Nature CommunicationsNeurosciencePeer-reviewed journal article
Hippocampal ripples predict motor learning during brief rest breaks in humans
Martin SjøgårdiD, Bryan BaxteriD, Dimitrios MylonasiD, Megan Thompson, Kristi Kwok, Bailey Driscoll, Anabella Tolosa, Wen ShiiD, Robert StickgoldiD, Mark G VangeliD, Catherine J. ChuiD, Dara S. ManoachiD
Abstract
Critical aspects of motor learning and memory happen offline, during both wake and sleep. When healthy young people learn a motor sequence task, most of their performance improvement happens not while typing, but offline, during interleaved rest breaks. In contrast, the performance of patients with dense amnesia due to hippocampal damage actually gets worse over the rest breaks and improves while typing. These findings indicate that an intact hippocampus is necessary for offline motor learning during wake, but do not specify its mechanism. Here, we studied epilepsy patients (n=17) undergoing direct intracranial EEG monitoring of the hippocampus as they learned the same motor sequence task. Like healthy young people, they showed greater speed gains across rest breaks than while typing. They also showed higher hippocampal ripple rates during these rest breaks that predicted offline gains in speed. This suggests that motor learning during brief rest breaks during wake is mediated by hippocampal ripples. These results expand our understanding of the role of hippocampal ripples beyond declarative memory to include enhancing motor procedural memory. Significance StatementIn patients with epilepsy undergoing direct intracranial EEG monitoring of the hippocampus, we found a higher rate of ripples during the brief rest breaks of a motor sequence task than during task execution. These offline hippocampal ripples predicted the amount of performance improvement over the break. We conclude that the hippocampus contributes to motor learning during brief rest breaks, and propose that this offline learning is mediated by ripples.
- Citations
- 19
- FWCI
- 9.64
- Field percentile
- top 1%
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