The motor cortex controls skilled arm movement by recruiting a variety of targets in the nervous system, and it is important to understand the emergent activity in these regions as refinement of a motor skill occurs. One fundamental projection of the motor cortex (M1) is to the cerebellum. However, the emergent activity in the motor cortex and the cerebellum that appears as a dexterous motor skill is consolidated is incompletely understood. Here, we report on low-frequency oscillatory (LFO) activity that emerges in cortico-cerebellar networks with learning the reach-to-grasp motor skill. We chronically recorded the motor and the cerebellar cortices in rats which revealed the emergence of coordinated movement-related activity in the local-field potentials (LFPs) as the reaching skill consolidated. Interestingly, we found this emergent activity only in the rats that gained expertise in the task. We found that the local and cross-area spiking activity was coordinated with LFOs in proficient rats. Finally, we also found that these neural dynamics were more prominently expressed during accurate behavior in the M1. This work furthers our understanding on emergent dynamics in the cortico-cerebellar loop that underlie learning and execution of precise skilled movement.Significance StatementMovement execution involves parallel processing across brain regions, with the motor cortex (M1) being a key hub that recruits several subcortical nodes. The cerebellar cortex is a principal receiver of M1 projections via pons, but the emergent dynamics in these regions with motor skill learning is incompletely understood. We performed simultaneous recordings of M1 and cerebellum in a reach-to-grasp task. We found low frequency activity and coordinated neural dynamics emerged within and across regions with skillful task execution. Recent interest in modulating cortico-cerebellar networks for motor-recovery post-injury/stroke make this work an important precursor to assessing whether similar low-frequency activity in cortico-cerebellar networks can serve as a biomarker of motor recovery and help optimize modulation of these networks.

Background Cerebellar electrical stimulation has shown promise in improving motor recovery post-stroke in both rodent and human studies. Past studies have used motor evoked potentials (MEPs) to evaluate how cerebellar stimulation modulates ongoing activity in the cortex, but the underlying mechanisms are incompletely understood. Here we used invasive electrophysiological recordings from the intact and stroke-injured rodent primary motor cortex (M1) to assess how epidural cerebellar stimulation modulates neural dynamics at the level of single neurons as well as at the level of mesoscale dynamics. Methods We recorded single unit spiking and local field potentials (LFPs) in both the intact and acutely stroke-injured M1 contralateral to the stimulated cerebellum in adult Long-Evans rats under anesthesia. We analyzed changes in the firing rates of single units, the extent of synchronous spiking and power spectral density (PSD) changes in LFPs during and post-stimulation. Results Our results show that post-stimulation, the firing rates of a majority of M1 neurons changed significantly with respect to their baseline rates. These firing rate changes were diverse in character, as the firing rate of some neurons increased while others decreased. Additionally, these changes started to set in during stimulation. Furthermore, cross-correlation analysis showed a significant increase in coincident firing amongst neuronal pairs. Interestingly, this increase in synchrony was unrelated to the direction of firing rate change. We also found that neuronal ensembles derived through principal component analysis were more active post-stimulation. Lastly, these changes occurred without a significant change in the overall spectral power of LFPs post-stimulation. Conclusions Our results show that cerebellar stimulation caused significant, long-lasting changes in the activity patterns of M1 neurons by altering firing rates, boosting neural synchrony and increasing neuronal assemblies’ activation strength. Our study provides evidence that cerebellar stimulation can directly modulate cortical dynamics. Since these results are present in the perilesional cortex, our data might also help explain the facilitatory effects of cerebellar stimulation post-stroke.

The motor cortex controls skilled arm movement by recruiting a variety of targets in the nervous system, and it is important to understand the emergent activity in these regions as refinement of a motor skill occurs. One fundamental projection of the motor cortex is to the cerebellum. However, the emergent activity in the motor cortex and the cerebellum that appears as a dexterous motor skill is consolidated is incompletely understood. Here, we report on low-frequency oscillatory (LFO) activity that emerges in cortico-cerebellar networks with learning the reach-to-grasp motor skill. We chronically recorded the motor and the cerebellar cortices in rats which revealed the emergence of coordinated movement-related activity in the local-field potentials (LFPs) as the reaching skill consolidated. We found that the local and cross-area spiking activity was coordinated with LFOs. Finally, we also found that these neural dynamics were more prominently expressed during accurate behavior. This work furthers our understanding on emergent dynamics in the cortico-cerebellar loop that underlie learning and execution of precise skilled movement.

Temporal coordination among neurons and development of functional neuronal assemblies is central to nervous system function and purposeful behavior. Still, there is a paucity of evidence about how functional coordination emerges in neuronal assemblies in cortical and subcortical regions that are directly related to the control of functional output. We investigated emergent neural dynamics between primary motor cortex (M1) and the contralateral cerebellar cortex as rats learned a neuroprosthetic/ brain-machine interface (BMI) task. BMIs offer a powerful tool to causally test how distributed neural networks achieve specific neural patterns. During neuroprosthetic learning, actuator movements are causally linked to primary motor cortex (M1) neurons, i.e., direct neurons, that project to the decoder and whose firing is required to successfully perform the task. However, it is unknown how such direct M1 activity interacts with cerebellar activity. We observed a striking 3-6 Hz coherence that emerged between these regions local-field potentials (LFPs) with neuroprosthetic learning which also modulated task-related spiking. We found a robust task-related indirect modulation in the cerebellum, and we found that it became synchronous with M1-direct activity with learning. We also performed optogenetic inhibition of cerebellar activity and found that this led to performance impairments in neuroprosthetic control. Together, these results demonstrate that coordinated neural dynamics emerge in cortico-cerebellar regions during neuroprosthetic learning which supports task-relevant activity in M1 direct neuronal populations, and further, that cerebellar influence is necessary for M1-driven rapid direct neural control.