Top-down beta rhythms support selective attention via interlaminar interaction: a model

Phase of neural oscillations as a reference frame for attention-based routing in visual cortex

Selective attention allows the brain to efficiently process the image projected onto the retina, selectively focusing neural processing resources on behaviorally relevant visual information. While previous studies have documented the crucial role of the action potential rate of single neurons in relaying such information, little is known about how the activity of single neurons relative to their neighboring network contributes to the efficient representation of attended stimuli and transmission of this information to downstream areas. Here, we show in the dorsal visual pathway of monkeys (medial superior temporal area) that neurons fire spikes preferentially at a specific phase of the ongoing population beta (∼20 Hz) oscillations of the surrounding local network. This preferred spiking phase shifts towards a later phase when monkeys selectively attend towards (rather than away from) the receptive field of the neuron. This shift of the locking phase is positively correlated with the speed at which animals report a visual change. Furthermore, our computational modeling suggests that neural networks can manipulate the preferred phase of coupling by imposing differential synaptic delays on postsynaptic potentials. This distinction between the locking phase of neurons activated by the spatially attended stimulus vs. that of neurons activated by the unattended stimulus, may enable the neural system to discriminate relevant from irrelevant sensory inputs and consequently filter out distracting stimuli information by aligning the spikes which convey relevant/irrelevant information to distinct phases linked to periods of better/worse perceptual sensitivity for higher cortices. This strategy may be used to reserve the narrow windows of highest perceptual efficacy to the processing of the most behaviorally relevant information, ensuring highly efficient responses to attended sensory events.

Information representation in an oscillating neural field model modulated by working memory signals

We study how stimulus information can be represented in the dynamical signatures of an oscillatory model of neural activity-a model whose activity can be modulated by input akin to signals involved in working memory (WM). We developed a neural field model, tuned near an oscillatory instability, in which the WM-like input can modulate the frequency and amplitude of the oscillation. Our neural field model has a spatial-like domain in which an input that preferentially targets a point-a stimulus feature-on the domain will induce feature-specific activity changes. These feature-specific activity changes affect both the mean rate of spikes and the relative timing of spiking activity to the global field oscillation-the phase of the spiking activity. From these two dynamical signatures, we define both a spike rate code and an oscillatory phase code. We assess the performance of these two codes to discriminate stimulus features using an information-theoretic analysis. We show that global WM input modulations can enhance phase code discrimination while simultaneously reducing rate code discrimination. Moreover, we find that the phase code performance is roughly two orders of magnitude larger than that of the rate code defined for the same model solutions. The results of our model have applications to sensory areas of the brain, to which prefrontal areas send inputs reflecting the content of WM. These WM inputs to sensory areas have been established to induce oscillatory changes similar to our model. Our model results suggest a mechanism by which WM signals may enhance sensory information represented in oscillatory activity beyond the comparatively weak representations based on the mean rate activity.

Information content and temporal structure of face selective local field potentials frequency bands in IT cortex

Sensory stimulation triggers synchronized bioelectrical activity in the brain across various frequencies. This study delves into network-level activities, specifically focusing on local field potentials as a neural signature of visual category representation. Specifically, we studied the role of different local field potential frequency oscillation bands in visual stimulus category representation by presenting images of faces and objects to three monkeys while recording local field potential from inferior temporal cortex. We found category selective local field potential responses mainly for animate, but not inanimate, objects. Notably, face-selective local field potential responses were evident across all tested frequency bands, manifesting in both enhanced (above mean baseline activity) and suppressed (below mean baseline activity) local field potential powers. We observed four different local field potential response profiles based on frequency bands and face selective excitatory and suppressive responses. Low-frequency local field potential bands (1-30 Hz) were more prodominstaly suppressed by face stimulation than the high-frequency (30-170 Hz) local field potential bands. Furthermore, the low-frequency local field potentials conveyed less face category informtion than the high-frequency local field potential in both enhansive and suppressive conditions. Furthermore, we observed a negative correlation between face/object d-prime values in all the tested local field potential frequency bands and the anterior-posterior position of the recording sites. In addition, the power of low-frequency local field potential systematically declined across inferior temporal anterior-posterior positions, whereas high-frequency local field potential did not exhibit such a pattern. In general, for most of the above-mentioned findings somewhat similar results were observed for body, but not, other stimulus categories. The observed findings suggest that a balance of face selective excitation and inhibition across time and cortical space shape face category selectivity in inferior temporal cortex.

Neural Oscillations and Multisensory Processing

Neural oscillations play a role in sensory processing by coordinating synchronized neuronal activity. Synchronization of gamma oscillations is engaged in local computation of feedforward signals and synchronization of alpha-beta oscillations is engaged in feedback processing over long-range areas. These spatially and spectrally segregated bi-directional signals may be integrated by a mechanism of cross-frequency coupling. Synchronization of neural oscillations has also been proposed as a mechanism for information integration across multiple sensory modalities. A transient stimulus or rhythmic stimulus from one modality may lead to phase alignment of ongoing neural oscillations in multiple sensory cortices, through a mechanism of cross-modal phase reset or cross-modal neural entrainment. Synchronized activities in multiple sensory cortices are more likely to boost stronger activities in downstream areas. Compared to synchronized oscillations, asynchronized oscillations may impede signal processing, and may contribute to sensory selection by setting the oscillations in the target-related cortex and the oscillations in the distractor-related cortex to opposite phases.

Comparing neuronal oscillations during visual spatial attention orienting between normobaric and hypobaric hypoxia

Normobaric hypoxia (NH) and hypobaric hypoxia (HH) are both used to train aircraft pilots to recognize symptoms of hypoxia. NH (low oxygen concentration) training is often preferred because it is more cost effective, simpler, and safer than HH. It is unclear, however, whether NH is neurophysiologically equivalent to HH (high altitude). Previous studies have shown that neural oscillations, particularly those in the alpha band (8-12 Hz), are impacted by hypoxia. Attention tasks have been shown to reliably modulate alpha oscillations, although the neurophysiological impacts of hypoxia during cognitive processing remains poorly understood. To address this we investigated induced and evoked power alongside physiological data while participants performed an attention task during control (normobaric normoxia or NN), NH (fraction of inspired oxygen = 12.8%, partial pressure of inspired oxygen = 87.2 mmHg), and HH (3962 m, partial pressure of inspired oxygen = 87.2 mmHg) conditions inside a hypobaric chamber. No significant differences between NH and HH were found in oxygen saturation, end tidal gases, breathing rate, middle cerebral artery velocity and blood pressure. Induced alpha power was significantly decreased in NH and HH when compared to NN. Participants in the HH condition showed significantly increased induced lower-beta power and evoked higher-beta power, compared with the NH and NN conditions, indicating that NH and HH differ in their impact on neurophysiological activity supporting cognition. NH and HH were found not to be neurophysiologically equivalent as electroencephalography was able to differentiate NH from HH.

The alpha2 nicotinic acetylcholine receptor, a subunit with unique and selective expression in inhibitory interneurons associated with principal cells

Nicotinic acetylcholine receptors (nAChRs) play crucial roles in various human disorders, with the α7, α4, α6, and α3-containing nAChR subtypes extensively studied in relation to conditions such as Alzheimer's disease, Parkinson's disease, nicotine dependence, mood disorders, and stress disorders. In contrast, the α2-nAChR subunit has received less attention due to its more restricted expression and the scarcity of specific agonists and antagonists for studying its function. Nevertheless, recent research has shed light on the unique expression pattern of the Chrna2 gene, which encodes the α2-nAChR subunit, and its involvement in distinct populations of inhibitory interneurons. This review highlights the structure, pharmacology, localization, function, and disease associations of α2-containing nAChRs and points to the unique expression pattern of the Chrna2 gene and its role in different inhibitory interneuron populations. These populations, including the oriens lacunosum moleculare (OLM) cells in the hippocampus, Martinotti cells in the neocortex, and Renshaw cells in the spinal cord, share common features and contribute to recurrent inhibitory microcircuits. Thus, the α2-nAChR subunit's unique expression pattern in specific interneuron populations and its role in recurrent inhibitory microcircuits highlight its importance in various physiological processes. Further research is necessary to uncover the comprehensive functionality of α2-containing nAChRs, delineate their specific contributions to neuronal circuits, and investigate their potential as therapeutic targets for related disorders.

Transient Oscillations of Neural Firing Rate Associated With Routing of Evidence in a Perceptual Decision

To form a perceptual decision, the brain must acquire samples of evidence from the environment and incorporate them in computations that mediate choice behavior. While much is known about the neural circuits that process sensory information and those that form decisions, less is known about the mechanisms that establish the functional linkage between them. We trained monkeys of both sexes to make difficult decisions about the net direction of visual motion under conditions that required trial-by-trial control of functional connectivity. In one condition, the motion appeared at different locations on different trials. In the other, two motion patches appeared, only one of which was informative. Neurons in the parietal cortex produced brief oscillations in their firing rate at the time routing was established: upon onset of the motion display when its location was unpredictable across trials, and upon onset of an attention cue that indicated in which of two locations an informative patch of dots would appear. The oscillation was absent when the stimulus location was fixed across trials. We interpret the oscillation as a manifestation of the mechanism that establishes the source and destination of flexibly routed information, but not the transmission of the information per se Significance Statement It has often been suggested that oscillations in neural activity might serve a role in routing information appropriately. We observe an oscillation in neural firing rate in the lateral intraparietal area consistent with such a role. The oscillations are transient. They coincide with the establishment of routing, but they do not appear to play a role in the transmission (or conveyance) of the routed information itself.

A recruitment through coherence theory of working memory

The interactions between prefrontal cortex and other areas during working memory have been studied for decades. Here we outline a conceptual framework describing interactions between these areas during working memory, and review evidence for key elements of this model. We specifically suggest that a top-down signal sent from prefrontal to sensory areas drives oscillations in these areas. Spike timing within sensory areas becomes locked to these working-memory-driven oscillations, and the phase of spiking conveys information about the representation available within these areas. Downstream areas receiving these phase-locked spikes from sensory areas can recover this information via a combination of coherent oscillations and gating of input efficacy based on the phase of their local oscillations. Although the conceptual framework is based on prefrontal interactions with sensory areas during working memory, we also discuss the broader implications of this framework for flexible communication between brain areas in general.

Random Tactile Noise Stimulation Reveals Beta-Rhythmic Impulse Response Function of the Somatosensory System

Both passive tactile stimulation and motor actions result in dynamic changes in beta band (15-30 Hz Hz) oscillations over somatosensory cortex. Similar to alpha band (8-12 Hz) power decrease in the visual system, beta band power also decreases following stimulation of the somatosensory system. This relative suppression of α and β oscillations is generally interpreted as an increase in cortical excitability. Here, next to traditional single-pulse stimuli, we used a random intensity continuous right index finger tactile stimulation (white noise), which enabled us to uncover an impulse response function of the somatosensory system. Contrary to previous findings, we demonstrate a burst-like initial increase rather than decrease of beta activity following white noise stimulation (human participants, N = 18, 8 female). These β bursts, on average, lasted for 3 cycles, and their frequency was correlated with resonant frequency of somatosensory cortex, as measured by a multifrequency steady-state somatosensory evoked potential paradigm. Furthermore, beta band bursts shared spectro-temporal characteristics with evoked and resting-state β oscillations. Together, our findings not only reveal a novel oscillatory signature of somatosensory processing that mimics the previously reported visual impulse response functions, but also point to a common oscillatory generator underlying spontaneous β bursts in the absence of tactile stimulation and phase-locked β bursts following stimulation, the frequency of which is determined by the resonance properties of the somatosensory system.SIGNIFICANCE STATEMENT The investigation of the transient nature of oscillations has gained great popularity in recent years. The findings of bursting activity, rather than sustained oscillations in the beta band, have provided important insights into its role in movement planning, working memory, inhibition, and reactivation of neural ensembles. In this study, we show that also in response to tactile stimulation the somatosensory system responds with ∼3 cycle oscillatory beta band bursts, whose spectro-temporal characteristics are shared with evoked and resting-state beta band oscillatory signatures of the somatosensory system. As similar bursts have been observed in the visual domain, these oscillatory signatures might reflect an important supramodal mechanism in sensory processing.

When do bursts matter in the primary motor cortex? Investigating changes in the intermittencies of beta rhythms associated with movement states

Brain activity exhibits significant temporal structure that is not well captured in the power spectrum. Recently, attention has shifted to characterising the properties of intermittencies in rhythmic neural activity (i.e. bursts), yet the mechanisms that regulate them are unknown. Here, we present evidence from electrocorticography recordings made over the motor cortex to show that the statistics of bursts, such as duration or amplitude, in the beta frequency (14-30 Hz) band, significantly aid the classification of motor states such as rest, movement preparation, execution, and imagery. These features reflect nonlinearities not detectable in the power spectrum, with states increasing in nonlinearity from movement execution to preparation to rest. Further, we show using a computational model of the cortical microcircuit, constrained to account for burst features, that modulations of laminar specific inhibitory interneurons are responsible for the temporal organisation of activity. Finally, we show that the temporal characteristics of spontaneous activity can be used to infer the balance of cortical integration between incoming sensory information and endogenous activity. Critically, we contribute to the understanding of how transient brain rhythms may underwrite cortical processing, which in turn, could inform novel approaches for brain state classification, and modulation with novel brain-computer interfaces.

Interacting rhythms enhance sensitivity of target detection in a fronto-parietal computational model of visual attention

Even during sustained attention, enhanced processing of attended stimuli waxes and wanes rhythmically, with periods of enhanced and relatively diminished visual processing (and subsequent target detection) alternating at 4 or 8 Hz in a sustained visual attention task. These alternating attentional states occur alongside alternating dynamical states, in which lateral intraparietal cortex (LIP), the frontal eye field (FEF), and the mediodorsal pulvinar (mdPul) exhibit different activity and functional connectivity at α, β, and γ frequencies-rhythms associated with visual processing, working memory, and motor suppression. To assess whether and how these multiple interacting rhythms contribute to periodicity in attention, we propose a detailed computational model of FEF and LIP. When driven by θ-rhythmic inputs simulating experimentally-observed mdPul activity, this model reproduced the rhythmic dynamics and behavioral consequences of observed attentional states, revealing that the frequencies and mechanisms of the observed rhythms allow for peak sensitivity in visual target detection while maintaining functional flexibility.

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.

A microcircuit model involving parvalbumin, somatostatin, and vasoactive intestinal polypeptide inhibitory interneurons for the modulation of neuronal oscillation during visual processing

Various subtypes of inhibitory interneurons contact one another to organize cortical networks. Most cortical inhibitory interneurons express 1 of 3 genes: parvalbumin (PV), somatostatin (SOM), or vasoactive intestinal polypeptide (VIP). This diversity of inhibition allows the flexible regulation of neuronal responses within and between cortical areas. However, the exact roles of these interneuron subtypes and of excitatory pyramidal (Pyr) neurons in regulating neuronal network activity and establishing perception (via interactions between feedforward sensory and feedback attentional signals) remain largely unknown. To explore the regulatory roles of distinct neuronal types in cortical computation, we developed a computational microcircuit model with biologically plausible visual cortex layers 2/3 that combined Pyr neurons and the 3 inhibitory interneuron subtypes to generate network activity. In simulations with our model, inhibitory signals from PV and SOM neurons preferentially induced neuronal firing at gamma (30-80 Hz) and beta (20-30 Hz) frequencies, respectively, in agreement with observed physiological results. Furthermore, our model indicated that rapid inhibition from VIP to SOM subtypes underlies marked attentional modulation for low-gamma frequency (30-50 Hz) in Pyr neuron responses. Our results suggest the distinct but cooperative roles of inhibitory interneuron subtypes in the establishment of visual perception.

Oscillatory Neural Signatures of Visual Perception Across Developmental Stages in Individuals With 22q11.2 Deletion Syndrome

BACKGROUND

Numerous behavioral studies have highlighted the contribution of visual perceptual deficits to the nonverbal cognitive profile of individuals with 22q11.2 deletion syndrome. However, the neurobiological processes underlying these widespread behavioral alterations are yet to be fully understood. Thus, in this paper, we investigated the role of neural oscillations toward visuoperceptual deficits to elucidate the neurobiology of sensory impairments in deletion carriers.

METHODS

We acquired 125 high-density electroencephalography recordings during a visual grating task in a group of 62 deletion carriers and 63 control subjects. Stimulus-elicited oscillatory responses were analyzed with 1) time-frequency analysis using wavelets decomposition at sensor and source level, 2) intertrial phase coherence, and 3) Granger causality connectivity in source space. Additional analyses examined the development of neural oscillations across age bins.

RESULTS

Deletion carriers had decreased theta-band (4-8 Hz) and gamma-band (58-68 Hz) spectral power compared with control subjects in response to the visual stimuli, with an absence of age-related increase of theta- and gamma-band responses. Moreover, adult deletion carriers had decreased gamma- and theta-band responses but increased alpha/beta desynchronization (10-25 Hz) that correlated with behavioral performance. Granger causality estimates reflected an increased frontal-occipital connectivity in the beta range (22-40 Hz).

CONCLUSIONS

Deletion carriers exhibited decreased theta- and gamma-band responses to visual stimuli, while alpha/beta desynchronization was preserved. Overall, the lack of age-related changes in deletion carriers implicates developmental impairments in circuit mechanisms underlying neural oscillations. The dissociation between the maturation of theta/gamma- and alpha/beta-band responses may indicate a selective impairment in supragranular cortical layers, leading to compensatory top-down connectivity.

Mutual beta power modulation in dyadic entrainment

Across a broad spectrum of interactions, humans exhibit a prominent tendency to synchronize their movements with one another. Traditionally, this phenomenon has been explained from the perspectives of predictive coding or dynamical systems theory. While these theories diverge with respect to whether individuals hold internal models of each other, they both assume a predictive or anticipatory mechanism enabling rhythmic interactions. However, the neural bases underpinning interpersonal synchronization are still a subject under active investigation. Here we provide evidence that the brain relies on a common oscillatory mechanism to pace self-generated rhythmic movements and to track the movements produced by a partner. By performing dual-electroencephalography recordings during a joint finger-tapping task, we identified an oscillatory component in the beta range (∼ 20 Hz), which was significantly modulated by both self-generated and other-generated movement. In conditions where the partners perceived each other, we observed periodic fluctuations of beta power as a function of the reciprocal movement cycles. Crucially, this modulation occurred both in visually and in auditorily coupled conditions, and was accompanied by recurrent periods of dyadic synchronized behavior. Our results show that periodic beta power modulations may be a critical mechanism underlying interpersonal synchronization, possibly enabling mutual predictions between coupled individuals, leading to co-regulation of timing and overt mutual adaptation. Our findings thus provide a potential bridge between influential theories attempting to explain interpersonal coordination, and a concrete connection to its neurophysiological bases.

Modulation of inhibitory communication coordinates looking and reaching

Looking and reaching are controlled by different brain regions and are coordinated during natural behaviour1. Understanding how flexible, natural behaviours such as coordinated looking and reaching are controlled depends on understanding how neurons in different regions of the brain communicate2. Neural coherence in a gamma-frequency (40-90 Hz) band has been implicated in excitatory multiregional communication3. Inhibitory control mechanisms are also required to flexibly control behaviour4, but little is known about how neurons in one region transiently suppress individual neurons in another to support behaviour. How neuronal firing in a sender region transiently suppresses firing in a receiver region remains poorly understood. Here we study inhibitory communication during a flexible, natural behaviour, termed gaze anchoring, in which saccades are transiently inhibited by coordinated reaches. During gaze anchoring, we found that neurons in the reach region of the posterior parietal cortex can inhibit neuronal firing in the parietal saccade region to suppress eye movements and improve reach accuracy. Suppression is transient, only present around the coordinated reach, and greatest when reach neurons fire spikes with respect to beta-frequency (15-25 Hz) activity, not gamma-frequency activity. Our work provides evidence in the activity of single neurons for a novel mechanism of inhibitory communication in which beta-frequency neural coherence transiently inhibits multiregional communication to flexibly coordinate natural behaviour.

Feedforward and feedback influences through distinct frequency bands between two spiking-neuron networks

Several studies on brain signals suggested that bottom-up and top-down influences are exerted through distinct frequency bands among visual cortical areas. It was recently shown that theta and gamma rhythms subserve feedforward, whereas the feedback influence is dominated by the alpha-beta rhythm in primates. A few theoretical models for reproducing these effects have been proposed so far. Here we show that a simple but biophysically plausible two-network motif composed of spiking-neuron models and chemical synapses can exhibit feedforward and feedback influences through distinct frequency bands. Different from previous studies, this kind of model allows us to study directed influences not only at the population level, by using a proxy for the local field potential, but also at the cellular level, by using the neuronal spiking series.

Electrophysiological signatures of attentional control in bilingual processing: Evidence from proactive interference

Monolingual and bilingual participants performed a Proactive Interference task in verbal and nonverbal conditions while EEG was recorded. Behavioral results showed faster responses for bilinguals on interference trials in the nonverbal condition, and electrophysiological results indicated greater attentional control for bilinguals. ROI analyses showed this pattern for bilinguals mainly in the verbal condition, whereas whole brain analyses found this association in both conditions. Frequency power analysis found activity related to interference trials was associated with recruitment of different neural resources for verbal and nonverbal conditions. Nonverbal results indicated beta activity for interference trials in bilinguals and the verbal condition showed this pattern in theta and gamma frequency bands as well, revealing more extensive brain activation in the verbal domain for bilinguals. For monolinguals, frequency power in beta, gamma, and theta were related to facilitation trials. These results suggest different strategies for allocating attention by monolingual and bilingual young adults.

Brain Synchrony in Competition and Collaboration During Multiuser Neurofeedback-Based Gaming

EEG hyperscanning during multiuser gaming offers opportunities to study brain characteristics of social interaction under various paradigms. In this study, we aimed to characterize neural signatures and phase-based functional connectivity patterns of gaming strategies during collaborative and competitive alpha neurofeedback games. Twenty pairs of participants with no close relationship took part in three sessions of collaborative or competitive multiuser neurofeedback (NF), with identical graphical user interface, using Relative Alpha (RA) power as a control signal. Collaborating dyads had to keep their RA within 5% of each other for the team to be awarded a point, while members of competitive dyads scored points if their RA was 10% above their opponent's. Interbrain synchrony existed only during gaming but not during baseline in either collaborative or competitive gaming. Spectral analysis and interbrain connectivity showed that in collaborative gaming, players with higher resting state alpha content were more active in regulating their RA to match those of their partner. Moreover, interconnectivity was the strongest between homologous brain structures of the dyad in theta and alpha bands, indicating a similar degree of planning and social exchange. Competitive gaming emphasized the difference between participants who were able to relax and, in this way, maintain RA, and those who had an unsuccessful approach. Analysis of interbrain connections shows engagement of frontal areas in losers, but not in winners, indicating the formers' attempt to mentalise and apply strategies that might be suitable for conventional gaming, but inappropriate for the alpha neurofeedback-based game. We show that in gaming based on multiplayer non-verbalized NF, the winning strategy is dependent on the rules of the game and on the behavior of the opponent. Mental strategies that characterize successful gaming in the physical world might not be adequate for NF-based gaming.

Dynamic large-scale connectivity of intrinsic cortical oscillations supports adaptive listening in challenging conditions

In multi-talker situations, individuals adapt behaviorally to this listening challenge mostly with ease, but how do brain neural networks shape this adaptation? We here establish a long-sought link between large-scale neural communications in electrophysiology and behavioral success in the control of attention in difficult listening situations. In an age-varying sample of N = 154 individuals, we find that connectivity between intrinsic neural oscillations extracted from source-reconstructed electroencephalography is regulated according to the listener's goal during a challenging dual-talker task. These dynamics occur as spatially organized modulations in power-envelope correlations of alpha and low-beta neural oscillations during approximately 2-s intervals most critical for listening behavior relative to resting-state baseline. First, left frontoparietal low-beta connectivity (16 to 24 Hz) increased during anticipation and processing of a spatial-attention cue before speech presentation. Second, posterior alpha connectivity (7 to 11 Hz) decreased during comprehension of competing speech, particularly around target-word presentation. Connectivity dynamics of these networks were predictive of individual differences in the speed and accuracy of target-word identification, respectively, but proved unconfounded by changes in neural oscillatory activity strength. Successful adaptation to a listening challenge thus latches onto two distinct yet complementary neural systems: a beta-tuned frontoparietal network enabling the flexible adaptation to attentive listening state and an alpha-tuned posterior network supporting attention to speech.

Monitoring the Cortical Activity of Children and Adults during Cognitive Task Completion

In this paper, we used an EEG system to monitor and analyze the cortical activity of children and adults at a sensor level during cognitive tasks in the form of a Schulte table. This complex cognitive task simultaneously involves several cognitive processes and systems: visual search, working memory, and mental arithmetic. We revealed that adults found numbers on average two times faster than children in the beginning. However, this difference diminished at the end of table completion to 1.8 times. In children, the EEG analysis revealed high parietal alpha-band power at the end of the task. This indicates the shift from procedural strategy to less demanding fact-retrieval. In adults, the frontal beta-band power increased at the end of the task. It reflects enhanced reliance on the top-down mechanisms, cognitive control, or attentional modulation rather than a change in arithmetic strategy. Finally, the alpha-band power of adults exceeded one of the children in the left hemisphere, providing potential evidence for the fact-retrieval strategy. Since the completion of the Schulte table involves a whole set of elementary cognitive functions, the obtained results were essential for developing passive brain-computer interfaces for monitoring and adjusting a human state in the process of learning and solving cognitive tasks of various types.

Guided Search 6.0: An updated model of visual search

This paper describes Guided Search 6.0 (GS6), a revised model of visual search. When we encounter a scene, we can see something everywhere. However, we cannot recognize more than a few items at a time. Attention is used to select items so that their features can be "bound" into recognizable objects. Attention is "guided" so that items can be processed in an intelligent order. In GS6, this guidance comes from five sources of preattentive information: (1) top-down and (2) bottom-up feature guidance, (3) prior history (e.g., priming), (4) reward, and (5) scene syntax and semantics. These sources are combined into a spatial "priority map," a dynamic attentional landscape that evolves over the course of search. Selective attention is guided to the most active location in the priority map approximately 20 times per second. Guidance will not be uniform across the visual field. It will favor items near the point of fixation. Three types of functional visual field (FVFs) describe the nature of these foveal biases. There is a resolution FVF, an FVF governing exploratory eye movements, and an FVF governing covert deployments of attention. To be identified as targets or rejected as distractors, items must be compared to target templates held in memory. The binding and recognition of an attended object is modeled as a diffusion process taking > 150 ms/item. Since selection occurs more frequently than that, it follows that multiple items are undergoing recognition at the same time, though asynchronously, making GS6 a hybrid of serial and parallel processes. In GS6, if a target is not found, search terminates when an accumulating quitting signal reaches a threshold. Setting of that threshold is adaptive, allowing feedback about performance to shape subsequent searches. Simulation shows that the combination of asynchronous diffusion and a quitting signal can produce the basic patterns of response time and error data from a range of search experiments.

Coordination of top-down influence on V1 responses by interneurons and brain rhythms

Top-down processing in neocortex underlies functions such as prediction, expectation, and attention. Visual systems have much feedback connection that carries information of behavioral context. Top-down signals along feedback pathways modulate the representation of visual information in early visual areas such as primary visual cortex (V1). Recent studies have shown further that beta rhythms are responsible for the transmission of behavioral-context information to lower visual areas. However, the mechanism underlying top-down influence and the role of brain rhythms in top-down processing are poorly understood. To address these issues, we focus on experimental studies on top-down influence in visual perceptual tasks. We develop a model of visual system, in which early visual areas are subjected to top-down influence from a recognition area. We show that task-relevant information in early visual areas is regulated by a push-pull effect, produced by somatostatin-expressing interneurons and top-down signal. We also show that task-context information is coordinated by the phase-phase coupling of beta rhythms, while the local, task-relevant stimulus features are enhanced by the phase-amplitude coupling of beta and gamma rhythms. Furthermore, the feedback from a higher visual area such as secondary visual area facilitates the gating of task-relevant information in V1. The results provide insights to understanding the roles of inhibitory interneurons and brain rhythms in top-down influence on information processing in early visual areas.

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

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

Cortical gamma-band resonance preferentially transmits coherent input

Synchronization has been implicated in neuronal communication, but causal evidence remains indirect. We use optogenetics to generate depolarizing currents in pyramidal neurons of the cat visual cortex, emulating excitatory synaptic inputs under precise temporal control, while measuring spike output. The cortex transforms constant excitation into strong gamma-band synchronization, revealing the well-known cortical resonance. Increasing excitation with ramps increases the strength and frequency of synchronization. Slow, symmetric excitation profiles reveal hysteresis of power and frequency. White-noise input sequences enable causal analysis of network transmission, establishing that the cortical gamma-band resonance preferentially transmits coherent input components. Models composed of recurrently coupled excitatory and inhibitory units uncover a crucial role of feedback inhibition and suggest that hysteresis can arise through spike-frequency adaptation. The presented approach provides a powerful means to investigate the resonance properties of local circuits and probe how these properties transform input and shape transmission.

Rhythmic synchronization has been implicated in neuronal communication, yet causal evidence has remained scarce. Lewis et al. optogenetically stimulate the visual cortex to emulate synaptic input while recording spike output. Cortex resonates at the gamma band (30–90 Hz) and preferentially transmits input that is coherent to the ongoing gamma-band rhythm.

Differential contributions of synaptic and intrinsic inhibitory currents to speech segmentation via flexible phase-locking in neural oscillators

Current hypotheses suggest that speech segmentation—the initial division and grouping of the speech stream into candidate phrases, syllables, and phonemes for further linguistic processing—is executed by a hierarchy of oscillators in auditory cortex. Theta (∼3-12 Hz) rhythms play a key role by phase-locking to recurring acoustic features marking syllable boundaries. Reliable synchronization to quasi-rhythmic inputs, whose variable frequency can dip below cortical theta frequencies (down to ∼1 Hz), requires “flexible” theta oscillators whose underlying neuronal mechanisms remain unknown. Using biophysical computational models, we found that the flexibility of phase-locking in neural oscillators depended on the types of hyperpolarizing currents that paced them. Simulated cortical theta oscillators flexibly phase-locked to slow inputs when these inputs caused both (i) spiking and (ii) the subsequent buildup of outward current sufficient to delay further spiking until the next input. The greatest flexibility in phase-locking arose from a synergistic interaction between intrinsic currents that was not replicated by synaptic currents at similar timescales. Flexibility in phase-locking enabled improved entrainment to speech input, optimal at mid-vocalic channels, which in turn supported syllabic-timescale segmentation through identification of vocalic nuclei. Our results suggest that synaptic and intrinsic inhibition contribute to frequency-restricted and -flexible phase-locking in neural oscillators, respectively. Their differential deployment may enable neural oscillators to play diverse roles, from reliable internal clocking to adaptive segmentation of quasi-regular sensory inputs like speech.

Oscillatory activity in auditory cortex is believed to play an important role in auditory and speech processing. One suggested function of these rhythms is to divide the speech stream into candidate phonemes, syllables, words, and phrases, to be matched with learned linguistic templates. This requires brain rhythms to flexibly synchronize with regular acoustic features of the speech stream. How neuronal circuits implement this task remains unknown. In this study, we explored the contribution of inhibitory currents to flexible phase-locking in neuronal theta oscillators, believed to perform initial syllabic segmentation. We found that a combination of specific intrinsic inhibitory currents at multiple timescales, present in a large class of cortical neurons, enabled exceptionally flexible phase-locking, which could be used to precisely segment speech by identifying vowels at mid-syllable. This suggests that the cells exhibiting these currents are a key component in the brain’s auditory and speech processing architecture.

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

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

Differential Involvement of EEG Oscillatory Components in Sameness versus Spatial-Relation Visual Reasoning Tasks

The development of deep convolutional neural networks (CNNs) has recently led to great successes in computer vision, and CNNs have become de facto computational models of vision. However, a growing body of work suggests that they exhibit critical limitations on tasks beyond image categorization. Here, we study one such fundamental limitation, concerning the judgment of whether two simultaneously presented items are the same or different (SD) compared with a baseline assessment of their spatial relationship (SR). In both human subjects and artificial neural networks, we test the prediction that SD tasks recruit additional cortical mechanisms which underlie critical aspects of visual cognition that are not explained by current computational models. We thus recorded electroencephalography (EEG) signals from human participants engaged in the same tasks as the computational models. Importantly, in humans the two tasks were matched in terms of difficulty by an adaptive psychometric procedure; yet, on top of a modulation of evoked potentials (EPs), our results revealed higher activity in the low β (16–24 Hz) band in the SD compared with the SR conditions. We surmise that these oscillations reflect the crucial involvement of additional mechanisms, such as working memory and attention, which are missing in current feed-forward CNNs.

EEG, MEG and neuromodulatory approaches to explore cognition: Current status and future directions

Neural oscillations and their association with brain states and cognitive functions have been object of extensive investigation over the last decades. Several electroencephalography (EEG) and magnetoencephalography (MEG) analysis approaches have been explored and oscillatory properties have been identified, in parallel with the technical and computational advancement. This review provides an up-to-date account of how EEG/MEG oscillations have contributed to the understanding of cognition. Methodological challenges, recent developments and translational potential, along with future research avenues, are discussed.

Oscillations as a window into neuronal mechanisms underlying dorsal anterior cingulate cortex function

The function of dorsal Anterior Cingulate Cortex (dACC) remains poorly understood. While many methods, spanning bottom-up and top-down approaches, have been deployed, the view they offer is often conflicting. Integrating bottom-up and top-down approaches requires an intermediary with sufficient explanatory power, theoretical development, and empirical support. Oscillations in the local field potential (LFP) provide such a link. LFP oscillations arise from empirically well-characterized neuronal circuit motifs. Synchronizing the firing of individual units has appealing properties to bind disparate brain regions and propagate information, including gating, routing, and coding. Moreover, the LFP, rather than single unit activity, more closely relates to macro-scale recordings, such as the electroencephalogram and functional magnetic resonance imaging. Thus, LFP oscillations are a critical link that allow for the inference of neuronal micro-circuitry underlying macroscopic brain recordings.

Brain connectomes come of age

Databases of consistent, directed- and weighted inter-areal connectivity for mouse, macaque and marmoset monkeys have recently become available and begun to be used to build structural and dynamical models. A structural hierarchy can be defined based by laminar patterns of cortical connections. A large-scale dynamical model of the macaque cortex endowed with a laminar structure accounts for empirically observed frequency-modulated interplay between bottom-up and top-down processes. Signal propagation in the model with spiking neurons displays a threshold of stimulus amplitude for the activity to gain access to the prefrontal cortex, reminiscent of the ignition phenomenon associated with conscious perception. These two examples illustrate how connectomics inform structurally based dynamic models of multi-regional brain systems. Theory raises novel questions for future anatomical and physiological empirical research, in a back-and-forth collaboration between experimentalists and theorists. Directed- and weighted inter-areal cortical connectivity matrices of macaque, marmoset and mouse exhibit similarities as well as marked differences. The new connectomic data provide quantitative information for structural and dynamical modeling of multi-regional cortical circuit providing insight to the global cortical function. Quantification of cortical hierarchy guides investigations of interplay between bottom-up and top-down information processes.

Cortical beta oscillations reflect the contextual gating of visual action feedback

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

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

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

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DCM suggests underlying changes in cortical (visual) excitability.

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

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

Long-range phase synchronization of high-frequency oscillations in human cortex

Inter-areal synchronization of neuronal oscillations at frequencies below ~100 Hz is a pervasive feature of neuronal activity and is thought to regulate communication in neuronal circuits. In contrast, faster activities and oscillations have been considered to be largely local-circuit-level phenomena without large-scale synchronization between brain regions. We show, using human intracerebral recordings, that 100–400 Hz high-frequency oscillations (HFOs) may be synchronized between widely distributed brain regions. HFO synchronization expresses individual frequency peaks and exhibits reliable connectivity patterns that show stable community structuring. HFO synchronization is also characterized by a laminar profile opposite to that of lower frequencies. Importantly, HFO synchronization is both transiently enhanced and suppressed in separate frequency bands during a response-inhibition task. These findings show that HFO synchronization constitutes a functionally significant form of neuronal spike-timing relationships in brain activity and thus a mesoscopic indication of neuronal communication per se.

High-frequency oscillations (HFOs) are common in mammalian brains and have been assumed to be strictly local. Using human intracerebral recordings, the authors find that HFOs can be phase synchronized across long distances between active cortical sites during resting and task states, which may reflect neuronal communication.

Spike Timing in the Attention Network Predicts Behavioral Outcome Prior to Target Selection

There has been little evidence linking changes in spiking activity that occur prior to a spatially predictable target (i.e., prior to target selection) to behavioral outcomes, despite such preparatory changes being widely assumed to enhance the sensitivity of sensory processing. We simultaneously recorded from frontal and parietal nodes of the attention network while macaques performed a spatial cueing task. When anticipating a spatially predictable target, different patterns of coupling between spike timing and the oscillatory phase in local field potentials-but not changes in spike rate-were predictive of different behavioral outcomes. These behaviorally relevant differences in local and between-region synchronization occurred among specific cell types that were defined based on their sensory and motor properties, providing insight into the mechanisms underlying enhanced sensory processing prior to target selection. We propose that these changes in neural synchronization reflect differential anticipatory engagement of the network nodes and functional units that shape attention-related sampling.

Dynamic Modulation of Cortical Excitability during Visual Active Sensing

Visual physiology is traditionally investigated by presenting stimuli with gaze held constant. However, during active viewing of a scene, information is actively acquired using systematic patterns of fixations and saccades. Prior studies suggest that during such active viewing, both nonretinal, saccade-related signals and “extra-classical” receptive field inputs modulate visual processing. This study used a set of active viewing tasks that allowed us to compare visual responses with and without direct foveal input, thus isolating the contextual eye movement-related influences. Studying nonhuman primates, we find strong contextual modulation in primary visual cortex (V1): excitability and response amplification immediately after fixation onset, transiting to suppression leading up to the next saccade. Time-frequency decomposition suggests that this amplification and suppression cycle stems from a phase reset of ongoing neuronal oscillatory activity. The impact of saccade-related contextual modulation on stimulus processing makes active visual sensing fundamentally different from the more passive processes investigated in traditional paradigms.

By isolating contextual eye movement-related influences during active vision, Barczak et al. show that eye movements affect excitability in V1 such that responses are amplified immediately after fixation onset and suppressed as the next saccade approaches. This amplification and suppression cycle stems from a phase reset of ambient oscillatory activity in V1.

Altered Connectivity During a False-Belief Task in Adults With Autism Spectrum Disorder

BACKGROUND

Deficits in social communication are one of the main features of autism spectrum disorder (ASD). Adults with ASD show atypical brain activity during false-belief understanding, an aspect of social communication involving the ability to infer that an individual can have an incorrect belief about a situation. Our study is the first to investigate whether adults with ASD exhibit differences in frequency-specific functional connectivity patterns during false-belief reasoning.

METHODS

We used magnetoencephalography to contrast functional connectivity underlying false-belief understanding between 40 adults with ASD and 39 control adults. We examined whole-brain phase synchrony measures during a false-belief task in 3 frequency bands: theta (4-7 Hz), alpha (8-14 Hz), and beta (15-30 Hz).

RESULTS

Adults with ASD demonstrated reduced theta-band connectivity compared with control adults between several right-lateralized and midline regions such as the medial prefrontal cortex, right temporoparietal junction, right inferior frontal gyrus, and right superior temporal gyrus. During false-belief trials, they also recruited a network in the beta band that included primary visual regions such as the bilateral inferior occipital gyri and the left anterior temporoparietal junction.

CONCLUSIONS

Reduced theta-band synchrony between areas associated with mentalizing, inhibition, and visual processing implies some difficulty in communication among these functions in ASD. This impairment in top-down control in the theta band may be counterbalanced by their engagement of a beta-band network because both the left anterior temporoparietal junction and beta-band oscillations are associated with attentional processes. Thus, adults with ASD demonstrate alternative neural mechanisms for successful false-belief reasoning.

Converging intracortical signatures of two separated processing timescales in human early auditory cortex

Neural oscillations in auditory cortex are argued to support parsing and representing speech constituents at their corresponding temporal scales. Yet, how incoming sensory information interacts with ongoing spontaneous brain activity, what features of the neuronal microcircuitry underlie spontaneous and stimulus-evoked spectral fingerprints, and what these fingerprints entail for stimulus encoding, remain largely open questions. We used a combination of human invasive electrophysiology, computational modeling and decoding techniques to assess the information encoding properties of brain activity and to relate them to a plausible underlying neuronal microarchitecture. We analyzed intracortical auditory EEG activity from 10 patients while they were listening to short sentences. Pre-stimulus neural activity in early auditory cortical regions often exhibited power spectra with a shoulder in the delta range and a small bump in the beta range. Speech decreased power in the beta range, and increased power in the delta-theta and gamma ranges. Using multivariate machine learning techniques, we assessed the spectral profile of information content for two aspects of speech processing: detection and discrimination. We obtained better phase than power information decoding, and a bimodal spectral profile of information content with better decoding at low (delta-theta) and high (gamma) frequencies than at intermediate (beta) frequencies. These experimental data were reproduced by a simple rate model made of two subnetworks with different timescales, each composed of coupled excitatory and inhibitory units, and connected via a negative feedback loop. Modeling and experimental results were similar in terms of pre-stimulus spectral profile (except for the iEEG beta bump), spectral modulations with speech, and spectral profile of information content. Altogether, we provide converging evidence from both univariate spectral analysis and decoding approaches for a dual timescale processing infrastructure in human auditory cortex, and show that it is consistent with the dynamics of a simple rate model.

Cortical Responses to Input From Distant Areas are Modulated by Local Spontaneous Alpha/Beta Oscillations

Any given area in human cortex may receive input from multiple, functionally heterogeneous areas, potentially representing different processing threads. Alpha (8-13 Hz) and beta oscillations (13-20 Hz) have been hypothesized by other investigators to gate local cortical processing, but their influence on cortical responses to input from other cortical areas is unknown. To study this, we measured the effect of local oscillatory power and phase on cortical responses elicited by single-pulse electrical stimulation (SPES) at distant cortical sites, in awake human subjects implanted with intracranial electrodes for epilepsy surgery. In 4 out of 5 subjects, the amplitudes of corticocortical evoked potentials (CCEPs) elicited by distant SPES were reproducibly modulated by the power, but not the phase, of local oscillations in alpha and beta frequencies. Specifically, CCEP amplitudes were higher when average oscillatory power just before distant SPES (-110 to -10 ms) was high. This effect was observed in only a subset (0-33%) of sites with CCEPs and, like the CCEPs themselves, varied with stimulation at different distant sites. Our results suggest that although alpha and beta oscillations may gate local processing, they may also enhance the responsiveness of cortex to input from distant cortical sites.

Top-down versus bottom-up attention differentially modulate frontal-parietal connectivity

The moment-to-moment focus of our mind's eye results from a complex interplay of voluntary and involuntary influences on attention. Previous neuroimaging studies suggest that the brain networks of voluntary versus involuntary attention can be segregated into a frontal-versus-parietal or a dorsal-versus-ventral partition-although recent work suggests that the dorsal network may be involved in both bottom-up and top-down attention. Research with nonhuman primates has provided evidence that a key distinction between top-down and bottom-up attention may be the direction of connectivity between frontal and parietal areas. Whereas typical fMRI connectivity analyses cannot disambiguate the direction of connections, dynamic causal modeling (DCM) can model directionality. Using DCM, we provide new evidence that directed connections within the dorsal attention network are differentially modulated for voluntary versus involuntary attention. These results suggest that the intraparietal sulcus exerts a baseline inhibitory effect on the frontal eye fields that is strengthened during exogenous orienting and attenuated during endogenous orienting. Furthermore, the attenuation from endogenous attention occurs even with salient peripheral cues when those cues are known to be counter predictive. Thus, directed connectivity between frontal and parietal regions of the dorsal attention network is highly influenced by the type of attention that is engaged.

Emergence of β and γ networks following multisensory training

Our perceptual reality relies on inferences about the causal structure of the world given by multiple sensory inputs. In ecological settings, multisensory events that cohere in time and space benefit inferential processes: hearing and seeing a speaker enhances speech comprehension, and the acoustic changes of flapping wings naturally pace the motion of a flock of birds. Here, we asked how a few minutes of (multi)sensory training could shape cortical interactions in a subsequent unisensory perceptual task. For this, we investigated oscillatory activity and functional connectivity as a function of individuals' sensory history during training. Human participants performed a visual motion coherence discrimination task while being recorded with magnetoencephalography. Three groups of participants performed the same task with visual stimuli only, while listening to acoustic textures temporally comodulated with the strength of visual motion coherence, or with auditory noise uncorrelated with visual motion. The functional connectivity patterns before and after training were contrasted to resting-state networks to assess the variability of common task-relevant networks, and the emergence of new functional interactions as a function of sensory history. One major finding is the emergence of a large-scale synchronization in the high γ (gamma: 60-120Hz) and β (beta: 15-30Hz) bands for individuals who underwent comodulated multisensory training. The post-training network involved prefrontal, parietal, and visual cortices. Our results suggest that the integration of evidence and decision-making strategies become more efficient following congruent multisensory training through plasticity in network routing and oscillatory regimes.

Beta power encodes contextual estimates of temporal event probability in the human brain

To prepare for an impending event of unknown temporal distribution, humans internally increase the perceived probability of event onset as time elapses. This effect is termed the hazard rate of events. We tested how the neural encoding of hazard rate changes by providing human participants with prior information on temporal event probability. We recorded behavioral and electroencephalographic (EEG) data while participants listened to continuously repeating five-tone sequences, composed of four standard tones followed by a non-target deviant tone, delivered at slow (1.6 Hz) or fast (4 Hz) rates. The task was to detect a rare target tone, which equiprobably appeared at either position two, three or four of the repeating sequence. In this design, potential target position acts as a proxy for elapsed time. For participants uninformed about the target's distribution, elapsed time to uncertain target onset increased response speed, displaying a significant hazard rate effect at both slow and fast stimulus rates. However, only in fast sequences did prior information about the target's temporal distribution interact with elapsed time, suppressing the hazard rate. Importantly, in the fast, uninformed condition pre-stimulus power synchronization in the beta band (Beta 1, 15-19 Hz) predicted the hazard rate of response times. Prior information suppressed pre-stimulus power synchronization in the same band, while still significantly predicting response times. We conclude that Beta 1 power does not simply encode the hazard rate, but-more generally-internal estimates of temporal event probability based upon contextual information.

Human Genomic Signatures of Brain Oscillations During Memory Encoding

Memory encoding is an essential step for all learning. However, the genetic and molecular mechanisms underlying human memory encoding remain poorly understood, and how this molecular framework permits the emergence of specific patterns of brain oscillations observed during mnemonic processing is unknown. Here, we directly compare intracranial electroencephalography recordings from the neocortex in individuals performing an episodic memory task with human gene expression from the same areas. We identify genes correlated with oscillatory memory effects across 6 frequency bands. These genes are enriched for autism-related genes and have preferential expression in neurons, in particular genes encoding synaptic proteins and ion channels, supporting the idea that the genes regulating voltage gradients are involved in the modulation of oscillatory patterns during successful memory encoding across brain areas. Memory-related genes are distinct from those correlated with other forms of cognitive processing and resting state fMRI. These data are the first to identify correlations between gene expression and active human brain states as well as provide a molecular window into memory encoding oscillations in the human brain.

Toward understanding the neurophysiological basis of peripersonal space: An EEG study on healthy individuals

The subcortical mechanisms subtending the sensorimotor processes related to the peripersonal space (PPS) have been well characterized, whereas less evidence is available concerning the cortical mechanisms. We investigated the theta, alpha and beta event-related spectral perturbations (ERSP) while holding the forearm in different positions into the PPS of the face. Fifty healthy individuals were subjected to EEG recording while being provided with median nerve electric stimulation at the wrist of the right hand held at different hand-to-face distances. Theta and beta rhythms were significantly perturbed depending on the hand-to-face distance, whereas alpha oscillations reflected a more general, non-specific oscillatory response to the motor task. The perturbation of theta and beta frequency bands may reflect the processes of top-down modulation overseeing the conscious spatiotemporal encoding of sensory-motor information within the PPS. In other words, such perturbation reflects the continuous update of the conscious internal representations of the PPS to build up a purposeful and reflexive motor response.

Emergence of cognitive priming and structure building from the hierarchical interaction of canonical microcircuit models

The concept of connectionism states that higher cognitive functions emerge from the interaction of many simple elements. Accordingly, research on canonical microcircuits conceptualizes findings on fundamental neuroanatomical circuits as well as recurrent organizational principles of the cerebral cortex and examines the link between architectures and their associated functionality. In this study, we establish minimal canonical microcircuit models as elements of hierarchical processing networks. Based on a combination of descriptive time simulations and explanatory state-space mappings, we show that minimal canonical microcircuits effectively segregate feedforward and feedback information flows and that feedback information conditions basic processing operations in minimal canonical microcircuits. Further, we derive and examine two prototypical meta-circuits of cooperating minimal canonical microcircuits for the neurocognitive problems of priming and structure building. Through the application of these findings to a language network of syntax parsing, this study embodies neurocognitive research on hierarchical communication in light of canonical microcircuits, cell assembly theory, and predictive coding.

Signature Patterns for Top-Down and Bottom-Up Information Processing via Cross-Frequency Coupling in Macaque Auditory Cortex

Predictive coding is a theoretical framework that provides a functional interpretation of top-down and bottom-up interactions in sensory processing. The theory suggests there are differences in message passing up versus down the cortical hierarchy. These differences result from the linear feedforward of prediction errors, and the nonlinear feedback of predictions. This implies that cross-frequency interactions should predominate top-down. But it remains unknown whether these differences are expressed in cross-frequency interactions in the brain. Here we examined bidirectional cross-frequency coupling across four sectors of the auditory hierarchy in the macaque. We computed two measures of cross-frequency coupling, phase-amplitude coupling (PAC) and amplitude-amplitude coupling (AAC). Our findings revealed distinct patterns for bottom-up and top-down information processing among cross-frequency interactions. Both top-down and bottom-up interactions made prominent use of low frequencies: low-to-low-frequency (theta, alpha, beta) and low-frequency-to-high- gamma couplings were predominant top-down, while low-frequency-to-low-gamma couplings were predominant bottom-up. These patterns were largely preserved across coupling types (PAC and AAC) and across stimulus types (natural and synthetic auditory stimuli), suggesting that they are a general feature of information processing in auditory cortex. Our findings suggest the modulatory effect of low frequencies on gamma-rhythms in distant regions is important for bidirectional information transfer. The finding of low-frequency-to-low-gamma interactions in the bottom-up direction suggest that nonlinearities may also play a role in feedforward message passing. Altogether, the patterns of cross-frequency interaction we observed across the auditory hierarchy are largely consistent with the predictive coding framework.

Modulation of Beta Oscillations for Implicit Motor Timing in Primate Sensorimotor Cortex during Movement Preparation

Motor timing is an important part of sensorimotor control. Previous studies have shown that beta oscillations embody the process of temporal perception in explicit timing tasks. In contrast, studies focusing on beta oscillations in implicit timing tasks are lacking. In this study, we set up an implicit motor timing task and found a modulation pattern of beta oscillations with temporal perception during movement preparation. We trained two macaques in a repetitive visually-guided reach-to-grasp task with different holding intervals. Spikes and local field potentials were recorded from microelectrode arrays in the primary motor cortex, primary somatosensory cortex, and posterior parietal cortex. We analyzed the association between beta oscillations and temporal interval in fixed-duration experiments (500 ms as the Short Group and 1500 ms as the Long Group) and random-duration experiments (500 ms to 1500 ms). The results showed that the peak beta frequencies in both experiments ranged from 15 Hz to 25 Hz. The beta power was higher during the hold period than the movement (reach and grasp) period. Further, in the fixed-duration experiments, the mean power as well as the maximum rate of change of beta power in the first 300 ms were higher in the Short Group than in the Long Group when aligned with the Center Hit event. In contrast, in the random-duration experiments, the corresponding values showed no statistical differences among groups. The peak latency of beta power was shorter in the Short Group than in the Long Group in the fixed-duration experiments, while no consistent modulation pattern was found in the random-duration experiments. These results indicate that beta oscillations can modulate with temporal interval in their power mode. The synchronization period of beta power could reflect the cognitive set maintaining working memory of the temporal structure and attention.

Long-range functional coupling predicts performance: Oscillatory EEG networks in multisensory processing

The integration of sensory signals from different modalities requires flexible interaction of remote brain areas. One candidate mechanism to establish communication in the brain is transient synchronization of oscillatory neural signals. Although there is abundant evidence for the involvement of cortical oscillations in brain functions based on the analysis of local power, assessment of the phase dynamics among spatially distributed neuronal populations and their relevance for behavior is still sparse. In the present study, we investigated the interaction between remote brain areas by analyzing high-density electroencephalogram (EEG) data obtained from human participants engaged in a visuotactile pattern matching task. We deployed an approach for purely data-driven clustering of neuronal phase coupling in source space, which allowed imaging of large-scale functional networks in space, time and frequency without defining a priori constraints. Based on the phase coupling results, we further explored how brain areas interacted across frequencies by computing phase-amplitude coupling. Several networks of interacting sources were identified with our approach, synchronizing their activity within and across the theta (∼5 Hz), alpha (∼10 Hz), and beta (∼20 Hz) frequency bands and involving multiple brain areas that have previously been associated with attention and motor control. We demonstrate the functional relevance of these networks by showing that phase delays - in contrast to spectral power - were predictive of task performance. The data-driven analysis approach employed in the current study allowed an unbiased examination of functional brain networks based on EEG source level connectivity data. Showcased for multisensory processing, our results provide evidence that large-scale neuronal coupling is vital to long-range communication in the human brain and relevant for the behavioral outcome in a cognitive task.

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.

The Strength of Alpha-Beta Oscillatory Coupling Predicts Motor Timing Precision

Precise timing makes the difference between harmony and cacophony, but how the brain achieves precision during timing is unknown. In this study, human participants (7 females, 5 males) generated a time interval while being recorded with magnetoencephalography. Building on the proposal that the coupling of neural oscillations provides a temporal code for information processing in the brain, we tested whether the strength of oscillatory coupling was sensitive to self-generated temporal precision. On a per individual basis, we show the presence of alpha-beta phase-amplitude coupling whose strength was associated with the temporal precision of self-generated time intervals, not with their absolute duration. Our results provide evidence that active oscillatory coupling engages α oscillations in maintaining the precision of an endogenous temporal motor goal encoded in β power; the when of self-timed actions. We propose that oscillatory coupling indexes the variance of neuronal computations, which translates into the precision of an individual's behavioral performance.SIGNIFICANCE STATEMENT Which neural mechanisms enable precise volitional timing in the brain is unknown, yet accurate and precise timing is essential in every realm of life. In this study, we build on the hypothesis that neural oscillations, and their coupling across time scales, are essential for the coding and for the transmission of information in the brain. We show the presence of alpha-beta phase-amplitude coupling (α-β PAC) whose strength was associated with the temporal precision of self-generated time intervals, not with their absolute duration. α-β PAC indexes the temporal precision with which information is represented in an individual's brain. Our results link large-scale neuronal variability on the one hand, and individuals' timing precision, on the other.