Serotonin transporter knockout in rats reduces beta- and gamma-band functional connectivity between the orbitofrontal cortex and amygdala during auditory discrimination.

The orbitofrontal cortex and amygdala collaborate in outcome-guided decision-making through reciprocal projections. While serotonin transporter knockout (SERT-/-) rodents show changes in outcome-guided decision-making, and in orbitofrontal cortex and amygdala neuronal activity, it remains unclear whether SERT genotype modulates orbitofrontal cortex-amygdala synchronization. We trained SERT-/- and SERT+/+ male rats to execute a task requiring to discriminate between two auditory stimuli, one predictive of a reward (CS+) and the other not (CS-), by responding through nose pokes in opposite-side ports. Overall, task acquisition was not influenced by genotype. Next, we simultaneously recorded local field potentials in the orbitofrontal cortex and amygdala of both hemispheres while the rats performed the task. Behaviorally, SERT-/- rats showed a nonsignificant trend for more accurate responses to the CS-. Electrophysiologically, orbitofrontal cortex-amygdala synchronization in the beta and gamma frequency bands during response selection was significantly reduced and associated with decreased hubness and clustering coefficient in both regions in SERT-/- rats compared to SERT+/+ rats. Conversely, theta synchronization at the time of behavioral response in the port associated with reward was similar in both genotypes. Together, our findings reveal the modulation by SERT genotype of the orbitofrontal cortex-amygdala functional connectivity during an auditory discrimination task.

Beta-band power modulation in the human amygdala differentiates between go/no-go responses in an arm-reaching task.

Objective. Traditionally known for its involvement in emotional processing, the amygdala's involvement in motor control remains relatively unexplored, with sparse investigations into the neural mechanisms governing amygdaloid motor movement and inhibition. This study aimed to characterize the amygdaloid beta-band (13-30 Hz) power between 'Go' and 'No-go' trials of an arm-reaching task.Approach. Ten participants with drug-resistant epilepsy implanted with stereoelectroencephalographic (SEEG) electrodes in the amygdala were enrolled in this study. SEEG data was recorded throughout discrete phases of a direct reach Go/No-go task, during which participants reached a touchscreen monitor or withheld movement based on a colored cue. Multitaper power analysis along with Wilcoxon signed-rank and Yates-correctedZtests were used to assess significant modulations of beta power between the Response and fixation (baseline) phases in the 'Go' and 'No-go' conditions.Main results. In the 'Go' condition, nine out of the ten participants showed a significant decrease in relative beta-band power during the Response phase (p⩽ 0.0499). In the 'No-go' condition, eight out of the ten participants presented a statistically significant increase in relative beta-band power during the response phase (p⩽ 0.0494). Four out of the eight participants with electrodes in the contralateral hemisphere and seven out of the eight participants with electrodes in the ipsilateral hemisphere presented significant modulation in beta-band power in both the 'Go' and 'No-go' conditions. At the group level, no significant differences were found between the contralateral and ipsilateral sides or between genders.Significance.This study reports beta-band power modulation in the human amygdala during voluntary movement in the setting of motor execution and inhibition. This finding supplements prior research in various brain regions associating beta-band power with motor control. The distinct beta-power modulation observed between these response conditions suggests involvement of amygdaloid oscillations in differentiating between motor inhibition and execution.

Grasp Posture Variability Leads to Greater Ipsilateral Sensorimotor Beta Activation During Simulated Prosthesis Use.

Motor behaviour using upper-extremity prostheses of different levels is greatly variable, leading to challenges interpreting ideal rehabilitation strategies. Elucidating the underlying neural control mechanisms driving variability benefits our understanding of adaptation after limb loss. In this follow-up study, non-amputated participants completed simple and complex reach-to-grasp motor tasks using a body-powered transradial or partial-hand prosthesis simulator. We hypothesised that under complex task constraints, individuals employing variable grasp postures will show greater sensorimotor beta activation compared to individuals relying on uniform grasping, and activation will occur later in variable compared to uniform graspers. In the simple task, partial-hand variable and transradial users showed increased neural activation from the early to late phase of the reach, predominantly in the hemisphere ipsilateral to device use. In the complex task, only partial-hand variable graspers showed a significant increase in neural activation of the sensorimotor cortex from the early to the late phase of the reach. These results suggest that grasp variability may be a crucial component in the mechanism of neural adaptation to prosthesis use, and may be mediated by device level and task complexity, with implications for rehabilitation after amputation.

Developmental trajectories of EEG aperiodic and periodic components in children 2-44 months of age.

The development of neural circuits has long-lasting effects on brain function, yet our understanding of early circuit development in humans remains limited. Here, periodic EEG power features and aperiodic components were examined from longitudinal EEGs collected from 592 healthy 2-44 month-old infants, revealing age-dependent nonlinear changes suggestive of distinct milestones in early brain maturation. Developmental changes in periodic peaks include (1) the presence and then absence of a 9-10 Hz alpha peak between 2-6 months, (2) nonlinear changes in high beta peaks (20-30 Hz) between 4-18 months, and (3) the emergence of a low beta peak (12-20 Hz) in some infants after six months of age. We hypothesized that the emergence of the low beta peak may reflect maturation of thalamocortical network development. Infant anesthesia studies observe that GABA-modulating anesthetics do not induce thalamocortical mediated frontal alpha coherence until 10-12 months of age. Using a small cohort of infants (n = 23) with EEG before and during GABA-modulating anesthesia, we provide preliminary evidence that infants with a low beta peak have higher anesthesia-induced alpha coherence compared to those without a low beta peak.

Beta activity in human anterior cingulate cortex mediates reward biases.

The rewards that we get from our choices and actions can have a major influence on our future behavior. Understanding how reward biasing of behavior is implemented in the brain is important for many reasons, including the fact that diminution in reward biasing is a hallmark of clinical depression. We hypothesized that reward biasing is mediated by the anterior cingulate cortex (ACC), a cortical hub region associated with the integration of reward and executive control and with the etiology of depression. To test this hypothesis, we recorded neural activity during a biased judgment task in patients undergoing intracranial monitoring for either epilepsy or major depressive disorder. We found that beta (12-30 Hz) oscillations in the ACC predicted both associated reward and the size of the choice bias, and also tracked reward receipt, thereby predicting bias on future trials. We found reduced magnitude of bias in depressed patients, in whom the beta-specific effects were correspondingly reduced. Our findings suggest that ACC beta oscillations may orchestrate the learning of reward information to guide adaptive choice, and, more broadly, suggest a potential biomarker for anhedonia and point to future development of interventions to enhance reward impact for therapeutic benefit.

Cholinergic and behavior-dependent beta and gamma waves are coupled between olfactory bulb and hippocampus.

Olfactory oscillations may enhance cognitive processing through coupling with beta (ß, 15-30 Hz) and gamma (γ, 30-160 Hz) activity in the hippocampus (HPC). We hypothesize that coupling between olfactory bulb (OB) and HPC oscillations is increased by cholinergic activation in control rats and is reduced in kainic-acid-treated epileptic rats, a model of temporal lobe epilepsy. OB γ2 (63-100 Hz) power was higher during walking and immobility-awake (IMM) compared to sleep, while γ1 (30-57 Hz) power was higher during grooming than other behavioral states. Muscarinic cholinergic agonist pilocarpine (25 mg/kg ip) with peripheral muscarinic blockade increased OB power and OB-HPC coherence at ß and γ1 frequency bands. A similar effect was found after physostigmine (0.5 mg/kg ip) but not scopolamine (10 mg/kg ip). Pilocarpine increased bicoherence and cross-frequency coherence (CFC) between OB slow waves (SW, 1-5 Hz) and hippocampal ß, γ1 and γ2 waves, with stronger coherence at CA1 alveus and CA3c than CA1 stratum radiatum. Bicoherence further revealed a nonlinear interaction of ß waves in OB with ß waves at the CA1-alveus. Beta and γ1 waves in OB or HPC were segregated at one phase of the OB-SW, opposite to the phase of γ2 and γ3 (100-160 Hz) waves, suggesting independent temporal processing of ß/γ1 versus γ2/γ3 waves. At CA1 radiatum, kainic-acid-treated epileptic rats compared to control rats showed decreased theta power, theta-ß and theta-γ2 CFC during baseline walking, decreased CFC of HPC SW with γ2 and γ3 waves during baseline IMM, and decreased coupling of OB SW with ß and γ2 waves at CA1 alveus after pilocarpine. It is concluded that ß and γ waves in the OB and HPC are modulated by a slow respiratory rhythm, in a cholinergic and behavior-dependent manner, and OB-HPC functional connectivity at ß and γ frequencies may enhance cognitive functions.

Beta and theta oscillations track effort and previous reward in the human basal ganglia and prefrontal cortex during decision making.

Choosing whether to exert effort to obtain rewards is fundamental to human motivated behavior. However, the neural dynamics underlying the evaluation of reward and effort in humans is poorly understood. Here, we report an exploratory investigation into this with chronic intracranial recordings from the prefrontal cortex (PFC) and basal ganglia (BG; subthalamic nuclei and globus pallidus) in people with Parkinson's disease performing a decision-making task with offers that varied in levels of reward and physical effort required. This revealed dissociable neural signatures of reward and effort, with BG beta (12 to 20 Hz) oscillations tracking effort on a single-trial basis and PFC theta (4 to 7 Hz) signaling previous trial reward, with no effects of net subjective value. Stimulation of PFC increased overall acceptance of offers and sensitivity to reward while decreasing the impact of effort on choices. This work uncovers oscillatory mechanisms that guide fundamental decisions to exert effort for reward across BG and PFC, supports a causal role of PFC for such choices, and seeds hypotheses for future studies.

Low and high beta rhythms have different motor cortical sources and distinct roles in movement control and spatiotemporal attention.

Low and high beta frequency rhythms were observed in the motor cortex, but their respective sources and behavioral correlates remain unknown. We studied local field potentials (LFPs) during pre-cued reaching behavior in macaques. They contained a low beta band (<20 Hz) dominant in primary motor cortex and a high beta band (>20 Hz) dominant in dorsal premotor cortex (PMd). Low beta correlated positively with reaction time (RT) from visual cue onset and negatively with uninstructed hand postural micro-movements throughout the trial. High beta reflected temporal task prediction, with selective modulations before and during cues, which were enhanced in moments of increased focal attention when the gaze was on the work area. This double-dissociation in sources and behavioral correlates of motor cortical low and high beta, with respect to both task-instructed and spontaneous behavior, reconciles the largely disparate roles proposed for the beta rhythm, by suggesting band-specific roles in both movement control and spatiotemporal attention.

Beta-band power classification of go/no-go arm-reaching responses in the human hippocampus.

Objective.Can we classify movement execution and inhibition from hippocampal oscillations during arm-reaching tasks? Traditionally associated with memory encoding, spatial navigation, and motor sequence consolidation, the hippocampus has come under scrutiny for its potential role in movement processing. Stereotactic electroencephalography (SEEG) has provided a unique opportunity to study the neurophysiology of the human hippocampus during motor tasks. In this study, we assess the accuracy of discriminant functions, in combination with principal component analysis (PCA), in classifying between 'Go' and 'No-go' trials in a Go/No-go arm-reaching task.Approach.Our approach centers on capturing the modulation of beta-band (13-30 Hz) power from multiple SEEG contacts in the hippocampus and minimizing the dimensional complexity of channels and frequency bins. This study utilizes SEEG data from the human hippocampus of 10 participants diagnosed with epilepsy. Spectral power was computed during a 'center-out' Go/No-go arm-reaching task, where participants reached or withheld their hand based on a colored cue. PCA was used to reduce data dimension and isolate the highest-variance components within the beta band. The Silhouette score was employed to measure the quality of clustering between 'Go' and 'No-go' trials. The accuracy of five different discriminant functions was evaluated using cross-validation.Main results.The Diagonal-Quadratic model performed best of the 5 classification models, exhibiting the lowest error rate in all participants (median: 9.91%, average: 14.67%). PCA showed that the first two principal components collectively accounted for 54.83% of the total variance explained on average across all participants, ranging from 36.92% to 81.25% among participants.Significance.This study shows that PCA paired with a Diagonal-Quadratic model can be an effective method for classifying between Go/No-go trials from beta-band power in the hippocampus during arm-reaching responses. This emphasizes the significance of hippocampal beta-power modulation in motor control, unveiling its potential implications for brain-computer interface applications.

A Model with Dopamine Depletion in Basal Ganglia and Cerebellum Predicts Changes in Thalamocortical Beta Oscillations.

Parkinsonism is presented as a motor syndrome characterized by rigidity, tremors, and bradykinesia, with Parkinson's disease (PD) being the predominant cause. The discovery that those motor symptoms result from the death of dopaminergic cells in the substantia nigra led to focus most of parkinsonism research on the basal ganglia (BG). However, recent findings point to an active involvement of the cerebellum in this motor syndrome. Here, we have developed a multiscale computational model of the rodent brain's BG-cerebellar network. Simulations showed that a direct effect of dopamine depletion on the cerebellum must be taken into account to reproduce the alterations of neural activity in parkinsonism, particularly the increased beta oscillations widely reported in PD patients. Moreover, dopamine depletion indirectly impacted spike-time-dependent plasticity at the parallel fiber-Purkinje cell synapses, degrading associative motor learning as observed in parkinsonism. Overall, these results suggest a relevant involvement of cerebellum in parkinsonism associative motor symptoms.

Aperiodic and periodic components of oscillatory brain activity in relation to cognition and symptoms in pediatric ADHD.

Children with attention-deficit/hyperactivity disorder show deficits in processing speed, as well as aberrant neural oscillations, including both periodic (oscillatory) and aperiodic (1/f-like) activity, reflecting the pattern of power across frequencies. Both components were suggested as underlying neural mechanisms of cognitive dysfunctions in attention-deficit/hyperactivity disorder. Here, we examined differences in processing speed and resting-state-Electroencephalogram neural oscillations and their associations between 6- and 12-year-old children with (n = 33) and without (n = 33) attention-deficit/hyperactivity disorder. Spectral analyses of the resting-state EEG signal using fast Fourier transform revealed increased power in fronto-central theta and beta oscillations for the attention-deficit/hyperactivity disorder group, but no differences in the theta/beta ratio. Using the parameterization method, we found a higher aperiodic exponent, which has been suggested to reflect lower neuronal excitation-inhibition, in the attention-deficit/hyperactivity disorder group. While fast Fourier transform-based theta power correlated with clinical symptoms for the attention-deficit/hyperactivity disorder group only, the aperiodic exponent was negatively correlated with processing speed across the entire sample. Finally, the aperiodic exponent was correlated with fast Fourier transform-based beta power. These results highlight the different and complementary contribution of periodic and aperiodic components of the neural spectrum as metrics for evaluation of processing speed in attention-deficit/hyperactivity disorder. Future studies should further clarify the roles of periodic and aperiodic components in additional cognitive functions and in relation to clinical status.

Robust adaptive deep brain stimulation control of in-silico non-stationary Parkinsonian neural oscillatory dynamics.

Objective. Closed-loop deep brain stimulation (DBS) is a promising therapy for Parkinson's disease (PD) that works by adjusting DBS patterns in real time from the guidance of feedback neural activity. Current closed-loop DBS mainly uses threshold-crossing on-off controllers or linear time-invariant (LTI) controllers to regulate the basal ganglia (BG) Parkinsonian beta band oscillation power. However, the critical cortex-BG-thalamus network dynamics underlying PD are nonlinear, non-stationary, and noisy, hindering accurate and robust control of Parkinsonian neural oscillatory dynamics.Approach. Here, we develop a new robust adaptive closed-loop DBS method for regulating the Parkinsonian beta oscillatory dynamics of the cortex-BG-thalamus network. We first build an adaptive state-space model to quantify the dynamic, nonlinear, and non-stationary neural activity. We then construct an adaptive estimator to track the nonlinearity and non-stationarity in real time. We next design a robust controller to automatically determine the DBS frequency based on the estimated Parkinsonian neural state while reducing the system's sensitivity to high-frequency noise. We adopt and tune a biophysical cortex-BG-thalamus network model as an in-silico simulation testbed to generate nonlinear and non-stationary Parkinsonian neural dynamics for evaluating DBS methods.Main results. We find that under different nonlinear and non-stationary neural dynamics, our robust adaptive DBS method achieved accurate regulation of the BG Parkinsonian beta band oscillation power with small control error, bias, and deviation. Moreover, the accurate regulation generalizes across different therapeutic targets and consistently outperforms current on-off and LTI DBS methods.Significance. These results have implications for future designs of closed-loop DBS systems to treat PD.

Contingent magnetic variation and beta-band oscillations in sensorimotor temporal decision-making.

The ability to accurately encode the temporal information of sensory events and hence to make prompt action is fundamental to humans' prompt behavioral decision-making. Here we examined the ability of ensemble coding (averaging multiple inter-intervals in a sound sequence) and subsequent immediate reproduction of target duration at half, equal, or double that of the perceived mean interval in a sensorimotor loop. With magnetoencephalography (MEG), we found that the contingent magnetic variation (CMV) in the central scalp varied as a function of the averaging tasks, with a faster rate for buildup amplitudes and shorter peak latencies in the "half" condition as compared to the "double" condition. ERD (event-related desynchronization) -to-ERS (event-related synchronization) latency was shorter in the "half" condition. A robust beta band (15-23 Hz) power suppression and recovery between the final tone and the action of key pressing was found for time reproduction. The beta modulation depth (i.e., the ERD-to-ERS power difference) was larger in motor areas than in primary auditory areas. Moreover, results of phase slope index (PSI) indicated that beta oscillations in the left supplementary motor area (SMA) led those in the right superior temporal gyrus (STG), showing SMA to STG directionality for the processing of sequential (temporal) auditory interval information. Our findings provide the first evidence to show that CMV and beta oscillations predict the coupling between perception and action in time averaging.

Neurofeedback-enabled beta power control with a fully implanted DBS system in patients with Parkinson's disease.

OBJECTIVE: Parkinsonian motor symptoms are linked to pathologically increased beta oscillations in the basal ganglia. Studies with externalised deep brain stimulation electrodes showed that Parkinson patients were able to rapidly gain control over these pathological basal ganglia signals through neurofeedback. Studies with fully implanted deep brain stimulation systems duplicating these promising results are required to grant transferability to daily application. METHODS: In this study, seven patients with idiopathic Parkinson's disease and one with familial Parkinson's disease were included. In a postoperative setting, beta oscillations from the subthalamic nucleus were recorded with a fully implanted deep brain stimulation system and converted to a real-time visual feedback signal. Participants were instructed to perform bidirectional neurofeedback tasks with the aim to modulate these oscillations. RESULTS: While receiving regular medication and deep brain stimulation, participants were able to significantly improve their neurofeedback ability and achieved a significant decrease of subthalamic beta power (median reduction of 31% in the final neurofeedback block). CONCLUSION: We could demonstrate that a fully implanted deep brain stimulation system can provide visual neurofeedback enabling patients with Parkinson's disease to rapidly control pathological subthalamic beta oscillations. SIGNIFICANCE: Fully-implanted DBS electrode-guided neurofeedback is feasible and can now be explored over extended timespans.

Reduced TMS-evoked EEG oscillatory activity in cortical motor regions in patients with post-COVID fatigue.

OBJECTIVE: Persistent fatigue is a major symptom of the so-called 'long-COVID syndrome', but the pathophysiological processes that cause it remain unclear. We hypothesized that fatigue after COVID-19 would be associated with altered cortical activity in premotor and motor regions. METHODS: We used transcranial magnetic stimulation combined with EEG (TMS-EEG) to explore the neural oscillatory activity of the left primary motor area (l-M1) and supplementary motor area (SMA) in a group of sixteen post-COVID patients complaining of lingering fatigue as compared to a sample of age-matched healthy controls. Perceived fatigue was assessed with the Fatigue Severity Scale (FSS) and Fatigue Rating Scale (FRS). RESULTS: Post-COVID patients showed a remarkable reduction of beta frequency in both areas. Correlation analysis exploring linear relation between neurophysiological and clinical measures revealed a significant inverse correlation between the individual level of beta oscillations evoked by TMS of SMA with the individual scores in the FRS (r(15) = -0.596; p = 0.012). CONCLUSIONS: Post-COVID fatigue is associated with a reduction of TMS-evoked beta oscillatory activity in SMA. SIGNIFICANCE: TMS-EEG could be used to identify early alterations of cortical oscillatory activity that could be related to the COVID impact in central fatigue.

Clinical asymmetry in Parkinson's disease is characterized by prevalence of subthalamic pause-burst neurons and alpha-beta oscillations.

OBJECTIVE: We aimed to establish specific biomarkers of Parkinson's disease (PD) by comparing activity of more affected (MA) and less affected (LA) subthalamic nucleus (STN) of patients with prominent clinical asymmetry. METHODS: We recorded single unit activity and local field potentials (LFP) of the STN during deep brain stimulation surgeries. Neuronal firing patterns and discharge rate, as well as oscillatory features of both single cells and LFP, were analyzed. RESULTS: We observed notable differences in proportions of irregular-burst and pause-burst, but not tonic neurons, between the hemispheres. Oscillations of pause-burst neurons correlated significantly with the bradykinesia and rigidity scores of the corresponding hemibody. LFP derived from MA STN featured greater power in 12-15 Hz. CONCLUSIONS: Our results provide evidence that the increased proportion of units with prolonged pauses may be associated with PD. We also speculate that some of them may gain rhythmicity in the alpha-beta range in relation to hypokinetic symptoms, long-term disease, or both. SIGNIFICANCE: Our findings highlight the relation between specific oscillatory features of the STN, predominance of subthalamic pause-burst units and PD pathophysiology.

Cross-Frequency Coupling as a Biomarker for Early Stroke Recovery.

BACKGROUND: The application of neuroimaging-based biomarkers in stroke has enriched our understanding of post-stroke recovery mechanisms, including alterations in functional connectivity based on synchronous oscillatory activity across various cortical regions. Phase-amplitude coupling, a type of cross-frequency coupling, may provide additional mechanistic insight. OBJECTIVE: To determine how the phase of prefrontal cortex delta (1-3 Hz) oscillatory activity mediates the amplitude of motor cortex beta (13-20 Hz) oscillations in individual's early post-stroke. METHODS: Participants admitted to an inpatient rehabilitation facility completed resting and task-based EEG recordings and motor assessments around the time of admission and discharge along with structural neuroimaging. Unimpaired controls completed EEG procedures during a single visit. Mixed-effects linear models were performed to assess within- and between-group differences in delta-beta prefrontomotor coupling. Associations between coupling and motor status and injury were also determined. RESULTS: Thirty individuals with stroke and 17 unimpaired controls participated. Coupling was greater during task versus rest conditions for all participants. Though coupling during affected extremity task performance decreased during hospitalization, coupling remained elevated at discharge compared to controls. Greater baseline coupling was associated with better motor status at admission and discharge and positively related to motor recovery. Coupling demonstrated both positive and negative associations with injury involving measures of lesion volume and overlap injury to anterior thalamic radiation, respectively. CONCLUSIONS: This work highlights the utility of prefrontomotor cross-frequency coupling as a potential motor status and recovery biomarker in stroke. The frequency- and region-specific neurocircuitry featured in this work may also facilitate novel treatment strategies in stroke.

Tracking the neurodevelopmental trajectory of beta band oscillations with optically pumped magnetometer-based magnetoencephalography.

Neural oscillations mediate the coordination of activity within and between brain networks, supporting cognition and behaviour. How these processes develop throughout childhood is not only an important neuroscientific question but could also shed light on the mechanisms underlying neurological and psychiatric disorders. However, measuring the neurodevelopmental trajectory of oscillations has been hampered by confounds from instrumentation. In this paper, we investigate the suitability of a disruptive new imaging platform - optically pumped magnetometer-based magnetoencephalography (OPM-MEG) - to study oscillations during brain development. We show how a unique 192-channel OPM-MEG device, which is adaptable to head size and robust to participant movement, can be used to collect high-fidelity electrophysiological data in individuals aged between 2 and 34 years. Data were collected during a somatosensory task, and we measured both stimulus-induced modulation of beta oscillations in sensory cortex, and whole-brain connectivity, showing that both modulate significantly with age. Moreover, we show that pan-spectral bursts of electrophysiological activity drive task-induced beta modulation, and that their probability of occurrence and spectral content change with age. Our results offer new insights into the developmental trajectory of beta oscillations and provide clear evidence that OPM-MEG is an ideal platform for studying electrophysiology in neurodevelopment.

Decreased Beta Power and OFC-STN Phase Synchronization during Reactive Stopping in Freely Behaving Rats.

During natural behavior, an action often needs to be suddenly stopped in response to an unexpected sensory input-referred to as reactive stopping. Reactive stopping has been mostly investigated in humans, which led to hypotheses about the involvement of different brain structures, in particular the hyperdirect pathway. Here, we directly investigate the contribution and interaction of two key regions of the hyperdirect pathway, the orbitofrontal cortex (OFC) and subthalamic nucleus (STN), using dual-area, multielectrode recordings in male rats performing a stop-signal task. In this task, rats have to initiate movement to a go-signal, and occasionally stop their movement to the go-signal side after a stop-signal, presented at various stop-signal delays. Both the OFC and STN show near-simultaneous field potential reductions in the beta frequency range (12-30 Hz) compared with the period preceding the go-signal and the movement period. These transient reductions (∼200 ms) only happen during reactive stopping, which is when the stop-signal was received after action initiation, and are well timed after stop-signal onset and before the estimated time of stopping. Phase synchronization analysis also showed a transient attenuation of synchronization between the OFC and STN in the beta range during reactive stopping. The present results provide the first direct quantification of local neural oscillatory activity in the OFC and STN and interareal synchronization specifically timed during reactive stopping.

Motor imagery of finger movements: Effects on cortical and muscle activities.

PURPOSE: The purpose of the current study was to explore the immediate effect of motor imagery (MI) involving finger movement of a given limb on cortical response and muscle activity in healthy subjects. METHODS: Twenty healthy right-handed adults (7 females and 13 males) with a mean + SD age of 22.05 + 6.08 years participated in the study. The beta-band event-related desynchronization (ERD) at the sensorimotor cortex and muscle activity during finger movement tasks using either the index, middle, or thumb digits on the non-dominant left hand were compared before and after an MI training session. Subjects underwent a pre-MI, MI training, and finally a post-MI session where they either performed or imagined performing a button-pushing action 50 times per session with each of the three digits. RESULTS: The ERD power in the beta frequency band was lower in pre-MI compared to post-MI and was significantly different between the pre- and post-MI sessions for both the index and middle fingers, but not the thumb. A significant decrease was seen in the mean muscle activity during post-MI compared to pre-MI for all the digits except the thumb. CONCLUSIONS: The results from the current study suggest that complex MI can result in motor learning and improvement in motor performance, thereby requiring less effort during motion.