A θ-γ oscillation code for neuronal coordination during motor behavior

Adults with cerebral palsy exhibit uncharacteristic cortical oscillations during an adaptive sensorimotor control task

Prior research has shown that the sensorimotor cortical oscillations are uncharacteristic in persons with cerebral palsy (CP); however, it is unknown if these altered cortical oscillations have an impact on adaptive sensorimotor control. This investigation evaluated the cortical dynamics when the motor action needs to be changed "on-the-fly". Adults with CP and neurotypical controls completed a sensorimotor task that required either proactive or reactive control while undergoing magnetoencephalography (MEG). When compared with the controls, the adults with CP had a weaker beta (18-24 Hz) event-related desynchronization (ERD), post-movement beta rebound (PMBR, 16-20 Hz) and theta (4-6 Hz) event-related synchronization (ERS) in the sensorimotor cortices. In agreement with normative work, the controls exhibited differences in the strength of the sensorimotor gamma (66-84 Hz) ERS during proactive compared to reactive trials, but similar condition-wise changes were not seen in adults with CP. Lastly, the adults with CP who had a stronger theta ERS tended to have better hand dexterity, as indicated by the Box and Blocks Test and Purdue Pegboard Test. These results may suggest that alterations in the theta and gamma cortical oscillations play a role in the altered hand dexterity and uncharacteristic adaptive sensorimotor control noted in adults with CP.

High-Gamma Activity Is Coupled to Low-Gamma Oscillations in Precentral Cortices and Modulates with Movement and Speech

Planning and executing motor behaviors requires coordinated neural activity among multiple cortical and subcortical regions of the brain. Phase-amplitude coupling between the high-gamma band amplitude and the phase of low frequency oscillations (theta, alpha, beta) has been proposed to reflect neural communication, as has synchronization of low-gamma oscillations. However, coupling between low-gamma and high-gamma bands has not been investigated. Here, we measured phase-amplitude coupling between low- and high-gamma in monkeys performing a reaching task and in humans either performing finger-flexion or word-reading tasks. We found significant coupling between low-gamma phase and high-gamma amplitude in multiple sensorimotor and premotor cortices of both species during all tasks. This coupling modulated with the onset of movement. These findings suggest that interactions between the low and high gamma bands are markers of network dynamics related to movement and speech generation.

Traumatic brain injury disrupts state-dependent functional cortical connectivity in a mouse model

Traumatic brain injury (TBI) is the leading cause of death in young people and can cause cognitive and motor dysfunction and disruptions in functional connectivity between brain regions. In human TBI patients and rodent models of TBI, functional connectivity is decreased after injury. Recovery of connectivity after TBI is associated with improved cognition and memory, suggesting an important link between connectivity and functional outcome. We examined widespread alterations in functional connectivity following TBI using simultaneous widefield mesoscale GCaMP7c calcium imaging and electrocorticography (ECoG) in mice injured using the controlled cortical impact (CCI) model of TBI. Combining CCI with widefield cortical imaging provides us with unprecedented access to characterize network connectivity changes throughout the entire injured cortex over time. Our data demonstrate that CCI profoundly disrupts functional connectivity immediately after injury, followed by partial recovery over 3 weeks. Examining discrete periods of locomotion and stillness reveals that CCI alters functional connectivity and reduces theta power only during periods of behavioral stillness. Together, these findings demonstrate that TBI causes dynamic, behavioral state-dependent changes in functional connectivity and ECoG activity across the cortex.

Neural oscillatory activity and connectivity in children who stutter during a non-speech motor task

BACKGROUND

Neural motor control rests on the dynamic interaction of cortical and subcortical regions, which is reflected in the modulation of oscillatory activity and connectivity in multiple frequency bands. Motor control is thought to be compromised in developmental stuttering, particularly involving circuits in the left hemisphere that support speech, movement initiation, and timing control. However, to date, evidence comes from adult studies, with a limited understanding of motor processes in childhood, closer to the onset of stuttering.

METHODS

We investigated the neural control of movement initiation in children who stutter and children who do not stutter by evaluating transient changes in EEG oscillatory activity (power, phase locking to button press) and connectivity (phase synchronization) during a simple button press motor task. We compared temporal changes in these oscillatory dynamics between the left and right hemispheres and between children who stutter and children who do not stutter, using mixed-model analysis of variance.

RESULTS

We found reduced modulation of left hemisphere oscillatory power, phase locking to button press and phase connectivity in children who stutter compared to children who do not stutter, consistent with previous findings of dysfunction within the left sensorimotor circuits. Interhemispheric connectivity was weaker at lower frequencies (delta, theta) and stronger in the beta band in children who stutter than in children who do not stutter.

CONCLUSIONS

Taken together, these findings indicate weaker engagement of the contralateral left motor network in children who stutter even during low-demand non-speech tasks, and suggest that the right hemisphere might be recruited to support sensorimotor processing in childhood stuttering. Differences in oscillatory dynamics occurred despite comparable task performance between groups, indicating that an altered balance of cortical activity might be a core aspect of stuttering, observable during normal motor behavior.

Enhancing Prediction of Forelimb Movement Trajectory through a Calibrating-Feedback Paradigm Incorporating RAT Primary Motor and Agranular Cortical Ensemble Activity in the Goal-Directed Reaching Task

Complete reaching movements involve target sensing, motor planning, and arm movement execution, and this process requires the integration and communication of various brain regions. Previously, reaching movements have been decoded successfully from the motor cortex (M1) and applied to prosthetic control. However, most studies attempted to decode neural activities from a single brain region, resulting in reduced decoding accuracy during visually guided reaching motions. To enhance the decoding accuracy of visually guided forelimb reaching movements, we propose a parallel computing neural network using both M1 and medial agranular cortex (AGm) neural activities of rats to predict forelimb-reaching movements. The proposed network decodes M1 neural activities into the primary components of the forelimb movement and decodes AGm neural activities into internal feedforward information to calibrate the forelimb movement in a goal-reaching movement. We demonstrate that using AGm neural activity to calibrate M1 predicted forelimb movement can improve decoding performance significantly compared to neural decoders without calibration. We also show that the M1 and AGm neural activities contribute to controlling forelimb movement during goal-reaching movements, and we report an increase in the power of the local field potential (LFP) in beta and gamma bands over AGm in response to a change in the target distance, which may involve sensorimotor transformation and communication between the visual cortex and AGm when preparing for an upcoming reaching movement. The proposed parallel computing neural network with the internal feedback model improves prediction accuracy for goal-reaching movements.

Theta-gamma phase amplitude coupling in a hippocampal CA1 microcircuit

Phase amplitude coupling (PAC) between slow and fast oscillations is found throughout the brain and plays important functional roles. Its neural origin remains unclear. Experimental findings are often puzzling and sometimes contradictory. Most computational models rely on pairs of pacemaker neurons or neural populations tuned at different frequencies to produce PAC. Here, using a data-driven model of a hippocampal microcircuit, we demonstrate that PAC can naturally emerge from a single feedback mechanism involving an inhibitory and excitatory neuron population, which interplay to generate theta frequency periodic bursts of higher frequency gamma. The model suggests the conditions under which a CA1 microcircuit can operate to elicit theta-gamma PAC, and highlights the modulatory role of OLM and PVBC cells, recurrent connectivity, and short term synaptic plasticity. Surprisingly, the results suggest the experimentally testable prediction that the generation of the slow population oscillation requires the fast one and cannot occur without it.

High-gamma activity is coupled to low-gamma oscillations in precentral cortices and modulates with movement and speech

Planning and executing motor behaviors requires coordinated neural activity among multiple cortical and subcortical regions of the brain. Phase-amplitude coupling between the high-gamma band amplitude and the phase of low frequency oscillations (theta, alpha, beta) has been proposed to reflect neural communication, as has synchronization of low-gamma oscillations. However, coupling between low-gamma and high-gamma bands has not been investigated. Here, we measured phase-amplitude coupling between low- and high-gamma in monkeys performing a reaching task and in humans either performing finger movements or speaking words aloud. We found significant coupling between low-gamma phase and high-gamma amplitude in multiple sensorimotor and premotor cortices of both species during all tasks. This coupling modulated with the onset of movement. These findings suggest that interactions between the low and high gamma bands are markers of network dynamics related to movement and speech generation.

Cortical theta-gamma coupling governs the adaptive control of motor commands

Motor control requires the adaptive updating of internal models to successfully target desired outcomes. This adaptive control can be proactive, such that imminent actions and corresponding sensorimotor programmes are anticipated prior to movement, or reactive, such that online error correction is necessary to adjust to sudden changes. While substantial evidence implicates a distributed cortical network serving adaptive control when behavioural changes are required (e.g. response inhibition), the neural dynamics serving such control when the target motor commands are to remain intact are poorly understood. To address this, we developed a novel proactive-reactive cued finger tapping paradigm that was performed during magnetoencephalography by 25 healthy adults. Importantly, to ensure condition-wise differences in adaptive cueing were not attributable to changes in movement kinematics, motor selection and planning processes were held constant despite changes in task demands. All data were imaged in the time-frequency domain using a beamformer to evaluate the effect of proactive and reactive cues on movement-related oscillations and subsequent performance. Our results indicated spectrally specific increases in low (i.e. theta) and high (i.e. gamma) frequency oscillations during motor execution as a function of adaptive cueing. Additionally, we observed robust cross-frequency coupling of theta and gamma oscillatory power in the contralateral motor cortex and further, the strength of this theta-gamma coupling during motor execution was differentially predictive of behavioural improvements and decrements during reactive and proactive trials, respectively. These data indicate that functional oscillatory coupling may govern the adaptive control of movement in the healthy brain and importantly, may serve as effective proxies for characterizing declines in motor function in clinical populations in the future.

A Pursuit of the Degree of Nonlinearity for β Oscillations under Motor Imagery

The power of β oscillations is an essential pathological biomarker for movement disorders, parkinsonism in particular. Motor imagery training was reported to support self-regulate such β oscillations. Past studies had focused on the modulation of β oscillatory power per se, ignoring the intrinsic oscillatory characteristics-the nonlinearity of the waveform. This work applied ensemble empirical mode decomposition to decompose neural activities in multiple frequency bands without destroying the temporal characteristics of the raw signal at all scales. We explored the dynamics of the degree of nonlinearity plus the averaged power across all periods and frequency bands of interest and tested how motor imagery may or may not induce nonlinearities under various frequency bands. With motor imagery, the degree of nonlinearity for the β activity is significantly suppressed referenced to that without, of note, and the average power fails to present significant differences between segments with and without motor imagery training. Our results indicate that the degree of nonlinearity is a complementary and vital biomarker as the average power for β oscillations, thereby providing theoretical support for the possible application in motor imagery therapy. Clinical Relevance- This suggests that motor imagery can suppress irregular patterns of β oscillations for healthy, and the degree of nonlinearity is an effective feature in improving classification in training states for the MI-neurofeedback paradigm compared to that of the averaged power.

A translational perspective on pathophysiological changes of oscillatory activity in dystonia and parkinsonism

Intracerebral recordings from movement disorders patients undergoing deep brain stimulation have allowed the identification of pathophysiological patterns in oscillatory activity that correlate with symptom severity. Changes in oscillatory synchrony occur within and across brain areas, matching the classification of movement disorders as network disorders. However, the underlying mechanisms of oscillatory changes are difficult to assess in patients, as experimental interventions are technically limited and ethically problematic. This is why animal models play an important role in neurophysiological research of movement disorders. In this review, we highlight the contributions of translational research to the mechanistic understanding of pathological changes in oscillatory activity, with a focus on parkinsonism and dystonia, while addressing the limitations of current findings and proposing possible future directions.

Electrocorticographic effects of acute ketamine on non-human primate brains

OBJECTIVE

Acute blockade of glutamate N-methyl-D-aspartate (NMDA) receptors by ketamine induces symptoms and electrophysiological changes similar to schizophrenia. Previous studies have shown that ketamine elicits aberrant gamma oscillations in several cortical areas and impairs coupling strength between the low-frequency phase and fast frequency amplitude (PAC), which plays an important role in integrating functional information.

APPROACH

This study utilized a customized wireless electrocorticography (ECoG) recording device to collect subdural signals from the somatosensory and primary auditory cortices in two monkeys. Ketamine was administered at a dose of 3 mg/kg (intramuscular) or 0.56 mg/kg (intravenous) to elicit brain oscillation reactions. We analyzed the raw data using methods such as power spectral density, time-frequency spectra, and PAC.

MAIN RESULTS

Acute ketamine triggered broadband gamma and high gamma oscillation power and decreased lower frequencies. The effect was stronger in the primary auditory cortex than in the somatosensory area. The coupling strength between the low phase of theta and the faster amplitude of gamma/high gamma bands was increased by a lower dose (0.56 mg/kg iv) and decreased with a higher dose (3 mg/kg im) ketamine.

SIGNIFICANCE

Our results showed that lower and higher doses of ketamine elicited differential effects on theta-gamma PAC. These findings support the utility of ECoG models as a translational platform for pharmacodynamic research in future research.

Theta Dynamics Contribute to Retrieving Motor Plans after Interruptions in the Primate Premotor Area

To achieve a behavioral goal, we often need to maintain an internal action plan against external interruption and thereafter retrieve the action plan. We recently found that the maintenance and updating of motor plans are reflected by reciprocal changes in the beta and gamma power of the local field potential (LFP) of the primate medial motor areas. In particular, the maintenance of the immediate motor plan is supported by enhanced beta oscillations. However, it is unclear how the brain manages to maintain and retrieve the internal action plan against interruptions. Here, we show that dynamic theta changes contribute to the maintenance of the action plan. Specifically, the power of the theta frequency band (4-10 Hz) of LFPs increased before and during the interruption in the dorsal premotor areas in two monkeys. Without theta enhancement before the interruption, retrieval of the internal action plan was impaired. Theta and beta oscillations showed distinct changes depending on the behavioral context. Our results demonstrate that immediate and suspended motor plans are supported by the beta and theta oscillatory components of LFPs. Motor cortical theta oscillations may contribute to bridging motor plans across behavioral interruptions in a prospective manner.

Neural oscillatory activity serving sensorimotor control is predicted by superoxide-sensitive mitochondrial redox environments

Mitochondrial integrity and associated redox profiles have long been revered as key contributors to a host of age- and disease-related pathologies, which eventually lead to neuronal and behavioral dysfunction in the sensorimotor and other systems. However, the precise role of the mitochondrial redox environment in human sensorimotor brain systems and motor behavior remains poorly understood. Herein, we provide evidence for a strong predictive capacity of superoxide and its scavenger, superoxide dismutase, on the neural oscillatory dynamics serving motor planning and execution above and beyond the effects of mitochondrial respiratory capacities alone. Importantly, these data provide insight regarding the impact of the redox environment on the population-level neural oscillations that serve motor function in healthy humans.

Motor control requires a coordinated ensemble of spatiotemporally precise neural oscillations across a distributed motor network, particularly in the beta range (15 to 30 Hz) to successfully plan and execute volitional actions. While substantial evidence implicates beta activity as critical to motor control, the molecular processes supporting these microcircuits and their inherent oscillatory dynamics remain poorly understood. Among these processes are mitochondrial integrity and the associated redox environments, although their direct impact on human neurophysiological function is unknown. Herein, 40 healthy adults completed a motor sequence paradigm during magnetoencephalography (MEG). MEG data were imaged in the time–frequency domain using a beamformer to evaluate beta oscillatory profiles during distinct phases of motor control (i.e., planning and execution) and subsequent behavior. To comprehensively quantify features of the mitochondrial redox environment, we used state-of-the-art systems biology approaches including Seahorse Analyzer to assess mitochondrial respiration and electron paramagnetic resonance spectroscopy to measure superoxide levels in whole blood as well as antioxidant activity assays. Using structural equation modeling, we tested the relationship between mitochondrial function and sensorimotor brain-behavior dynamics through alterations in the redox environment (e.g., generation of superoxide and alteration in antioxidant defenses). Our results indicated that superoxide-sensitive but not hydrogen peroxide–sensitive features of the redox environment had direct and mediating effects on the bioenergetic–neural pathways serving motor performance in healthy adults. Importantly, our results suggest that alterations in the redox environment may directly impact behavior above and beyond mitochondrial respiratory capacities alone and further may be effective targets for age- and disease-related declines in cognitive–motor function.

Distributed cell assemblies spanning prefrontal cortex and striatum

Highly synchronous neuronal assembly activity is deemed essential for cognitive brain function. In theory, such synchrony could coordinate multiple brain areas performing complementary processes. However, cell assemblies have been observed only in single structures, typically cortical areas, and little is known about their synchrony with downstream subcortical structures, such as the striatum. Here, we demonstrate distributed cell assemblies activated at high synchrony (∼10 ms) spanning prefrontal cortex and striatum. In addition to including neurons at different brain hierarchical levels, surprisingly, they synchronized functionally distinct limbic and associative sub-regions. These assembly activations occurred when members shifted their firing phase relative to ongoing 4 Hz and theta rhythms, in association with high gamma oscillations. This suggests that these rhythms could mediate the emergence of cross-structural assemblies. To test for the role of assemblies in behavior, we trained the rats to perform a task requiring cognitive flexibility, alternating between two different rules in a T-maze. Overall, assembly activations were correlated with task-relevant parameters, including impending choice, reward, rule, or rule order. Moreover, these behavioral correlates were more robustly expressed by assemblies than by their individual member neurons. Finally, to verify whether assemblies can be endogenously generated, we found that they were indeed spontaneously reactivated during sleep and quiet immobility. Thus, cell assemblies are a more general coding mechanism than previously envisioned, linking distributed neocortical and subcortical areas at high synchrony.

Discrete spectral eigenmode-resonance network of brain dynamics and connectivity

The problem of finding a compact natural representation of brain dynamics and connectivity is addressed using an expansion in terms of physical spatial eigenmodes and their frequency resonances. It is demonstrated that this discrete expansion via the system transfer function enables linear and nonlinear dynamics to be analyzed in compact form in terms of natural dynamic "atoms," each of which is a frequency resonance of an eigenmode. Because these modal resonances are determined by the system dynamics, not the investigator, they are privileged over widely used phenomenological patterns, and obviate the need for artificial discretizations and thresholding in coordinate space. It is shown that modal resonances participate as nodes of a discrete spectral network, are noninteracting in the linear regime, but are linked nonlinearly by wave-wave coalescence and decay processes. The modal resonance formulation is shown to be capable of speeding numerical calculations of strongly nonlinear interactions. Recent work in brain dynamics, especially based on neural field theory (NFT) approaches, allows eigenmodes and their resonances to be estimated from data without assuming a specific brain model. This means that dynamic equations can be inferred using system identification methods from control theory, rather than being assumed, and resonances can be interpreted as control-systems data filters. The results link brain activity and connectivity with control-systems functions such as prediction and attention via gain control and can also be linked to specific NFT predictions if desired, thereby providing a convenient bridge between physiologically based theories and experiment. Amplitudes of modes and resonances can also be tracked to provide a more direct and temporally localized representation of the dynamics than correlations and covariances, which are widely used in the field. By synthesizing many different lines of research, this work provides a way to link quantitative electrophysiological and imaging measurements, connectivity, brain dynamics, and function. This underlines the need to move between coordinate and spectral representations as required. Moreover, standard theoretical-physics approaches and mathematical methods can be used in place of ad hoc statistical measures such as those based on graph theory of artificially discretized and decimated networks, which are highly prone to selection effects and artifacts.

Movement-Related Gamma Synchrony Differentially Predicts Behavior in the Presence of Visual Interference Across the Lifespan

The ability to allocate neural resources to task-relevant stimuli, while inhibiting distracting information in the surrounding environment (i.e., selective attention) is critical for high-level cognitive function, and declines in this ability have been linked to functional deficits in later life. Studies of age-related declines in selective attention have focused on frontal circuitry, with almost no work evaluating the contribution of motor cortical dynamics to successful task performance. Herein, we examined 69 healthy adults (23-72 years old) who completed a flanker task during magnetoencephalography (MEG). MEG data were imaged in the time-frequency domain using a beamformer to evaluate the contribution of motor cortical dynamics to age-related increases in behavioral interference effects. Our results showed that gamma oscillations in the contralateral motor cortex (M1) were a robust predictor of reaction time, regardless of interference level. Additionally, we observed condition-wise differences in gamma-by-age interactions, such that in younger adults, increases in M1 gamma power were predictive of faster reaction times during incongruent trials, while older adults did not receive this same behavioral benefit. Importantly, these data indicate that M1 gamma oscillations are differentially predictive of behavior in the presence, but not absence of visual interference, resulting in exhausted compensatory strategies with age.

Peripheral Somatosensory Entrainment Modulates the Cross-Frequency Coupling of Movement-Related Theta-Gamma Oscillations

Background: Motor control requires a reciprocal volley between somatosensory and motor systems, with somatosensory feedback being essential for the online updating of motor commands to achieve behavioral outcomes. However, this dynamic interplay among sensorimotor brain systems serving motor control remains poorly understood. Methods: To address this, we designed a novel somatosensory entrainment-movement task, which 25 adults completed during magnetoencephalography (MEG). Specifically, participants completed a quasi-paced finger-tapping paradigm while subthreshold electrical stimulation was applied to the right median nerve at a sensorimotor-relevant frequency (15 Hz) and during a second condition where no electrical stimulation was applied. The MEG data were transformed into the time-frequency domain and imaged by using a beamformer to evaluate the effect of somatosensory feedback (i.e., entrainment) on movement-related oscillations and motor performance at the single trial level. Results: Our results indicated spectrally specific reductions in movement-related oscillatory power (i.e., theta, gamma) during 15 Hz stimulation in the contralateral motor cortex during motor execution. In addition, we observed robust cross-frequency coupling within the motor cortex and further, stronger theta-gamma coupling was predictive of faster reaction times, irrespective of condition (i.e., stim vs. no stim). Finally, in the presence of electrical stimulation, cross-frequency coupling of movement-related oscillations was reduced, and the stronger the entrained neuronal populations (i.e., increased oscillatory power) were before movement onset, the weaker the inherent theta-gamma coupling became in the motor cortex. Discussion: This novel exogenous manipulation paradigm provides key insights on how the somatosensory system modulates the motor cortical oscillations required for volitional movement in the normative sensorimotor system.

Pyramidal cell subtype-dependent cortical oscillatory activity regulates motor learning

The cortex processes information through intricate circuitry and outputs to multiple brain areas by different sets of pyramidal cells (PCs). PCs form intra- and inter-laminar subnetworks, depending on PC projection subtypes. However, it remains unknown how individual PC subtypes are involved in cortical network activity and, thereby, in distinct brain functions. Here, we examined the effects of optogenetic manipulations of specific PC subtypes on network activity in the motor cortex. In layer V, the beta/gamma frequency band of oscillation was evoked by photostimulation, depending on PC subtypes. Our experimental and simulation results suggest that oscillatory activity is generated in reciprocal connections between pyramidal tract (PT) and fast-spiking cells. A similar frequency band was also observed in local field potentials during a pattern learning task. Manipulation of PT cell activity affected beta/gamma band power and learning. Our results suggest that PT cell-dependent oscillations play important roles in motor learning.

Otsuka and Kawaguchi investigate how manipulation of pyramidal cell subtypes in the motor cortex affects cortical network activity. Their findings suggest that pyramidal cell type cell-dependent oscillatory activity play an important role in motor learning.

The Effect of Transcranial Pulsed Current Stimulation at 4 and 75 Hz on Electroencephalography Theta and High Gamma Band Power: A Pilot Study

Introduction: Transcranial pulsed current stimulation (tPCS) is an emerging noninvasive brain stimulation technique that has shown significant effects on cortical excitability. To date, electrophysiological measures of the efficiency of monophasic tPCS have not been reported. Objective: We aimed to explore the effects of monophasic anodal and cathodal-tPCS (a-tPCS/c-tPCS) at theta (4 Hz) and gamma (75 Hz) frequencies on theta and high gamma electroencephalography (EEG) oscillatory power. Methods: In a single-blind, randomized, sham-controlled crossover design, 15 healthy participants were randomly assigned into 5 experimental sessions in which they received a-PCS/c-tPCS at 4 and 75 Hz or sham stimulation over the left primary motor cortex (M1) for 15 min at an intensity of 1.5 mA. Changes in theta and high gamma oscillatory power were recorded at baseline, immediately after, and 30 min after stimulation using EEG at rest with eyes open. Results: a-tPCS at 4 Hz showed a significant increase in theta power compared with sham, whereas c-tPCS at 4 Hz had no significant effect on theta power. a-tPCS at 75 Hz produced no changes in high gamma power compared with sham. Importantly, c-tPCS at 75 Hz led to a significant reduction in high gamma power compared with baseline, as well as compared with c-tPCS at 4 Hz and sham stimulation. Conclusion: The results demonstrate the modulation of oscillatory brain activity by monophasic tPCS, and highlight the need for future studies on a larger scale to confirm these initial findings. Impact statement Transcranial pulsed current stimulation (tPCS) is a novel brain stimulation technique. Recently, tPCS has been introduced to directly modulate brain oscillations by applying pulsatile current over the target brain area. Using both anodal and cathodal monophasic tPCS at theta and gamma frequencies, we demonstrate the ability of the stimulation to modulate brain activity. The present findings are the first direct electroencephalography evidence of an interaction between tPCS and ongoing oscillatory activity in the human motor cortex. Our work recommends tPCS as a tool for investigating human brain oscillations and open more studies in this area.

Interactions Between Motor Thalamic Field Potentials and Single-Unit Spiking Are Correlated With Behavior in Rats

Field potential (FP) oscillations are believed to coordinate brain activity over large spatiotemporal scales, with specific features (e.g., phase and power) in discrete frequency bands correlated with motor output. Furthermore, complex correlations between oscillations in distinct frequency bands (phase-amplitude, amplitude-amplitude, and phase-phase coupling) are commonly observed. However, the mechanisms underlying FP-behavior correlations and cross-frequency coupling remain unknown. The thalamus plays a central role in generating many circuit-level neural oscillations, and single-unit activity in motor thalamus (Mthal) is correlated with behavioral output. We, therefore, hypothesized that motor thalamic spiking coordinates motor system FPs and underlies FP-behavior correlations. To investigate this possibility, we recorded wideband motor thalamic (Mthal) electrophysiology as healthy rats performed a two-alternative forced-choice task. Delta (1–4 Hz), beta (13–30 Hz), low gamma (30–70 Hz), and high gamma (70–200 Hz) power were strongly modulated by task performance. As in the cortex, the delta phase was correlated with beta/low gamma power and reaction time. Most interestingly, subpopulations of Mthal neurons defined by their relationship to the behavior exhibited distinct relationships with FP features. Specifically, neurons whose activity was correlated with action selection and movement speed were entrained to delta oscillations. Furthermore, changes in their activity anticipated power fluctuations in beta/low gamma bands. These complex relationships suggest mechanisms for commonly observed FP-FP and spike-FP correlations, as well as subcortical influences on motor output.

Decreased neural inhibitory state in fibromyalgia pain: A cross-sectional study

OBJECTIVES

Chronic pain is one of the most common and challenging symptoms in fibromyalgia (FM). Currently, self-reported pain is the main criterion used by clinicians assessing patients with pain. However, it is subjective, and multiple factors can affect pain levels. In this study, we investigated the neural correlates of FM pain using conditioned pain modulation (CPM), electroencephalography (EEG), and transcranial magnetic stimulation (TMS).

METHODS

In this cross-sectional neurophysiological analysis of a randomized, double-blind controlled trial, 36 patients with fibromyalgia were included. We analyzed CPM, EEG variables and TMS measures and their correlation with pain levels as measured by a visual analog scale. Univariate and multivariate linear regression analyses were performed to identify the predictors of pain severity.

RESULTS

We found: (1) no association between pain levels and CPM; (2) an association between reduced alpha and beta power over the central region in resting-EEG and higher pain levels; (3) an association between smaller event-related desynchronization (ERD) responses in theta and delta bands over the central region and higher pain levels; (4) an association between smaller ERD responses in theta and delta bands and smaller intracortical inhibition and higher intracortical facilitation ratios; (5) an association between smaller ERD responses in delta band and reduced CPM.

CONCLUSIONS

Our results do not support CPM as a biomarker for pain intensity in FM. However, our specific EEG findings showing the relationship between pain, CPM and TMS measures suggest that FM leads to a disruption of inhibitory neural modulators and thus support CPM as a likely predictive marker of disrupted pain modulation system. These neurophysiological markers need to be further explored in potential future trials as to find novel targets for the treatment of FM.

Oscillations in the auditory system and their possible role

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

Parkinsonism Differently Affects the Single Neuronal Activity in the Primary and Supplementary Motor Areas in Monkeys: An Investigation in Linear and Nonlinear Domains

The changes in neuronal firing activity in the primary motor cortex (M1) and supplementary motor area (SMA) were compared in monkeys rendered parkinsonian by treatment with 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine. The neuronal dynamic was characterized using mathematical tools defined in different frameworks (rate, oscillations or complex patterns). Then, and for each cortical area, multivariate and discriminate analyses were further performed on these features to identify those important to differentiate between the normal and the pathological neuronal activity. Our results show a different order in the importance of the features to discriminate the pathological state in each cortical area which suggests that the M1 and the SMA exhibit dissimilarities in their neuronal alterations induced by parkinsonism. Our findings highlight the need for multiple mathematical frameworks to best characterize the pathological neuronal activity related to parkinsonism. Future translational studies are warranted to investigate the causal relationships between cortical region-specificities, dominant pathological hallmarks and symptoms.

Local field potential dynamics in the primate cortex in relation to parkinsonism reveled by machine learning: A comparison between the primary motor cortex and the supplementary area

The present study compares the cortical local field potentials (LFPs) in the primary motor cortex (M1) and the supplementary motor area (SMA) of non-human primates rendered Parkinsonian with administration of dopaminergic neurotoxin, 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine. The dynamic of the LFPs was investigated under several mathematical frameworks and machine learning was used to discriminate the recordings based on these features between healthy, parkinsonian with off-medication and parkinsonian with on-medication states. The importance of each feature in the discrimination process was further investigated. The dynamic of the LFPs in M1 and SMA was affected regarding its variability (time domain analysis), oscillatory activities (frequency domain analysis) and complex patterns (non-linear domain analysis). Machine learning algorithms achieved accuracy near 0.90 for comparisons between conditions. The TreeBagger algorithm provided best accuracy. The relative importance of these features differed with the cortical location, condition and treatment. Overall, the most important features included beta oscillation, fractal dimension, gamma oscillation, entropy and asymmetry of amplitude fluctuation. The importance of features in discriminating between normal and pathological states, and on- or off-medication states depends on the pair-comparison and it is region-specific. These findings are discussed regarding the refinement of current models for movement disorders and the development of on-demand therapies.

The Cortical Physiology of Ipsilateral Limb Movements

Whereas voluntary movements have long been understood to derive primarily from the cortical hemisphere contralateral to a moving limb, substantial cortical activations also occur in the same-sided, or ipsilateral, cortical hemisphere. These ipsilateral motor activations have recently been shown to be useful to decode specific movement features. Furthermore, in contrast to the classical understanding that unilateral limb movements are solely driven by the contralateral hemisphere, it appears that the ipsilateral hemisphere plays an active and specific role in the planning and execution of voluntary movements. Here we review the movement-related activations observed in the ipsilateral cortical hemisphere, interpret this evidence in light of the potential roles of the ipsilateral hemisphere in the planning and execution of movements, and describe the implications for clinical populations.

Chronic stability of single-channel neurophysiological correlates of gross and fine reaching movements in the rat

While substantial task-related neural activity has been observed during motor tasks in rodent primary motor cortex and premotor cortex, the long-term stability of these responses in healthy rats is uncertain, limiting the interpretability of longitudinal changes in the specific patterns of neural activity associated with learning or motor recovery following injury. This study examined the stability of task-related neural activity associated with execution of two distinct reaching tasks in healthy rodents. A novel automated rodent behavioral apparatus was constructed and rats were trained to perform a reaching task combining a ‘gross’ lever press and a ‘fine’ pellet retrieval. In each animal, two chronic microelectrode arrays were implanted in motor cortex spanning the caudal forelimb area (rodent primary motor cortex) and the rostral forelimb area (rodent premotor cortex). We recorded multiunit spiking and local field potential activity from 10 days to 7–10 weeks post-implantation to characterize the patterns of neural activity observed during each task component and analyzed the consistency of channel-specific task-related neural activity. Task-related changes in neural activity were observed on the majority of channels. While the task-related changes in multi-unit spiking and local field potential spectral power were consistent over several weeks, spectral power changes were more stable, despite the trade-off of decreased spatial and temporal resolution. These results show that neural activity in rodent primary and premotor cortex is associated with specific phases of reaching movements with stable patterns of task-related activity across time, establishing the relevance of the rodent for future studies designed to examine changes in task-related neural activity during recovery from focal cortical lesions.

Sequential Neural Activity in Primary Motor Cortex during Sleep

Sequential firing of neurons during sleep is thought to play a role in the consolidation of learning. However, direct evidence for such sequence replay is limited to only a few brain areas and sleep states mainly in rodents. Using a custom-designed wearable neural data logger and chronically implanted electrodes, we made long-term recordings of neural activity in the primary motor cortex of two female nonhuman primates during free behavior and natural sleep. We used the local field potential (LFP) spectrogram to characterize sleep cycles, and examined firing rates, correlations, and sequential firing of neurons at different frequency bands through the cycle. Slow-wave sleep (SWS) was characterized by low neural firing rates and high synchrony, reflecting slow oscillations between cortical down and up states. However, the order in which neurons entered up states was similar to the sequence of neural activity observed at low frequencies during waking behavior. In addition, we found evidence of brief bursts of theta oscillation, associated with non-SWS states, during which neurons fired in strikingly regular sequential order phase-locked to the LFP. Theta sequences were preserved between waking and sleep, but appeared not to resemble the order of neural activity observed at lower frequencies. The sequential firing of neurons during slow oscillations and theta bursts may contribute to the consolidation of procedural memories during sleep.SIGNIFICANCE STATEMENT Replay of sequential neural activity during sleep is believed to support consolidation of daytime learning. Despite a wealth of studies investigating sequential replay in association with episodic and spatial memory, it is unknown whether similar sequences occur in motor areas during sleep. Within long-term neural recordings from monkey motor cortex, we found two distinct patterns of sequential activity during different phases of the natural sleep cycle. Slow-wave sleep was associated with delta-band sequences that resembled low-frequency activity during movement, while occasional brief bursts of theta oscillation were associated with a different order of sequential firing. Our results are the first report of sequential sleep replay in the motor cortex, which may play an important role in consolidation of procedural learning.

Super-wide-field two-photon imaging with a micro-optical device moving in post-objective space

Wide-field imaging of neural activity at a cellular resolution is a current challenge in neuroscience. To address this issue, wide-field two-photon microscopy has been developed; however, the field size is limited by the objective size. Here, we develop a micro-opto-mechanical device that rotates within the post-objective space between the objective and brain tissue. Two-photon microscopy with this device enables sub-second sequential calcium imaging of left and right mouse sensory forelimb areas 6 mm apart. When imaging the rostral and caudal motor forelimb areas (RFA and CFA) 2 mm apart, we found high pairwise correlations in spontaneous activity between RFA and CFA neurons and between an RFA neuron and its putative axons in CFA. While mice performed a sound-triggered forelimb-movement task, the population activity between RFA and CFA covaried across trials, although the field-averaged activity was similar across trials. The micro-opto-mechanical device in the post-objective space provides a novel and flexible design to clarify the correlation structure between distant brain areas at subcellular and population levels.

Serial representation of items during working memory maintenance at letter-selective cortical sites

A key component of working memory is the ability to remember multiple items simultaneously. To understand how the human brain maintains multiple items in memory, we examined direct brain recordings of neural oscillations from neurosurgical patients as they performed a working memory task. We analyzed the data to identify the neural representations of individual memory items by identifying recording sites with broadband gamma activity that varied according to the identity of the letter a subject viewed. Next, we tested a previously proposed model of working memory, which had hypothesized that the neural representations of individual memory items sequentially occurred at different phases of the theta/alpha cycle. Consistent with this model, the phase of the theta/alpha oscillation when stimulus-related gamma activity occurred during maintenance reflected the order of list presentation. These results suggest that working memory is organized by a cortical phase code coordinated by coupled theta/alpha and gamma oscillations and, more broadly, provide support for the serial representation of items in working memory.

Learning Task-Related Activities From Independent Local-Field-Potential Components Across Motor Cortex Layers

Motor cortical microcircuits receive inputs from dispersed cortical and subcortical regions in behaving animals. However, how these inputs contribute to learning and execution of voluntary sequential motor behaviors remains elusive. Here, we analyzed the independent components extracted from the local field potential (LFP) activity recorded at multiple depths of rat motor cortex during reward-motivated movement to study their roles in motor learning. Because slow gamma (30-50 Hz), fast gamma (60-120 Hz), and theta (4-10 Hz) oscillations temporally coordinate task-relevant motor cortical activities, we first explored the behavioral state- and layer-dependent coordination of motor behavior in these frequency ranges. Consistent with previous findings, oscillations in the slow and fast gamma bands dominated during distinct movement states, i.e., preparation and execution states, respectively. However, we identified a novel independent component that dominantly appeared in deep cortical layers and exhibited enhanced slow gamma activity during the execution state. Then, we used the four major independent components to train a recurrent network model for the same lever movements as the rats performed. We show that the independent components differently contribute to the formation of various task-related activities, but they also play overlapping roles in motor learning.

Motor Cortical Gamma Oscillations: What Have We Learnt and Where Are We Headed?

PURPOSE OF REVIEW

An increase in oscillatory activity in the γ-frequency band (approximately 50-100 Hz) has long been noted during human movement. However, its functional role has been difficult to elucidate. The advent of novel techniques, particularly transcranial alternating current stimulation (tACS), has dramatically increased our ability to study γ oscillations. Here, we review our current understanding of the role of γ oscillations in the human motor cortex, with reference to γ activity outside the motor system, and evidence from animal models.

RECENT FINDINGS

Evidence for the neurophysiological basis of human γ oscillations is beginning to emerge. Multimodal studies, essential given the necessarily indirect measurements acquired in humans, are beginning to provide convergent evidence for the role of γ oscillations in movement, and their relationship to plasticity.

SUMMARY

Human motor cortical γ oscillations appear to play a key role in movement, and relate to learning. However, there are still major questions to be answered about their physiological basis and precise role in human plasticity. It is to be hoped that future research will take advantage of recent technical advances and the physiological basis and functional significance of this intriguing and important brain rhythm will be fully elucidated.

Parallel detection of theta and respiration-coupled oscillations throughout the mouse brain

Slow brain oscillations are usually coherent over long distances and thought to link distributed cell assemblies. In mice, theta (5–10 Hz) stands as one of the most studied slow rhythms. However, mice often breathe at theta frequency, and we recently reported that nasal respiration leads to local field potential (LFP) oscillations that are independent of theta. Namely, we showed respiration-coupled oscillations in the hippocampus, prelimbic cortex, and parietal cortex, suggesting that respiration could impose a global brain rhythm. Here we extend these findings by analyzing LFPs from 15 brain regions recorded simultaneously with respiration during exploration and REM sleep. We find that respiration-coupled oscillations can be detected in parallel with theta in several neocortical regions, from prefrontal to visual areas, and also in subcortical structures such as the thalamus, amygdala and ventral hippocampus. They might have escaped attention in previous studies due to the absence of respiration monitoring, the similarity with theta oscillations, and the highly variable peak frequency. We hypothesize that respiration-coupled oscillations constitute a global brain rhythm suited to entrain distributed networks into a common regime. However, whether their widespread presence reflects local network activity or is due to volume conduction remains to be determined.

Age-related changes in oscillatory power affect motor action

With increasing age cognitive performance slows down. This includes cognitive processes essential for motor performance. Additionally, performance of motor tasks becomes less accurate. The objective of the present study was to identify general neural correlates underlying age-related behavioral slowing and the reduction in motor task accuracy. To this end, we continuously recorded EEG activity from 18 younger and 24 older right-handed healthy participants while they were performing a simple finger tapping task. We analyzed the EEG records with respect to local changes in amplitude (power spectrum) as well as phase locking between the two age groups. We found differences between younger and older subjects in the amplitude of post-movement synchronization in the β band of the sensory-motor and medial prefrontal cortex (mPFC). This post-movement β amplitude was significantly reduced in older subjects. Moreover, it positively correlated with the accuracy with which subjects performed the motor task at the electrode FCz, which detects activity of the mPFC and the supplementary motor area. In contrast, we found no correlation between the accurate timing of local neural activity, i.e. phase locking in the δ-θ frequency band, with the reaction and movement time or the accuracy with which the motor task was performed. Our results show that only post-movement β amplitude and not δ-θ phase locking is involved in the control of movement accuracy. The decreased post-movement β amplitude in the mPFC of older subjects hints at an impaired deactivation of this area, which may affect the cognitive control of stimulus-induced motor tasks and thereby motor output.

Age-related changes in oscillatory power affect motor action

With increasing age cognitive performance slows down. This includes cognitive processes essential for motor performance. Additionally, performance of motor tasks becomes less accurate. The objective of the present study was to identify general neural correlates underlying age-related behavioral slowing and the reduction in motor task accuracy. To this end, we continuously recorded EEG activity from 18 younger and 24 older right-handed healthy participants while they were performing a simple finger tapping task. We analyzed the EEG records with respect to local changes in amplitude (power spectrum) as well as phase locking between the two age groups. We found differences between younger and older subjects in the amplitude of post-movement synchronization in the β band of the sensory-motor and medial prefrontal cortex (mPFC). This post-movement β amplitude was significantly reduced in older subjects. Moreover, it positively correlated with the accuracy with which subjects performed the motor task at the electrode FCz, which detects activity of the mPFC and the supplementary motor area. In contrast, we found no correlation between the accurate timing of local neural activity, i.e. phase locking in the δ-θ frequency band, with the reaction and movement time or the accuracy with which the motor task was performed. Our results show that only post-movement β amplitude and not δ-θ phase locking is involved in the control of movement accuracy. The decreased post-movement β amplitude in the mPFC of older subjects hints at an impaired deactivation of this area, which may affect the cognitive control of stimulus-induced motor tasks and thereby motor output.

Detection of self-paced movement intention from pre-movement electroencephalogram signals with Hilbert transform

The movement related cortical potential (MRCP) is a well-known neural signature of human's self-paced movement intention, which can be exploited by future neuroprosthesis. Most existing studies have explored the amplitude representation for the movement intention. In this paper we investigate the Hilbert transformed MRCP, which implicitly includes phase information complementarily to amplitude information, for the detection of self-paced upper-limb movement intention. On the datasets in which 5 healthy subjects executed a self-initiated upper limb center-out reaching task in three sessions, we have evaluated the detection model with Hilbert transformed MRCP as features and the state-of-art one with the original MRCP amplitude as features. Results show that the Hilbert transformed MRCP based detector is more accurate than the original MRCP based one.

A corticostriatal deficit promotes temporal distortion of automatic action in ageing

The acquisition of motor skills involves implementing action sequences that increase task efficiency while reducing cognitive loads. This learning capacity depends on specific cortico-basal ganglia circuits that are affected by normal ageing. Here, combining a series of novel behavioural tasks with extensive neuronal mapping and targeted cell manipulations in mice, we explored how ageing of cortico-basal ganglia networks alters the microstructure of action throughout sequence learning. We found that, after extended training, aged mice produced shorter actions and displayed squeezed automatic behaviours characterised by ultrafast oligomeric action chunks that correlated with deficient reorganisation of corticostriatal activity. Chemogenetic disruption of a striatal subcircuit in young mice reproduced age-related within-sequence features, and the introduction of an action-related feedback cue temporarily restored normal sequence structure in aged mice. Our results reveal static properties of aged cortico-basal ganglia networks that introduce temporal limits to action automaticity, something that can compromise procedural learning in ageing.

Inferring oscillatory modulation in neural spike trains

Oscillations are observed at various frequency bands in continuous-valued neural recordings like the electroencephalogram (EEG) and local field potential (LFP) in bulk brain matter, and analysis of spike-field coherence reveals that spiking of single neurons often occurs at certain phases of the global oscillation. Oscillatory modulation has been examined in relation to continuous-valued oscillatory signals, and independently from the spike train alone, but behavior or stimulus triggered firing-rate modulation, spiking sparseness, presence of slow modulation not locked to stimuli and irregular oscillations with large variability in oscillatory periods, present challenges to searching for temporal structures present in the spike train. In order to study oscillatory modulation in real data collected under a variety of experimental conditions, we describe a flexible point-process framework we call the Latent Oscillatory Spike Train (LOST) model to decompose the instantaneous firing rate in biologically and behaviorally relevant factors: spiking refractoriness, event-locked firing rate non-stationarity, and trial-to-trial variability accounted for by baseline offset and a stochastic oscillatory modulation. We also extend the LOST model to accommodate changes in the modulatory structure over the duration of the experiment, and thereby discover trial-to-trial variability in the spike-field coherence of a rat primary motor cortical neuron to the LFP theta rhythm. Because LOST incorporates a latent stochastic auto-regressive term, LOST is able to detect oscillations when the firing rate is low, the modulation is weak, and when the modulating oscillation has a broad spectral peak.

Oscillatory modulation of neural activity in the brain is widely observed under conditions associated with a variety of cognitive tasks and mental states. Within individual neurons, oscillations may be uncovered in the moment-to-moment variation in neural firing rate. This, however, is often challenging because many factors may affect fluctuations in neural firing rate and, in addition, neurons fire irregular sets of action potentials, or spike trains, due to an unknown combination of meaningful signals and extraneous noise. We have devised a statistical Latent Oscillatory Spike Train (LOST) model with accompanying model-fitting technology, that is able to detect subtle oscillations in spike trains by taking into account both spiking noise and temporal variation in the oscillation itself. The method couples two techniques developed for other purposes in the literature on Bayesian analysis. Using data simulated from theoretical neurons and real data recorded from cortical motor neurons, we demonstrate the method’s ability to track changes in the modulatory structure of the oscillation across experimental trials.

Selective entrainment of gamma subbands by different slow network oscillations

Theta oscillations (4-12 Hz) are thought to provide a common temporal reference for the exchange of information among distant brain networks. On the other hand, faster gamma-frequency oscillations (30-160 Hz) nested within theta cycles are believed to underlie local information processing. Whether oscillatory coupling between global and local oscillations, as showcased by theta-gamma coupling, is a general coding mechanism remains unknown. Here, we investigated two different patterns of oscillatory network activity, theta and respiration-induced network rhythms, in four brain regions of freely moving mice: olfactory bulb (OB), prelimbic cortex (PLC), parietal cortex (PAC), and dorsal hippocampus [cornu ammonis 1 (CA1)]. We report differential state- and region-specific coupling between the slow large-scale rhythms and superimposed fast oscillations. During awake immobility, all four regions displayed a respiration-entrained rhythm (RR) with decreasing power from OB to CA1, which coupled exclusively to the 80- to 120-Hz gamma subband (γ₂). During exploration, when theta activity was prevailing, OB and PLC still showed exclusive coupling of RR with γ₂ and no theta-gamma coupling, whereas PAC and CA1 switched to selective coupling of theta with 40- to 80-Hz (γ₁) and 120- to 160-Hz (γ₃) gamma subbands. Our data illustrate a strong, specific interaction between neuronal activity patterns and respiration. Moreover, our results suggest that the coupling between slow and fast oscillations is a general brain mechanism not limited to the theta rhythm.

Phase-amplitude coupled persistent theta and gamma oscillations in rat primary motor cortex in vitro

In vivo, theta (4-7 Hz) and gamma (30-80 Hz) neuronal network oscillations are known to coexist and display phase-amplitude coupling (PAC). However, in vitro, these oscillations have for many years been studied in isolation. Using an improved brain slice preparation technique we have, using co-application of carbachol (10 μM) and kainic acid (150 nM), elicited simultaneous theta (6.6 ± 0.1 Hz) and gamma (36.6 ± 0.4 Hz) oscillations in rodent primary motor cortex (M1). Each oscillation showed greatest power in layer V. Using a variety of time series analyses we detected significant cross-frequency coupling in 74% of slice preparations. Differences were observed in the pharmacological profile of each oscillation. Thus, gamma oscillations were reduced by the GABA_A receptor antagonists, gabazine (250 nM and 2 μM), and picrotoxin (50 μM) and augmented by AMPA receptor antagonism with SYM2206 (20 μM). In contrast, theta oscillatory power was increased by gabazine, picrotoxin and SYM2206. GABA_B receptor blockade with CGP55845 (5 μM) increased both theta and gamma power, and similar effects were seen with diazepam, zolpidem, MK801 and a series of metabotropic glutamate receptor antagonists. Oscillatory activity at both frequencies was reduced by the gap junction blocker carbenoxolone (200 μM) and by atropine (5 μM). These data show theta and gamma oscillations in layer V of rat M1 in vitro are cross-frequency coupled, and are mechanistically distinct. The development of an in vitro model of phase-amplitude coupled oscillations will facilitate further mechanistic investigation of the generation and modulation of coupled activity in mammalian cortex.

Neural Cross-Frequency Coupling: Connecting Architectures, Mechanisms, and Functions

Neural oscillations are ubiquitously observed in the mammalian brain, but it has proven difficult to tie oscillatory patterns to specific cognitive operations. Notably, the coupling between neural oscillations at different timescales has recently received much attention, both from experimentalists and theoreticians. We review the mechanisms underlying various forms of this cross-frequency coupling. We show that different types of neural oscillators and cross-frequency interactions yield distinct signatures in neural dynamics. Finally, we associate these mechanisms with several putative functions of cross-frequency coupling, including neural representations of multiple environmental items, communication over distant areas, internal clocking of neural processes, and modulation of neural processing based on temporal predictions.

Hippocampal Respiration-Driven Rhythm Distinct from Theta Oscillations in Awake Mice

We have recently described a slow oscillation in the hippocampus of urethane-anesthetized mice, which couples to nasal respiration and is clearly distinct from co-occurring theta oscillations. Here we set out to investigate whether such type of patterned network activity, which we named "hippocampal respiration rhythm" (HRR), also occurs in awake mice. In freely moving mice, instantaneous respiration rate is extremely variable, and respiration is superimposed by bouts of sniffing. To reduce this variability, we clamped the behavior of the animal to either awake immobility or treadmill running by using a head-fixed setup while simultaneously recording respiration and field potentials from the olfactory bulb (OB) and hippocampus. Head-fixed animals often exhibited long periods of steady respiration rate during either immobility or running, which allowed for spectral and coherence analyses with a sufficient frequency resolution to sort apart respiration and theta activities. We could thus demonstrate the existence of HRR in awake animals, namely, a respiration-entrained slow rhythm with highest amplitude at the dentate gyrus. HRR was most prominent during immobility and running with respiration rates slower than theta oscillations. Nevertheless, HRR could also be faster than theta. Discharges of juxtacellularly recorded cells in CA1 and dentate gyrus were modulated by HRR and theta oscillations. Granger directionality analysis revealed that HRR is caused by the OB and that theta oscillations in OB are caused by the hippocampus. Our results suggest that respiration-coupled oscillations aid the exchange of information between olfactory and memory networks.

SIGNIFICANCE STATEMENT

Olfaction is a major sense in rodents. In consequence, the olfactory bulb (OB) should be able to transmit information to downstream regions. Here we report potential mechanisms underlying such information transfer. We demonstrate the existence of a respiration-entrained rhythm in the hippocampus of awake mice. Frequencies of the hippocampal respiration rhythm (HRR) overlap with classical theta oscillations, but both rhythms are clearly distinct. HRR is most prominent in the dentate gyrus, especially when respiration is slower than theta frequency. Discharges of neurons in CA1 and dentate gyrus are modulated by both HRR and theta. Directionality analysis shows that HRR is caused by the OB. Our results suggest that respiration-coupled oscillations aid the exchange of information between olfactory and memory networks.

Area- and band-specific representations of hand movements by local field potentials in caudal cingulate motor area and supplementary motor area of monkeys

The caudal cingulate motor area (CMAc) and the supplementary motor area (SMA) play important roles in movement execution. The present study examined the neural mechanisms underlying these roles by investigating local field potentials (LFPs) from these areas while monkeys pressed buttons with either their left or right hand. During hand movement, power increases in the high-gamma (80-120 Hz) and theta (3-8 Hz) bands and a power decrease in the beta (12-30 Hz) band were observed in both the CMAc and SMA. High-gamma and beta activity in the SMA predominantly represented contralateral hand movements, whereas activity in the CMAc preferentially represented movement of either hand. Theta activity in both brain regions most frequently reflected movement of either hand, but a contralateral hand bias was more evident in the SMA than in the CMAc. An analysis of the relationships of the laterality representations between the high-gamma and theta bands at each recording site revealed that, irrespective of the hand preference for the theta band, the high-gamma band in the SMA preferentially represented contralateral hand movement, whereas the high-gamma band in the CMAc represented movement of either hand. These findings suggest that the input-output relationships for ipsilateral and contralateral hand movements in the CMAc and SMA differ in terms of their functionality. The CMAc may transform the input signals representing general aspects of movement into commands to perform movements with either hand, whereas the SMA may transform the input signals into commands to perform movement with the contralateral hand.

Differential frequency modulation of neural activity in the lateral cerebellar nucleus in failed and successful grasps

The olivo-cerebellar system has an essential role in the detection and adaptive correction of movement errors. While there is evidence of an error signal in the cerebellar cortex and inferior olivary nucleus, the deep cerebellar nuclei have been less thoroughly investigated. Here, we recorded local field potential activity in the rodent lateral cerebellar nucleus during a skilled reaching task and compared event-related changes in neural activity between unsuccessful and successful attempts. Increased low gamma (40-50 Hz) band power was present throughout the reach and grasp behavior, with no difference between successful and unsuccessful trials. Beta band (12-30 Hz) power, however, was significantly increased in unsuccessful reaches, compared to successful, throughout the trial, including during the epoch preceding knowledge of the trial's outcome. This beta band activity was greater in unsuccessful trials of high-performing days, compared to unsuccessful trials of low-performing days, indicating that this activity may reflect an error prediction signal, developed over the course of motor learning. These findings suggest an error-related discriminatory oscillatory hallmark of movement in the deep cerebellar nuclei.

The challenge of understanding the brain: where we stand in 2015

Starting with the work of Cajal more than 100 years ago, neuroscience has sought to understand how the cells of the brain give rise to cognitive functions. How far has neuroscience progressed in this endeavor? This Perspective assesses progress in elucidating five basic brain processes: visual recognition, long-term memory, short-term memory, action selection, and motor control. Each of these processes entails several levels of analysis: the behavioral properties, the underlying computational algorithm, and the cellular/network mechanisms that implement that algorithm. At this juncture, while many questions remain unanswered, achievements in several areas of research have made it possible to relate specific properties of brain networks to cognitive functions. What has been learned reveals, at least in rough outline, how cognitive processes can be an emergent property of neurons and their connections.