henhaobio
Sign in

bioRxivNeurosciencePreprint

Cortico-cerebellar beta-band dynamics predict flexible motor timing

Coen S. ZandvoortiD, C. WissingiD, Jonathan L. Winter, Anna KowalczykiD, Ole B. JenseniD, R. Chris MialliD, Devika NarainiD, Katja KornyshevaiD

PDFDOI
Citations
0

Abstract

Flexible motor control requires that movements adapt to changing temporal contexts. Here, we test whether flexible timing is driven by context-dependent encoding across cortico-cerebellar circuits and how neural dynamics within these circuits enable accurate performance. To overcome the signal-to-noise limitations of conventional electro- and magnetoencephalography, we recorded whole-head neural dynamics using optically pumped magnetometer arrays (OPM-MEG). Participants learned a context-dependent task, executing manual button presses at time intervals 800 ms (T1) and 1,600 ms (T2), respectively, to avoid a periocular air puff, which was associated with an implicit conditioned eyeblink. We found that the motor cortex contralateral to the hand and bilateral cerebellar lobule VI dynamically encoded these intervals through beta-band (13-30 Hz) event-related desynchronisation (ERD) that precisely scaled with T1 and T2. The cerebellar trial-by-trial latency of the beta-band ERD predicted the timing of explicit manual actions. Finally, partial directed coherence revealed that baseline bidirectional beta-band coupling across the network transiently weakened from the ipsilateral cerebellum to the contralateral motor cortex during finger movement execution. Our findings show that cortico-cerebellar coupling functions as a gating mechanism and suggest that cerebellar circuits modulate cortical motor activity for flexible, accurate motor timing.

Reproducibility ledger

Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.

Sign in to file a reproducibility report.

Similarity Map
SelectedSame fieldCross-field
THISRen '25West '25Wang '17Nashef '19Zich '18Schipper '26
79% semantic matchNeuroscience
Zhong Ren, Xiaolu Wang, Milen Angelov+2 more·Nature Communications·Jan 12, 2025· 7 citations