Ensemble reactivations during brief rest drive fast learning of sequences

Sandon Griffin; Preeya Khanna; Hoseok Choi; Katherina Thiesen; Lisa Novik; Robert J Morecraft; Karunesh Ganguly

doi:10.1038/s41586-024-08414-9

Ensemble reactivations during brief rest drive fast learning of sequences

Nature. 2025 Jan 15. doi: 10.1038/s41586-024-08414-9. Online ahead of print.

Authors

Sandon Griffin^{1

2

3

4}, Preeya Khanna^{3

4}, Hoseok Choi^{3

4}, Katherina Thiesen⁴, Lisa Novik⁴, Robert J Morecraft⁵, Karunesh Ganguly^{6

7}

Affiliations

¹ Neuroscience Graduate Program, University of California, San Francisco, San Francisco, CA, USA.
² Medical Scientist Training Program, University of California, San Francisco, San Francisco, CA, USA.
³ Department of Neurology, University of California, San Francisco, San Francisco, CA, USA.
⁴ California National Primate Research Center, University of California, Davis, Davis, CA, USA.
⁵ Laboratory of Neurological Sciences, Division of Basic Biomedical Sciences, Sanford School of Medicine, The University of South Dakota, Vermillion, SD, USA.
⁶ Department of Neurology, University of California, San Francisco, San Francisco, CA, USA. [email protected].
⁷ California National Primate Research Center, University of California, Davis, Davis, CA, USA. [email protected].

PMID: 39814880
DOI: 10.1038/s41586-024-08414-9

Abstract

During motor learning, breaks in practice are known to facilitate behavioural optimizations. Although this process has traditionally been studied over long breaks that last hours to days^1-6, recent studies in humans have demonstrated that rapid performance gains during early motor sequence learning are most pronounced after very brief breaks lasting seconds to minutes^7-10. However, the precise causal neural mechanisms that facilitate performance gains after brief breaks remain poorly understood. Here we recorded neural ensemble activity in the motor cortex of macaques while they performed a visuomotor sequence learning task interspersed with brief breaks. We found that task-related neural cofiring patterns were reactivated during brief breaks. The rate and content of reactivations predicted the magnitude and pattern of subsequent performance gains. Of note, we found that performance gains and reactivations were positively correlated with cortical ripples (80-120 Hz oscillations) but anti-correlated with β bursts (13-30 Hz oscillations), which ultimately dominated breaks after the fast learning phase plateaued. We then applied 20 Hz epidural alternating current stimulation (ACS) to motor cortex, which reduced reactivation rates in a phase-specific and dose-dependent manner. Notably, 20 Hz ACS also eliminated performance gains. Overall, our results indicate that the reactivations of task ensembles during brief breaks are causal drivers of subsequent performance gains. β bursts compete with this process, possibly to support stable performance.