bioRxivNeurosciencePreprint
A Novel Cortico-Striatal NREM Sleep Rhythm in Mice and Non-Human Primates
Aviv D. Mizrahi-KligeriD, Samantha CouryiD, Cameron L. WoodardiD, Karunesh GangulyiD
Abstract
With practice, rapid early gains in performance are followed by a slower phase marked by kinematic refinement, automaticity and enhanced cortical and striatal interactions. While sleep is known to support early learning, its causal role in the slow phase of learning is not known. Here we recorded neuronal activity in primary motor cortex (M1) and the dorsolateral striatum (DLS) during long-term skill acquisition and interleaved sleep. Surprisingly, the slow phase of learning was marked by the emergence of a previously unrecognized 5-10 Hz oscillatory activity during NREM sleep that was coherent across M1 and DLS. This oscillation resulted in repeated joint reactivation of task-specific information in cortex and striatum. Strikingly, during later stages of training, such joint reactivation of task activity increased over the course of NREM sleep, suggesting that sleep-dependent processing strengthens cortico-striatal interactions. The strength of M1-DLS coherence was predictive of next-day performance gains and increased cortico-striatal coupling during task performance. Targeted closed-loop disruption of this oscillation during NREM sleep abolished performance gains, whereas switching to a dose matched random stimulation paradigm enabled performance improvements in the same animals. Importantly, the same cortico-striatal 5-10 Hz rhythm was also found in sleeping non-human primates, where it was selectively enhanced following learning. Together, we identify, across species, a novel NREM sleep oscillation that is important for sleep-dependent performance gains which depend on cortico-striatal processing.
- organism: mouse
- organism: non-human primate
- assay: electronic health records
- research focus: cell type annotation
- research focus: clustering
- research focus: differential expression
- research focus: gene regulatory network inference
- approach: experimental assay
- Citations
- 0
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