Computational modelling of movement-related beta-oscillatory dynamics in human motor cortex

Oscillatory activity in the beta range, in human primary motor cortex (M1), shows interesting dynamics that are tied to behaviour and change systematically in disease. To investigate the pathophysiology underlying these changes, we must first understand how changes in beta activity are caused in healthy subjects. We therefore adapted a canonical (repeatable) microcircuit model used in dynamic causal modelling (DCM) previously used to model induced responses in visual cortex. We adapted this model to accommodate cytoarchitectural differences between visual and motor cortex. Using biologically plausible connections, we used Bayesian model selection to identify the best model of measured MEG data from 11 young healthy participants, performing a simple handgrip task. We found that the canonical M1 model had substantially more model evidence than the generic canonical microcircuit model when explaining measured MEG data. The canonical M1 model reproduced measured dynamics in humans at rest, in a manner consistent with equivalent studies performed in mice. Furthermore, the changes in excitability (self-inhibition) necessary to explain beta suppression during handgrip were consistent with the attenuation of sensory precision implied by predictive coding. These results establish the face validity of a model that can be used to explore the laminar interactions that underlie beta-oscillatory dynamics in humans in vivo. Our canonical M1 model may be useful for characterising the synaptic mechanisms that mediate pathophysiological beta dynamics associated with movement disorders, such as stroke or Parkinson's disease

Increasing human motor skill acquisition by driving theta-gamma coupling

Skill learning is a fundamental adaptive process, but the mechanisms remain poorly understood. Some learning paradigms, particularly in the memory domain, are closely associated with gamma activity that is amplitude-modulated by the phase of underlying theta activity, but whether such nested activity patterns also underpin skill learning is unknown. Here we addressed this question by using transcranial alternating current stimulation (tACS) over sensorimotor cortex to modulate theta-gamma activity during motor skill acquisition, as an exemplar of a non-hippocampal-dependent task. We demonstrated, and then replicated, a significant improvement in skill acquisition with theta-gamma tACS, which outlasted the stimulation by an hour. Our results suggest that theta-gamma activity may be a common mechanism for learning across the brain and provides a putative novel intervention for optimising functional improvements in response to training or therapy

Computational modelling of movement-related beta-oscillatory dynamics in human motor cortex

Oscillatory activity in the beta range, in human primary motor cortex (M1), shows interesting dynamics that are tied to behaviour and change systematically in disease. To investigate the pathophysiology underlying these changes, we must first understand how changes in beta activity are caused in healthy subjects. We therefore adapted a canonical (repeatable) microcircuit model used in dynamic causal modelling (DCM) previously used to model induced responses in visual cortex. We adapted this model to accommodate cytoarchitectural differences between visual and motor cortex. Using biologically plausible connections, we used Bayesian model selection to identify the best model of measured MEG data from 11 young healthy participants, performing a simple handgrip task. We found that the canonical M1 model had substantially more model evidence than the generic canonical microcircuit model when explaining measured MEG data. The canonical M1 model reproduced measured dynamics in humans at rest, in a manner consistent with equivalent studies performed in mice. Furthermore, the changes in excitability (self-inhibition) necessary to explain beta suppression during handgrip were consistent with the attenuation of sensory precision implied by predictive coding. These results establish the face validity of a model that can be used to explore the laminar interactions that underlie beta-oscillatory dynamics in humans in vivo. Our canonical M1 model may be useful for characterising the synaptic mechanisms that mediate pathophysiological beta dynamics associated with movement disorders, such as stroke or Parkinson's disease

Motor training modulates intracortical inhibitory dynamics in motor cortex during movement preparation

BACKGROUND: The primary motor cortex (M1) has a vital role to play in the learning of novel motor skills. However, the physiological changes underpinning this learning, particularly in terms of dynamic changes during movement preparation, are incompletely understood. In particular, a substantial decrease in resting gamma-amino butyric acid (GABA) activity, i.e. a release of resting inhibition, is seen within M1 as a subject prepares to move. Although there is evidence that a decrease in resting inhibition occurs within M1 during motor learning it is not known whether the pre-movement "release" of GABAergic inhibition is modulated during skill acquisition. OBJECTIVE: Here, we investigated changes in pre-movement GABAergic inhibitory "release" during training on a motor skill task. METHODS: We studied GABAA activity using paired-pulse TMS (Short-Interval Intracortical Inhibition (SICI)) during training on a ballistic thumb abduction task, both at rest and at two time-points during movement preparation. RESULTS: Improvement in task performance was related to a later, steeper, release of inhibition during the movement preparation phase. Specifically, subjects who showed greater improvement in the task in the early stages of training showed a reduced level of GABAergic release immediately prior to movement compared with those who improved less. Later in training, subjects who performed better showed a reduction in GABAergic release early in movement preparation. CONCLUSIONS: These findings suggest that motor training is associated with maintained inhibition in motor cortex during movement preparation

Motor training modulates intracortical inhibitory dynamics in motor cortex during movement preparation

Background The primary motor cortex (M1) has a vital role to play in the learning of novel motor skills. However, the physiological changes underpinning this learning, particularly in terms of dynamic changes during movement preparation, are incompletely understood. In particular, a substantial decrease in resting gamma-amino butyric acid (GABA) activity, i.e. a release of resting inhibition, is seen within M1 as a subject prepares to move. Although there is evidence that a decrease in resting inhibition occurs within M1 during motor learning it is not known whether the pre-movement “release” of GABAergic inhibition is modulated during skill acquisition. Objective Here, we investigated changes in pre-movement GABAergic inhibitory “release” during training on a motor skill task. Methods We studied GABAA activity using paired-pulse TMS (Short-Interval Intracortical Inhibition (SICI)) during training on a ballistic thumb abduction task, both at rest and at two time-points during movement preparation. Results Improvement in task performance was related to a later, steeper, release of inhibition during the movement preparation phase. Specifically, subjects who showed greater improvement in the task in the early stages of training showed a reduced level of GABAergic release immediately prior to movement compared with those who improved less. Later in training, subjects who performed better showed a reduction in GABAergic release early in movement preparation. Conclusions These findings suggest that motor training is associated with maintained inhibition in motor cortex during movement preparation