Transitions between Multiband Oscillatory Patterns Characterize Memory-Guided Perceptual Decisions in Prefrontal Circuits

Distractor anticipation during working memory is associated with theta and beta oscillations across spatial scales

Introduction

Anticipating distractors during working memory maintenance is critical to reduce their disruptive effects. In this study, we aimed to identify the oscillatory correlates of this process across different spatial scales of neural activity.

Methods

We simultaneously recorded local field potentials (LFP) from the lateral prefrontal cortex (LPFC) and electroencephalograms (EEG) from the scalp of monkeys performing a modified memory-guided saccade (MGS) task. The monkeys were required to remember the location of a target visual stimulus while anticipating distracting visual stimulus, flashed at 50% probability during the delay period.

Results

We found significant theta-band activity across spatial scales during anticipation of a distractor, closely linked with underlying working memory dynamics, through decoding and cross-temporal generalization analyses. EEG particularly reflected reactivation of memory around the anticipated time of a distractor, even in the absence of stimuli. During this anticipated time, beta-band activity exhibited transiently enhanced intrahemispheric communication between the LPFC and occipitoparietal brain areas. These oscillatory phenomena were observed only when the monkeys successfully performed the task, implicating their possible functional role in mitigating anticipated distractors.

Discussion

Our results demonstrate that distractor anticipation recruits multiple oscillatory processes across the brain during working memory maintenance, with a key activity observed predominantly in the theta and beta bands.

Maintenance and transformation of representational formats during working memory prioritization

Visual working memory depends on both material-specific brain areas in the ventral visual stream (VVS) that support the maintenance of stimulus representations and on regions in the prefrontal cortex (PFC) that control these representations. How executive control prioritizes working memory contents and whether this affects their representational formats remains an open question, however. Here, we analyzed intracranial EEG (iEEG) recordings in epilepsy patients with electrodes in VVS and PFC who performed a multi-item working memory task involving a retro-cue. We employed Representational Similarity Analysis (RSA) with various Deep Neural Network (DNN) architectures to investigate the representational format of prioritized VWM content. While recurrent DNN representations matched PFC representations in the beta band (15-29 Hz) following the retro-cue, they corresponded to VVS representations in a lower frequency range (3-14 Hz) towards the end of the maintenance period. Our findings highlight the distinct coding schemes and representational formats of prioritized content in VVS and PFC.

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.

Beta oscillations in vision: a (preconscious) neural mechanism for the dorsal visual stream?

Neural oscillations in alpha (8-12 Hz) and beta (13-30 Hz) frequency bands are thought to reflect feedback/reentrant loops and large-scale cortical interactions. In the last decades a main effort has been made in linking perception with alpha-band oscillations, with converging evidence showing that alpha oscillations have a key role in the temporal and featural binding of visual input, configuring the alpha rhythm a key determinant of conscious visual experience. Less attention has been historically dedicated to link beta oscillations and visual processing. Nonetheless, increasing studies report that task conditions that require to segregate/integrate stimuli in space, to disentangle local/global shapes, to spatially reorganize visual inputs, and to achieve motion perception or form-motion integration, rely on the activity of beta oscillations, with a main hub in parietal areas. In the present review, we summarize the evidence linking oscillations within the beta band and visual perception. We propose that beta oscillations represent a neural code that supports the functionality of the magnocellular-dorsal (M-D) visual pathway, serving as a fast primary neural code to exert top-down influences on the slower parvocellular-ventral visual pathway activity. Such M-D-related beta activity is proposed to act mainly pre-consciously, providing the spatial coordinates of vision and guiding the conscious extraction of objects identity that are achieved with slower alpha rhythms in ventral areas. Finally, within this new theoretical framework, we discuss the potential role of M-D-related beta oscillations in visuo-spatial attention, oculo-motor behavior and reading (dis)abilities.

Cross-modal implicit learning of random time patterns

Perception is sensitive to statistical regularities in the environment, including temporal characteristics of sensory inputs. Interestingly, implicit learning of temporal patterns in one modality can also improve their processing in another modality. However, it is unclear how cross-modal learning transfer affects neural responses to sensory stimuli. Here, we recorded neural activity of human volunteers using electroencephalography (EEG), while participants were exposed to brief sequences of randomly timed auditory or visual pulses. Some trials consisted of a repetition of the temporal pattern within the sequence, and subjects were tasked with detecting these trials. Unknown to the participants, some trials reappeared throughout the experiment across both modalities (Transfer) or only within a modality (Control), enabling implicit learning in one modality and its transfer. Using a novel method of analysis of single-trial EEG responses, we showed that learning temporal structures within and across modalities is reflected in neural learning curves. These putative neural correlates of learning transfer were similar both when temporal information learned in audition was transferred to visual stimuli and vice versa. The modality-specific mechanisms for learning of temporal information and general mechanisms which mediate learning transfer across modalities had distinct physiological signatures: temporal learning within modalities relied on modality-specific brain regions while learning transfer affected beta-band activity in frontal regions.

Update on Nonhuman Primate Models of Brain Disease and Related Research Tools

The aging of the population is an increasingly serious issue, and many age-related illnesses are on the rise. These illnesses pose a serious threat to the health and safety of elderly individuals and create a serious economic and social burden. Despite substantial research into the pathogenesis of these diseases, their etiology and pathogenesis remain unclear. In recent decades, rodent models have been used in attempts to elucidate these disorders, but such models fail to simulate the full range of symptoms. Nonhuman primates (NHPs) are the most ideal neuroscientific models for studying the human brain and are more functionally similar to humans because of their high genetic similarities and phenotypic characteristics in comparison with humans. Here, we review the literature examining typical NHP brain disease models, focusing on NHP models of common diseases such as dementia, Parkinson's disease, and epilepsy. We also explore the application of electroencephalography (EEG), magnetic resonance imaging (MRI), and optogenetic study methods on NHPs and neural circuits associated with cognitive impairment.

β Band Rhythms Influence Reaction Times

Despite their involvement in many cognitive functions, β oscillations are among the least understood brain rhythms. Reports on whether the functional role of β is primarily inhibitory or excitatory have been contradictory. Our framework attempts to reconcile these findings and proposes that several β rhythms co-exist at different frequencies. β Frequency shifts and their potential influence on behavior have thus far received little attention. In this human magnetoencephalography (MEG) experiment, we asked whether changes in β power or frequency in auditory cortex and motor cortex influence behavior (reaction times) during an auditory sweep discrimination task. We found that in motor cortex, increased β power slowed down responses, while in auditory cortex, increased β frequency slowed down responses. We further characterized β as transient burst events with distinct spectro-temporal profiles influencing reaction times. Finally, we found that increased motor-to-auditory β connectivity also slowed down responses. In sum, β power, frequency, bursting properties, cortical focus, and connectivity profile all influenced behavioral outcomes. Our results imply that the study of β oscillations requires caution as β dynamics are multifaceted phenomena, and that several dynamics must be taken into account to reconcile mixed findings in the literature.

Naturalistic Spoken Language Comprehension Is Supported by Alpha and Beta Oscillations

Brain oscillations are prevalent in all species and are involved in numerous perceptual operations. α oscillations are thought to facilitate processing through the inhibition of task-irrelevant networks, while β oscillations are linked to the putative reactivation of content representations. Can the proposed functional role of α and β oscillations be generalized from low-level operations to higher-level cognitive processes? Here we address this question focusing on naturalistic spoken language comprehension. Twenty-two (18 female) Dutch native speakers listened to stories in Dutch and French while MEG was recorded. We used dependency parsing to identify three dependency states at each word: the number of (1) newly opened dependencies, (2) dependencies that remained open, and (3) resolved dependencies. We then constructed forward models to predict α and β power from the dependency features. Results showed that dependency features predict α and β power in language-related regions beyond low-level linguistic features. Left temporal, fundamental language regions are involved in language comprehension in α, while frontal and parietal, higher-order language regions, and motor regions are involved in β. Critically, α- and β-band dynamics seem to subserve language comprehension tapping into syntactic structure building and semantic composition by providing low-level mechanistic operations for inhibition and reactivation processes. Because of the temporal similarity of the α-β responses, their potential functional dissociation remains to be elucidated. Overall, this study sheds light on the role of α and β oscillations during naturalistic spoken language comprehension, providing evidence for the generalizability of these dynamics from perceptual to complex linguistic processes.SIGNIFICANCE STATEMENT It remains unclear whether the proposed functional role of α and β oscillations in perceptual and motor function is generalizable to higher-level cognitive processes, such as spoken language comprehension. We found that syntactic features predict α and β power in language-related regions beyond low-level linguistic features when listening to naturalistic speech in a known language. We offer experimental findings that integrate a neuroscientific framework on the role of brain oscillations as "building blocks" with spoken language comprehension. This supports the view of a domain-general role of oscillations across the hierarchy of cognitive functions, from low-level sensory operations to abstract linguistic processes.

The neural mechanism of non-phase-locked EEG activity in task switching

Flexible switching between different tasks is an important cognitive ability for humans and it is often studied using the task-switching paradigm. Although the neural mechanisms of task switching have been extensively explored in previous studies using event-related potentials techniques, the activity and process mechanisms of non-phase-locked electroencephalography (EEG) have rarely been revealed. For this reason, this paper discusses the processing of non-phase-locked EEG oscillations in task switching based on frequency-band delineation. First, the roles of each frequency band in local brain regions were summarized. In particular, during the proactive control process (the cue-stimulus interval), delta, theta, and alpha oscillations played more roles in the switch condition while beta played more roles in repeat task. In the reactive control process (post-target), delta, alpha, and beta are all related to sensorimotor function. Then, utilizing the functional connectivity (FC) method, delta connections in the frontotemporal regions and theta connections located in the parietal-to-occipital sites are involved in the preparatory period before task switching, while alpha connections located in the sensorimotor areas and beta connections located in the frontal-parietal cortex are involved in response inhibition. Finally, cross-frequency coupling (CFC) play an important role in working memory among different band oscillation. The present study shows that in addition to the processing mechanisms specific to each frequency band, there are some shared and interactive neural mechanism in task switching by using different analysis techniques.

Shape and Rule Information Is Reflected in Different Local Field Potential Frequencies and Different Areas of the Primate Lateral Prefrontal Cortex

The lateral prefrontal cortex (LFPC) plays a crucial role in executive function by adaptively storing behavior-relevant information as working memory. Neural mechanisms associated with local field potentials (LFPs) may underlie the adaptive properties of the LFPC. Here, we analyzed how LFPs recorded from the monkey LFPC are modulated by the crucial factors of a shape manipulation task. In this task, the test shape is transformed by manipulating a lever to match the size and orientation of the sample shape. The subject is required to temporarily memorize the rules such as the arm-movement-manipulation relationship and the sample shape to generate the sequential behavior of operations. In the present study, we focused on task variables about shape and rules, and examined among which aspects distinguish the ventral and dorsal sides of the LFPC. We found that the transformed shape in the sample period strongly affected the theta and delta waves in the delay period on the ventral side, while the arm-manipulation assignment influenced the gamma components on the dorsal side. These findings suggest that area- and frequency-selective LFP modulations are involved in dynamically recruiting different behavior-relevant information in the LFPC.

Mechanisms of distributed working memory in a large-scale network of macaque neocortex

Neural activity underlying working memory is not a local phenomenon but distributed across multiple brain regions. To elucidate the circuit mechanism of such distributed activity, we developed an anatomically constrained computational model of large-scale macaque cortex. We found that mnemonic internal states may emerge from inter-areal reverberation, even in a regime where none of the isolated areas is capable of generating self-sustained activity. The mnemonic activity pattern along the cortical hierarchy indicates a transition in space, separating areas engaged in working memory and those which do not. A host of spatially distinct attractor states is found, potentially subserving various internal processes. The model yields testable predictions, including the idea of counterstream inhibitory bias, the role of prefrontal areas in controlling distributed attractors, and the resilience of distributed activity to lesions or inactivation. This work provides a theoretical framework for identifying large-scale brain mechanisms and computational principles of distributed cognitive processes.

Alpha-to-beta- and gamma-band activity reflect predictive coding in affective visual processing

Processing of negative affective pictures typically leads to desynchronization of alpha-to-beta frequencies (ERD) and synchronization of gamma frequencies (ERS). Given that in predictive coding higher frequencies have been associated with prediction errors, while lower frequencies have been linked to expectations, we tested the hypothesis that alpha-to-beta ERD and gamma ERS induced by aversive pictures are associated with expectations and prediction errors, respectively. We recorded EEG while volunteers were involved in a probabilistically cued affective picture task using three different negative valences to produce expectations and prediction errors. Our data show that alpha-to-beta band activity after stimulus presentation was related to the expected valence of the stimulus as predicted by a cue. The absolute mismatch of the expected and actual valence, which denotes an absolute prediction error was related to increases in alpha, beta and gamma band activity. This demonstrates that top-down predictions and bottom-up prediction errors are represented in typical spectral patterns associated with affective picture processing. This study provides direct experimental evidence that negative affective picture processing can be described by neuronal predictive coding computations.

Decreased Global EEG Synchronization in Amyloid Positive Mild Cognitive Impairment and Alzheimer's Disease Patients-Relationship to APOE ε4

The apolipoprotein E (APOE) ε4 allele is a risk factor for Alzheimer's disease (AD) that has been linked to changes in brain structure and function as well as to different biological subtypes of the disease. The present study aimed to investigate the association of APOE ε4 genotypes with brain functional impairment, as assessed by quantitative EEG (qEEG) in patients on the AD continuum. The study population included 101 amyloid positive patients diagnosed with mild cognitive impairment (MCI) (n = 50) and AD (n = 51) that underwent resting-state EEG recording and CSF Aβ42 analysis. In total, 31 patients were APOE ε4 non-carriers, 42 were carriers of one, and 28 were carriers of two APOE ε4 alleles. Quantitative EEG analysis included computation of the global field power (GFP) and global field synchronization (GFS) in conventional frequency bands. Amyloid positive patients who were carriers of APOE ε4 allele(s) had significantly higher GFP beta and significantly lower GFS in theta and beta bands compared to APOE ε4 non-carriers. Increased global EEG power in beta band in APOE ε4 carriers may represent a brain functional compensatory mechanism that offsets global EEG slowing in AD patients. Our findings suggest that decreased EEG measures of global synchronization in theta and beta bands reflect brain functional deficits related to the APOE ε4 genotype in patients that are on a biomarker-verified AD continuum.

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.

Across-Area Synchronization Supports Feature Integration in a Biophysical Network Model of Working Memory

Working memory function is severely limited. One key limitation that constrains the ability to maintain multiple items in working memory simultaneously is so-called swap errors. These errors occur when an inaccurate response is in fact accurate relative to a non-target stimulus, reflecting the failure to maintain the appropriate association or "binding" between the features that define one object (e.g., color and location). The mechanisms underlying feature binding in working memory remain unknown. Here, we tested the hypothesis that features are bound in memory through synchrony across feature-specific neural assemblies. We built a biophysical neural network model composed of two one-dimensional attractor networks - one for color and one for location - simulating feature storage in different cortical areas. Within each area, gamma oscillations were induced during bump attractor activity through the interplay of fast recurrent excitation and slower feedback inhibition. As a result, different memorized items were held at different phases of the network's oscillation. These two areas were then reciprocally connected via weak cortico-cortical excitation, accomplishing binding between color and location through the synchronization of pairs of bumps across the two areas. Encoding and decoding of color-location associations was accomplished through rate coding, overcoming a long-standing limitation of binding through synchrony. In some simulations, swap errors arose: "color bumps" abruptly changed their phase relationship with "location bumps." This model, which leverages the explanatory power of similar attractor models, specifies a plausible mechanism for feature binding and makes specific predictions about swap errors that are testable at behavioral and neurophysiological levels.

Neurophysiological responses of globus pallidus internus during the auditory oddball task in Parkinson's disease

Parkinson's disease can be associated with significant cognitive impairment that may lead to dementia. Deep brain stimulation (DBS) of the subthalamic nucleus is an effective therapy for motor symptoms but is associated with cognitive decline. DBS of globus pallidus internus (GPi) poses less risk of cognitive decline so may be the preferred target. A research priority is to identify biomarkers of cognitive decline in this population, but efforts are hampered by a lack of understanding of the role of the different basal ganglia nuclei, such as the globus pallidus, in cognitive processing. During deep brain stimulation (DBS) surgery, we monitored single units, beta oscillatory LFP activity as well as event related potentials (ERPs) from the globus pallidus internus (GPi) of 16 Parkinson's disease patients, while they performed an auditory attention task. We used an auditory oddball task, during which one standard tone is presented at regular intervals and a second deviant tone is presented with a low probability that the subject is requested to count and report at the end of the task. All forms of neuronal activity studied were selective modulated by the attended tones. Of 62 neurons studied, the majority (51 or 82%) responded selectively to the deviant tone. Beta oscillatory activity showed an overall desynchronization during both types of attended tones interspersed by bursts of beta activity giving rise to peaks at a latency of around 200 ms after tone onset. cognitive ERPs recorded in GPi were selective to the attended tone and the right-side cERP was larger than the left side. The averages of trials showing a difference in beta oscillatory activity between deviant and standard also had a significant difference in cERP amplitude. In one block of trials, the random occurrence of 3 deviant tones in short succession silenced the activity of the GPi neuron being recorded. Trial blocks where a clear difference in LFP beta was seen were twice as likely to yield a correct tone count (25 vs 11). The data demonstrate strong modulation of GPi neuronal activity during the auditory oddball task. Overall, this study demonstrates an involvement of GPi in processing of non-motor cognitive tasks such as working memory and attention, and suggests that direct effects of DBS in non-motor GPi may contribute to cognitive changes observed post-operatively.

Activity Stabilization in a Population Model of Working Memory by Sinusoidal and Noisy Inputs

According to mechanistic theories of working memory (WM), information is retained as stimulus-dependent persistent spiking activity of cortical neural networks. Yet, how this activity is related to changes in the oscillatory profile observed during WM tasks remains a largely open issue. We explore joint effects of input gamma-band oscillations and noise on the dynamics of several firing rate models of WM. The considered models have a metastable active regime, i.e., they demonstrate long-lasting transient post-stimulus firing rate elevation. We start from a single excitatory-inhibitory circuit and demonstrate that either gamma-band or noise input could stabilize the active regime, thus supporting WM retention. We then consider a system of two circuits with excitatory intercoupling. We find that fast coupling allows for better stabilization by common noise compared to independent noise and stronger amplification of this effect by in-phase gamma inputs compared to anti-phase inputs. Finally, we consider a multi-circuit system comprised of two clusters, each containing a group of circuits receiving a common noise input and a group of circuits receiving independent noise. Each cluster is associated with its own local gamma generator, so all its circuits receive gamma-band input in the same phase. We find that gamma-band input differentially stabilizes the activity of the "common-noise" groups compared to the "independent-noise" groups. If the inter-cluster connections are fast, this effect is more pronounced when the gamma-band input is delivered to the clusters in the same phase rather than in the anti-phase. Assuming that the common noise comes from a large-scale distributed WM representation, our results demonstrate that local gamma oscillations can stabilize the activity of the corresponding parts of this representation, with stronger effect for fast long-range connections and synchronized gamma oscillations.

Exact neural mass model for synaptic-based working memory

A synaptic theory of Working Memory (WM) has been developed in the last decade as a possible alternative to the persistent spiking paradigm. In this context, we have developed a neural mass model able to reproduce exactly the dynamics of heterogeneous spiking neural networks encompassing realistic cellular mechanisms for short-term synaptic plasticity. This population model reproduces the macroscopic dynamics of the network in terms of the firing rate and the mean membrane potential. The latter quantity allows us to gain insight of the Local Field Potential and electroencephalographic signals measured during WM tasks to characterize the brain activity. More specifically synaptic facilitation and depression integrate each other to efficiently mimic WM operations via either synaptic reactivation or persistent activity. Memory access and loading are related to stimulus-locked transient oscillations followed by a steady-state activity in the β-γ band, thus resembling what is observed in the cortex during vibrotactile stimuli in humans and object recognition in monkeys. Memory juggling and competition emerge already by loading only two items. However more items can be stored in WM by considering neural architectures composed of multiple excitatory populations and a common inhibitory pool. Memory capacity depends strongly on the presentation rate of the items and it maximizes for an optimal frequency range. In particular we provide an analytic expression for the maximal memory capacity. Furthermore, the mean membrane potential turns out to be a suitable proxy to measure the memory load, analogously to event driven potentials in experiments on humans. Finally we show that the γ power increases with the number of loaded items, as reported in many experiments, while θ and β power reveal non monotonic behaviours. In particular, β and γ rhythms are crucially sustained by the inhibitory activity, while the θ rhythm is controlled by excitatory synapses.

Working Memory (WM) is the ability to temporarily store and manipulate stimuli representations that are no longer available to the senses. We have developed an innovative coarse-grained population model able to mimic several operations associated to WM. The novelty of the model consists in reproducing exactly the dynamics of spiking neural networks with realistic synaptic plasticity composed of hundreds of thousands of neurons in terms of a few macroscopic variables. These variables give access to experimentally measurable quantities such as local field potentials and electroencephalographic signals. Memory operations are joined to sustained or transient oscillations emerging in different frequency bands, in accordance with experimental results for primate and humans performing WM tasks. We have designed an architecture composed of many excitatory populations and a common inhibitory pool able to store and retain several memory items. The capacity of our multi-item architecture is around 3–5 items, a value similar to the WM capacities measured in many experiments. Furthermore, the maximal capacity is achievable only for presentation rates within an optimal frequency range. Finally, we have defined a measure of the memory load analogous to the event-related potentials employed to test humans’ WM capacity during visual memory tasks.

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

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

Brain Activity during Different Throwing Games: EEG Exploratory Study

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

Functional Specialization in the Attention Network

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

Multimodal exploration of non-motor neural functions in ALS patients using simultaneous EEG-fNIRS recording

OBJECTIVE

Despite the high prevalence of non-motor impairments reported in patients with amyotrophic lateral sclerosis (ALS), little is known about the functional neural markers underlying such dysfunctions. In this study, a new dual-task multimodal framework relying on simultaneous electroencephalogram (EEG) and functional near-infrared spectroscopy (fNIRS) recordings was developed to characterize integrative non-motor neural functions in people with ALS.

APPROACH

Simultaneous EEG-fNIRS data were recorded from six subjects with ALS and twelve healthy controls. Through a proposed visuo-mental paradigm, subjects performed a set of visuo-mental arithmetic operations. The data recorded were analyzed with respect to event-related changes both in the time and frequency domains for EEG and de/oxygen-hemoglobin level (HbR/HbO) changes for fNIRS. The correlation of EEG spectral features with fNIRS HbO/HbR features were then evaluated to assess the mechanisms of ALS on the electrical (EEG)-vascular (fNIRS) interrelationships.

MAIN RESULTS

We observed overall smaller increases in EEG delta and theta power, decreases in beta power, reductions in HbO responses, and distortions both in early and later EEG event-related potentials in ALS subjects compared to healthy controls. While significant correlations between EEG features and HbO responses were observed in healthy controls, these patterns were absent in ALS patients. Distortions in both electrical and hemodynamic responses are speculated to be associated with cognitive deficits in ALS that center primarily on attentional and working memory processing.

SIGNIFICANCE

Our results highlight the important role of ALS non-motor dysfunctions in electrical and hemodynamic neural dynamics as well as their interrelationships. The insights obtained through this study can enhance our understanding of the underlying non-motor neural processes in ALS and enrich future diagnostic and prognostic techniques.

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.

Neuronal signatures of a random-dot motion comparison task

The study of perceptual decision making has made significant progress owing to major contributions from two experimental paradigms: the sequential vibrotactile frequency comparison task for the somatosensory domain requiring working memory, and the random-dot motion task in the visual domain requiring evidence accumulation over time. On the one hand, electrophysiological recordings in nonhuman primates and humans have identified changes in firing rates and power modulations of beta band oscillations with the vibrotactile frequencies held in working memory, as well as with the mental operation required for decision making. On the other hand, firing rates and centro-parietal potentials were found to increase to a fixed level at the time of responding during the random-dot motion task, possibly reflecting an underlying evidence accumulation mechanism until a decision threshold is met. Here, to bridge these two paradigms, we presented two visual random-dot motion stimuli in a sequential comparison task while recording EEG from human volunteers. We identified a modulation of prefrontal beta band power that scaled with the level of dot motion coherence of the first stimulus during a short retention interval. Furthermore, beta power in premotor areas was modulated by participants' choices approximately 700 ms before responses were given via button press. At the same time, dot motion patches of the second stimulus evoked a pattern of broadband centro-parietal signal build-up till responses were made, whose peak varied with trial difficulty. Hence, we show that known modulations of beta power during working memory and decision making extend from the vibrotactile to the visual domain and provide support for the notion of evidence accumulation as an unconfined decision-making mechanism generalizing over distinct decision types.

Pathway mechanism for excitatory and inhibitory control in working memory

Humans engage in many daily activities that rely on working memory, the ability to hold and sequence information temporarily to accomplish a task. We focus on the process of working memory, based on circuit mechanisms for attending to relevant signals and suppressing irrelevant stimuli. We discuss that connections critically depend on the systematic variation in laminar structure across all cortical systems. Laminar structure is used to group areas into types regardless of their placement in the cortex, ranging from low-type agranular areas that lack layer IV to high-type areas that have six well-delineated layers. Connections vary in laminar distribution and strength based on the difference in type between linked areas, according to the "structural model" (Barbas H, Rempel-Clower N. Cereb Cortex 7: 635-646, 1997). The many possible pathways thus vary systematically by laminar distribution and strength, and they interface with excitatory neurons to select relevant stimuli and with functionally distinct inhibitory neurons that suppress activity at the site of termination. Using prefrontal pathways, we discuss how systematic architectonic variation gives rise to diverse pathways that can be recruited, along with amygdalar and hippocampal pathways that provide sensory, affective, and contextual information. The prefrontal cortex is also connected with thalamic nuclei that receive the output of the basal ganglia and cerebellum, which may facilitate fast sequencing of information. The complement of connections and their interface with distinct inhibitory neurons allows dynamic recruitment of areas and shifts in cortical rhythms to meet rapidly changing demands of sequential components of working memory tasks.

Network mechanisms underlying the role of oscillations in cognitive tasks

Oscillatory activity robustly correlates with task demands during many cognitive tasks. However, not only are the network mechanisms underlying the generation of these rhythms poorly understood, but it is also still unknown to what extent they may play a functional role, as opposed to being a mere epiphenomenon. Here we study the mechanisms underlying the influence of oscillatory drive on network dynamics related to cognitive processing in simple working memory (WM), and memory recall tasks. Specifically, we investigate how the frequency of oscillatory input interacts with the intrinsic dynamics in networks of recurrently coupled spiking neurons to cause changes of state: the neuronal correlates of the corresponding cognitive process. We find that slow oscillations, in the delta and theta band, are effective in activating network states associated with memory recall. On the other hand, faster oscillations, in the beta range, can serve to clear memory states by resonantly driving transient bouts of spike synchrony which destabilize the activity. We leverage a recently derived set of exact mean-field equations for networks of quadratic integrate-and-fire neurons to systematically study the bifurcation structure in the periodically forced spiking network. Interestingly, we find that the oscillatory signals which are most effective in allowing flexible switching between network states are not smooth, pure sinusoids, but rather burst-like, with a sharp onset. We show that such periodic bursts themselves readily arise spontaneously in networks of excitatory and inhibitory neurons, and that the burst frequency can be tuned via changes in tonic drive. Finally, we show that oscillations in the gamma range can actually stabilize WM states which otherwise would not persist.

Dissonant Representations of Visual Space in Prefrontal Cortex during Eye Movements

We used local field potentials (LFPs) and spikes to investigate representations of visual space in prefrontal cortex and the dynamics of those representations during eye movements. Spatial information contained in LFPs of the frontal eye field (FEF) was differentially distributed across frequencies, with a majority of that information being carried in alpha and high-gamma bands and minimal signal in the low-gamma band. During fixation, spatial information from alpha and high-gamma bands and spiking activity was robust across cortical layers. Receptive fields (RFs) derived from alpha and high-gamma bands were retinocentrically organized, and they were spatially correlated both with each other and with spiking RFs. However, alpha and high-gamma RFs probed before eye movements were dissociated. Whereas high-gamma and spiking RFs immediately converged toward the movement goal, alpha RFs remained largely unchanged during the initial probe response, but they converged later. These observations reveal possible mechanisms of dynamic spatial representations that underlie visual perception during eye movements.

Gamma and beta bursts during working memory readout suggest roles in its volitional control

Working memory (WM) activity is not as stationary or sustained as previously thought. There are brief bursts of gamma (~50–120 Hz) and beta (~20–35 Hz) oscillations, the former linked to stimulus information in spiking. We examined these dynamics in relation to readout and control mechanisms of WM. Monkeys held sequences of two objects in WM to match to subsequent sequences. Changes in beta and gamma bursting suggested their distinct roles. In anticipation of having to use an object for the match decision, there was an increase in gamma and spiking information about that object and reduced beta bursting. This readout signal was only seen before relevant test objects, and was related to premotor activity. When the objects were no longer needed, beta increased and gamma decreased together with object spiking information. Deviations from these dynamics predicted behavioral errors. Thus, beta could regulate gamma and the information in WM.

Previously, the authors have shown that working memory can be maintained by brief gamma oscillation bursts. Here, the authors use a new task to further demonstrate the dynamics of gamma and beta oscillations in working memory readout, independent of behavioral response.

Cortical Connections Position Primate Area 25 as a Keystone for Interoception, Emotion, and Memory

The structural and functional integrity of subgenual cingulate area 25 (A25) is crucial for emotional expression and equilibrium. A25 has a key role in affective networks, and its disruption has been linked to mood disorders, but its cortical connections have yet to be systematically or fully studied. Using neural tracers in rhesus monkeys, we found that A25 was densely connected with other ventromedial and posterior orbitofrontal areas associated with emotions and homeostasis. A moderate pathway linked A25 with frontopolar area 10, an area associated with complex cognition, which may regulate emotions and dampen negative affect. Beyond the frontal lobe, A25 was connected with auditory association areas and memory-related medial temporal cortices, and with the interoceptive-related anterior insula. A25 mostly targeted the superficial cortical layers of other areas, where broadly dispersed terminations comingled with modulatory inhibitory or disinhibitory microsystems, suggesting a dominant excitatory effect. The architecture and connections suggest that A25 is the consummate feedback system in the PFC. Conversely, in the entorhinal cortex, A25 pathways terminated in the middle-deep layers amid a strong local inhibitory microenvironment, suggesting gating of hippocampal output to other cortices and memory storage. The graded cortical architecture and associated laminar patterns of connections suggest how areas, layers, and functionally distinct classes of inhibitory neurons can be recruited dynamically to meet task demands. The complement of cortical connections of A25 with areas associated with memory, emotion, and somatic homeostasis provide the circuit basis to understand its vulnerability in psychiatric and neurologic disorders.SIGNIFICANCE STATEMENT Integrity of the prefrontal subgenual cingulate cortex is crucial for healthy emotional function. Subgenual area 25 (A25) is mostly linked with other prefrontal areas associated with emotion in a dense network positioned to recruit large fields of cortex. In healthy states, A25 is associated with internal states, autonomic function, and transient negative affect. Constant hyperactivity in A25 is a biomarker for depression in humans and may trigger extensive activation in its dominant connections with areas associated with emotions and internal balance. A pathway between A25 and frontopolar area 10 may provide a critical link to regulate emotions and dampen persistent negative affect, which may be explored for therapeutic intervention in depression.

Beta oscillations reflect supramodal information during perceptual judgment

Previous work on perceptual decision making in the sensorimotor system has shown population dynamics in the beta band, corresponding to the encoding of stimulus properties and the final decision outcome. Here, we asked how oscillatory dynamics in the medial premotor cortex (MPC) contribute to supramodal perceptual decision making. We recorded local field potentials (LFPs) and spikes in two monkeys trained to perform a tactile-acoustic frequency discrimination task, including both unimodal and crossmodal conditions. We studied the role of oscillatory activity as a function of stimulus properties (frequency and sensory modality), as well as decision outcome. We found that beta-band power correlated with relevant stimulus properties: there was a significant modulation by stimulus frequency during the working-memory (WM) retention interval, as well as modulation by stimulus modality-the latter was observed only in the case of a purely unimodal task, where modality information was relevant to prepare for the upcoming second stimulus. Furthermore, we found a significant modulation of beta power during the comparison and decision period, which was predictive of decision outcome. Finally, beta-band spike-field coherence (SFC) matched these LFP observations. In conclusion, we demonstrate that beta power in MPC is reflective of stimulus features in a supramodal, context-dependent manner, and additionally reflects the decision outcome. We propose that these beta modulations are a signature of the recruitment of functional neuronal ensembles, which encode task-relevant information.

Prefrontal Neurons Represent Motion Signals from Across the Visual Field But for Memory-Guided Comparisons Depend on Neurons Providing These Signals

Visual decisions often involve comparisons of sequential stimuli that can appear at any location in the visual field. The lateral prefrontal cortex (LPFC) in nonhuman primates, shown to play an important role in such comparisons, receives information about contralateral stimuli directly from sensory neurons in the same hemisphere, and about ipsilateral stimuli indirectly from neurons in the opposite hemisphere. This asymmetry of sensory inputs into the LPFC poses the question of whether and how its neurons incorporate sensory information arriving from the two hemispheres during memory-guided comparisons of visual motion. We found that, although responses of individual LPFC neurons to contralateral stimuli were stronger and emerged 40 ms earlier, they carried remarkably similar signals about motion direction in the two hemifields, with comparable direction selectivity and similar direction preferences. This similarity was also apparent around the time of the comparison between the current and remembered stimulus because both ipsilateral and contralateral responses showed similar signals reflecting the remembered direction. However, despite availability in the LPFC of motion information from across the visual field, these "comparison effects" required for the comparison stimuli to appear at the same retinal location. This strict dependence on spatial overlap of the comparison stimuli suggests participation of neurons with localized receptive fields in the comparison process. These results suggest that while LPFC incorporates many key aspects of the information arriving from sensory neurons residing in opposite hemispheres, it continues relying on the interactions with these neurons at the time of generating signals leading to successful perceptual decisions.

SIGNIFICANCE STATEMENT

Visual decisions often involve comparisons of sequential visual motion that can appear at any location in the visual field. We show that during such comparisons, the lateral prefrontal cortex (LPFC) contains accurate representation of visual motion from across the visual field, supplied by motion processing neurons. However, at the time of comparison, LPFC neurons can only use this information to compute the differences between the stimuli, if stimuli appear at the same retinal location, implicating neurons with localized receptive fields in the comparison process. These findings show that sensory comparisons rely on the interactions between LPFC and sensory neurons that not only supply sensory signals but also actively participate in the comparison of these signals at the time of the decision.

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

Among the rhythms of the brain, oscillations in the beta frequency range (∼13-30 Hz) have been considered the most enigmatic. Traditionally associated with sensorimotor functions, beta oscillations have recently become more broadly implicated in top-down processing, long-range communication, and preservation of the current brain state. Here, we extend and refine these views based on accumulating new findings of content-specific beta-synchronization during endogenous information processing in working memory (WM) and decision making. We characterize such content-specific beta activity as short-lived, flexible network dynamics supporting the endogenous (re)activation of cortical representations. Specifically, we suggest that beta-mediated ensemble formation within and between cortical areas may awake, rather than merely preserve, an endogenous cognitive set in the service of current task demands. This proposal accommodates key aspects of content-specific beta modulations in monkeys and humans, integrates with timely computational models, and outlines a functional role for beta that fits its transient temporal characteristics.

Controlling Working Memory Operations by Selective Gating: The Roles of Oscillations and Synchrony

Working memory (WM) is a primary cognitive function that corresponds to the ability to update, stably maintain, and manipulate short-term memory (ST M) rapidly to perform ongoing cognitive tasks. A prevalent neural substrate of WM coding is persistent neural activity, the property of neurons to remain active after having been activated by a transient sensory stimulus. This persistent activity allows for online maintenance of memory as well as its active manipulation necessary for task performance. WM is tightly capacity limited. Therefore, selective gating of sensory and internally generated information is crucial for WM function. While the exact neural substrate of selective gating remains unclear, increasing evidence suggests that it might be controlled by modulating ongoing oscillatory brain activity. Here, we review experiments and models that linked selective gating, persistent activity, and brain oscillations, putting them in the more general mechanistic context of WM. We do so by defining several operations necessary for successful WM function and then discussing how such operations may be carried out by mechanisms suggested by computational models. We specifically show how oscillatory mechanisms may provide a rapid and flexible active gating mechanism for WM operations.

Oscillatory Dynamics of Prefrontal Cognitive Control

The prefrontal cortex (PFC) provides the structural basis for numerous higher cognitive functions. However, it is still largely unknown which mechanisms provide the functional basis for flexible cognitive control of goal-directed behavior. Here, we review recent findings that suggest that the functional architecture of cognition is profoundly rhythmic and propose that the PFC serves as a conductor to orchestrate task-relevant large-scale networks. We highlight several studies that demonstrated that oscillatory dynamics, such as phase resetting, cross-frequency coupling (CFC), and entrainment, support PFC-dependent recruitment of task-relevant regions into coherent functional networks. Importantly, these findings support the notion that distinct spectral signatures reflect different cortical computations supporting effective multiplexing on different temporal channels along the same anatomical pathways.

Oscillations in the bistable regime of neuronal networks

Bistability between attracting fixed points in neuronal networks has been hypothesized to underlie persistent activity observed in several cortical areas during working memory tasks. In network models this kind of bistability arises due to strong recurrent excitation, sufficient to generate a state of high activity created in a saddle-node (SN) bifurcation. On the other hand, canonical network models of excitatory and inhibitory neurons (E-I networks) robustly produce oscillatory states via a Hopf (H) bifurcation due to the E-I loop. This mechanism for generating oscillations has been invoked to explain the emergence of brain rhythms in the β to γ bands. Although both bistability and oscillatory activity have been intensively studied in network models, there has not been much focus on the coincidence of the two. Here we show that when oscillations emerge in E-I networks in the bistable regime, their phenomenology can be explained to a large extent by considering coincident SN and H bifurcations, known as a codimension two Takens-Bogdanov bifurcation. In particular, we find that such oscillations are not composed of a stable limit cycle, but rather are due to noise-driven oscillatory fluctuations. Furthermore, oscillations in the bistable regime can, in principle, have arbitrarily low frequency.