthermore, both terms have been used interchangeably in the literature, although they do not reflect the same aspect of neural oscillations. In this paper, we discuss the relation between instantaneous frequency, peak frequency, and local frequency, the latter also known as spectral centroid. Furthermore, we propose and validate three different methods to extract source signals from multichannel data whose (instantaneous, local, or peak) frequency estimate is maximally correlated to an experimental variable of interest. Results show that the local frequency might be a better estimate of frequency variability than instantaneous frequency under conditions with low signal-to-noise ratio. Additionally, the source separation methods based on local and peak frequency estimates, called LFD and PFD respectively, provide more stable estimates than the decomposition based on instantaneous frequency. In particular, LFD and PFD are able to recover the sources of interest in simulations performed with a realistic head model, providing higher correlations with an experimental variable than multiple linear regression. Finally, we also tested all decomposition methods on real EEG data from a steady-state visual evoked potential paradigm and show that the recovered sources are located in areas similar to those previously reported in other studies, thus providing further validation of the proposed methods.

Frontal-occipital phase synchronization predicts occipital alpha power in perceptual decision-making

Numerous studies of perceptual decision-making have shown that lower prestimulus alpha power leads to a higher hit rate in visual detection, which is believed to correlate with the top-down control. However, whether frontal-occipital phase synchronization underlying the top-down control could impact the occipital alpha power that directly affects the perceptual performance remains unclear. In this study, we used analyses of the general linear mixed model (GLMM) and event-related potentials (ERPs) to show that the prestimulus alpha power over the occipital area directly affected visual perception. Using both the univariate and multivariate methods, we found that low-frequency (4-30 Hz) frontal-occipital phase synchronization predicted the prestimulus alpha power over the occipital area. Overall, our results suggested that frontal-occipital phase synchronization could predict occipital alpha power that directly affects perceptual decision-making.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11571-022-09862-7.

No evidence for the effect of entrainment's phase on duration reproduction and precision of regular intervals

Perception of time is not always veridical; rather, it is subjected to distortions. One such compelling distortion is that the duration of regularly spaced intervals is often overestimated. One account suggests that excitatory phases of neural entrainment concomitant with such stimuli play a major role. However, assessing the correlation between the power of entrained oscillations and time dilation has yielded inconclusive results. In this study, we evaluated whether phase characteristics of neural oscillations impact time dilation. For this purpose, we entrained 10-Hz oscillations and experimentally manipulated the presentation of flickers so that they were presented either in-phase or out-of-phase relative to the established rhythm. Simultaneous electroencephalography (EEG) recordings confirmed that in-phase and out-of-phase flickers had landed on different inhibitory phases of high-amplitude alpha oscillations. Moreover, to control for confounding factors of expectancy and masking, we created two additional conditions. Results, supplemented by the Bayesian analysis, indicated that the phase of entrained visual alpha oscillation does not differentially affect flicker-induced time dilation. Repeating the same experiment with regularly spaced auditory stimuli replicated the null findings. Moreover, we found a robust enhancement of precision for the reproduction of flickers relative to static stimuli that were partially supported by entrainment models. We discussed our results within the framework of neural oscillations and time-perception models, suggesting that inhibitory cycles of visual alpha may have little relevance to the overestimation of regularly spaced intervals. Moreover, based on our findings, we proposed that temporal oscillators, assumed in entrainment models, may act independently of excitatory phases in the brain's lower level sensory areas.

Genuine beta bursts in human working memory: controlling for the influence of lower-frequency rhythms

Human working memory is associated with significant modulations in oscillatory brain activity. However, the functional role of brain rhythms at different frequencies is still debated. Modulations in the beta frequency range (15-40 Hz) are especially difficult to interpret because they could be artifactually produced by (more prominent) oscillations in lower frequencies that show non-sinusoidal properties. In this study, we investigate beta oscillations during working memory while controlling for the possible influence of lower frequency rhythms. We collected electroencephalography (EEG) data in 31 participants who performed a spatial working-memory task with two levels of cognitive load. In order to rule out the possibility that observed beta activity was affected by non-sinusoidalities of lower frequency rhythms, we developed an algorithm that detects transient beta oscillations that do not coincide with more prominent lower frequency rhythms in time and space. Using this algorithm, we show that the amplitude and duration of beta bursts decrease with memory load and during memory manipulation, while their peak frequency and rate increase. In addition, interindividual differences in performance were significantly associated with beta burst rates. Together, our results show that beta rhythms are functionally modulated during working memory and that these changes cannot be attributed to lower frequency rhythms with non-sinusoidal properties.

Crossmodal plasticity in hearing loss

Crossmodal plasticity is a textbook example of the ability of the brain to reorganize based on use. We review evidence from the auditory system showing that such reorganization has significant limits, is dependent on pre-existing circuitry and top-down interactions, and that extensive reorganization is often absent. We argue that the evidence does not support the hypothesis that crossmodal reorganization is responsible for closing critical periods in deafness, and crossmodal plasticity instead represents a neuronal process that is dynamically adaptable. We evaluate the evidence for crossmodal changes in both developmental and adult-onset deafness, which start as early as mild-moderate hearing loss and show reversibility when hearing is restored. Finally, crossmodal plasticity does not appear to affect the neuronal preconditions for successful hearing restoration. Given its dynamic and versatile nature, we describe how this plasticity can be exploited for improving clinical outcomes after neurosensory restoration.

Age-related trends in aperiodic EEG activity and alpha oscillations during early- to middle-childhood

Age-related structural and functional changes that occur during brain development are critical for cortical development and functioning. Previous electroencephalography (EEG) and magnetoencephalography (MEG) studies have highlighted the utility of power spectra analyses and have uncovered age-related trends that reflect perceptual, cognitive, and behavioural states as well as their underlying neurophysiology. The aim of the current study was to investigate age-related change in aperiodic and periodic alpha activity across a large sample of pre- and school-aged children (N = 502, age range 4 -11-years-of-age). Power spectra were extracted from baseline EEG recordings (eyes closed, eyes open) for each participant and parameterized into aperiodic activity to derive the offset and exponent parameters and periodic alpha oscillatory activity to derive the alpha peak frequency and the associated power estimates. Multilevel models were run to investigate age-related trends and condition-dependent changes for each of these measures. We found quadratic age-related effects for both the aperiodic offset and exponent. In addition, we observed increases in periodic alpha peak frequency as a function of age. Aperiodic measures and periodic alpha power were larger in magnitude during eyes closed compared to the eyes open baseline condition. Taken together, these results advance our understanding of the maturational patterns/trajectories of brain development during early- to middle-childhood.

Parieto-Occipital Electrocortical Dynamics during Real-World Table Tennis

Traditional human electroencephalography (EEG) experiments that study visuomotor processing use controlled laboratory conditions with limited ecological validity. In the real world, the brain integrates complex, dynamic, multimodal visuomotor cues to guide the execution of movement. The parietal and occipital cortices are especially important in the online control of goal-directed actions. Table tennis is a whole-body, responsive activity requiring rapid visuomotor integration that presents a myriad of unanswered neurocognitive questions about brain function during real-world movement. The aim of this study was to quantify the electrocortical dynamics of the parieto-occipital cortices while playing a sport with high-density electroencephalography. We included analysis of power spectral densities (PSDs), event-related spectral perturbations, intertrial phase coherences (ITPCs), event-related potentials (ERPs), and event-related phase coherences of parieto-occipital source-localized clusters while participants played table tennis with a ball machine and a human. We found significant spectral power fluctuations in the parieto-occipital cortices tied to hit events. Ball machine trials exhibited more fluctuations in θ power around hit events, an increase in intertrial phase coherence and deflection in the event-related potential, and higher event-related phase coherence between parieto-occipital clusters as compared with trials with a human. Our results suggest that sport training with a machine elicits fundamentally different brain dynamics than training with a human.

Advances in human intracranial electroencephalography research, guidelines and good practices

Since the second-half of the twentieth century, intracranial electroencephalography (iEEG), including both electrocorticography (ECoG) and stereo-electroencephalography (sEEG), has provided an intimate view into the human brain. At the interface between fundamental research and the clinic, iEEG provides both high temporal resolution and high spatial specificity but comes with constraints, such as the individual's tailored sparsity of electrode sampling. Over the years, researchers in neuroscience developed their practices to make the most of the iEEG approach. Here we offer a critical review of iEEG research practices in a didactic framework for newcomers, as well addressing issues encountered by proficient researchers. The scope is threefold: (i) review common practices in iEEG research, (ii) suggest potential guidelines for working with iEEG data and answer frequently asked questions based on the most widespread practices, and (iii) based on current neurophysiological knowledge and methodologies, pave the way to good practice standards in iEEG research. The organization of this paper follows the steps of iEEG data processing. The first section contextualizes iEEG data collection. The second section focuses on localization of intracranial electrodes. The third section highlights the main pre-processing steps. The fourth section presents iEEG signal analysis methods. The fifth section discusses statistical approaches. The sixth section draws some unique perspectives on iEEG research. Finally, to ensure a consistent nomenclature throughout the manuscript and to align with other guidelines, e.g., Brain Imaging Data Structure (BIDS) and the OHBM Committee on Best Practices in Data Analysis and Sharing (COBIDAS), we provide a glossary to disambiguate terms related to iEEG research.

Visual working memory recruits two functionally distinct alpha rhythms in posterior cortex

Oscillatory activity in the human brain is dominated by posterior alpha oscillations (8-14 Hz), which have been shown to be functionally relevant in a wide variety of cognitive tasks. Although posterior alpha oscillations are commonly considered a single oscillator anchored at an individual alpha frequency (IAF; ∼10 Hz), previous work suggests that IAF reflects a spatial mixture of different brain rhythms. In this study, we assess whether Independent Component Analysis (ICA) can disentangle functionally distinct posterior alpha rhythms in the context of visual short-term memory retention. Magnetoencephalography (MEG) was recorded in 33 subjects while performing a visual working memory task. Group analysis at sensor level suggested the existence of a single posterior alpha oscillator that increases in power and decreases in frequency during memory retention. Conversely, single-subject analysis of independent components revealed the existence of two dissociable alpha rhythms: one that increases in power during memory retention (Alpha1) and another one that decreases in power (Alpha2). Alpha1 and Alpha2 rhythms were differentially modulated by the presence of visual distractors (Alpha1 increased in power while Alpha2 decreased) and had an opposite relationship with accuracy (positive for Alpha1 and negative for Alpha2). In addition, Alpha1 rhythms showed a lower peak frequency, a narrower peak width, a greater relative peak amplitude and a more central source than Alpha2 rhythms. Together, our results demonstrate that modulations in posterior alpha oscillations during short-term memory retention reflect the dynamics of at least two distinct brain rhythms with different functions and spatiospectral characteristics.Significance statementAlpha oscillations are the most prominent feature of the human brain's electrical activity, and consist of rhythmic neuronal activity in posterior parts of the cortex. Alpha is usually considered a single brain rhythm that changes in power and frequency to support cognitive operations. We here show that posterior alpha entails at least two dissociable rhythms with distinct functions and characteristics. These findings could solve previous inconsistencies in the literature regarding the direction of task-related alpha power/frequency modulations and their relation to cognitive performance. In addition, the existence of two distinct posterior alpha rhythms could have important consequences for the design of neurostimulation protocols aimed at modulating alpha oscillations and subsequently cognition.

Oscillatory beta/alpha band modulations: A potential biomarker of functional language and motor recovery in chronic stroke?

Stroke remains one of the leading causes of various disabilities, including debilitating motor and language impairments. Though various treatments exist, post-stroke impairments frequently become chronic, dramatically reducing daily life quality, and requiring specific rehabilitation. A critical goal of chronic stroke rehabilitation is to induce, usually through behavioral training, experience-dependent plasticity processes in order to promote functional recovery. However, the efficiency of such interventions is typically modest, and very little is known regarding the neural dynamics underpinning recovery processes and possible biomarkers of their efficiency. Some studies have emphasized specific alterations of excitatory–inhibitory balance within distributed neural networks as an important recovery correlate. Neural processes sensitive to these alterations, such as task-dependent oscillatory activity in beta as well as alpha bands, may be candidate biomarkers of chronic stroke functional recovery. In this review, we discuss the results of studies on motor and language recovery with a focus on oscillatory processes centered around the beta band and their modulations during functional recovery in chronic stroke. The discussion is based on a framework where task-dependent modulations of beta and alpha oscillatory activity, generated by the deep cortical excitatory–inhibitory microcircuits, serve as a neural mechanism of domain-general top-down control processes. We discuss the findings, their limitations, and possible directions for future research.

Alpha blocking and 1/fβ spectral scaling in resting EEG can be accounted for by a sum of damped alpha band oscillatory processes

The dynamical and physiological basis of alpha band activity and 1/f^β noise in the EEG are the subject of continued speculation. Here we conjecture, on the basis of empirical data analysis, that both of these features may be economically accounted for through a single process if the resting EEG is conceived of being the sum of multiple stochastically perturbed alpha band damped linear oscillators with a distribution of dampings (relaxation rates). The modulation of alpha-band and 1/f^β noise activity by changes in damping is explored in eyes closed (EC) and eyes open (EO) resting state EEG. We aim to estimate the distribution of dampings by solving an inverse problem applied to EEG power spectra. The characteristics of the damping distribution are examined across subjects, sensors and recording condition (EC/EO). We find that there are robust changes in the damping distribution between EC and EO recording conditions across participants. The estimated damping distributions are found to be predominantly bimodal, with the number and position of the modes related to the sharpness of the alpha resonance and the scaling (β) of the power spectrum (1/f^β). The results suggest that there exists an intimate relationship between resting state alpha activity and 1/f^β noise with changes in both governed by changes to the damping of the underlying alpha oscillatory processes. In particular, alpha-blocking is observed to be the result of the most weakly damped distribution mode becoming more heavily damped. The results suggest a novel way of characterizing resting EEG power spectra and provides new insight into the central role that damped alpha-band activity may play in characterising the spatio-temporal features of resting state EEG.

The resting human electroencephalogram (EEG) exhibits two dominant spectral features: the alpha rhythm (8–13 Hz) and its associated attenuation between eyes-closed and eyes-open resting state (alpha blocking), and the 1/f^β scaling of the power spectrum. While these phenomena are well studied a thorough understanding of their respective generative processes remains elusive. By employing a theoretical approach that follows from neural population models of EEG we demonstrate that it is possible to economically account for both of these phenomena using a singular mechanistic framework: resting EEG is assumed to arise from the summed activity of multiple uncorrelated, stochastically driven, damped alpha band linear oscillatory processes having a distribution of relaxation rates or dampings. By numerically estimating these damping distributions from eyes-closed and eyes-open EEG data, in a total of 136 participants, it is found that such damping distributions are predominantly bimodal in shape. The most weakly damped mode is found to account for alpha band power, with alpha blocking being driven by an increase in the damping of this weakly damped mode, whereas the second, and more heavily damped mode, is able to explain 1/f^β scaling present in the resting state EEG spectra.