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      Sleep-Dependent Reactivation of Ensembles in Motor Cortex Promotes Skill Consolidation

      1 , 2 , 3 , 1 , 4 , 1 , 4 , *

      PLoS Biology

      Public Library of Science

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          Despite many prior studies demonstrating offline behavioral gains in motor skills after sleep, the underlying neural mechanisms remain poorly understood. To investigate the neurophysiological basis for offline gains, we performed single-unit recordings in motor cortex as rats learned a skilled upper-limb task. We found that sleep improved movement speed with preservation of accuracy. These offline improvements were linked to both replay of task-related ensembles during non-rapid eye movement (NREM) sleep and temporal shifts that more tightly bound motor cortical ensembles to movements; such offline gains and temporal shifts were not evident with sleep restriction. Interestingly, replay was linked to the coincidence of slow-wave events and bursts of spindle activity. Neurons that experienced the most consistent replay also underwent the most significant temporal shift and binding to the motor task. Significantly, replay and the associated performance gains after sleep only occurred when animals first learned the skill; continued practice during later stages of learning (i.e., after motor kinematics had stabilized) did not show evidence of replay. Our results highlight how replay of synchronous neural activity during sleep mediates large-scale neural plasticity and stabilizes kinematics during early motor learning.


          During non-REM sleep in rats, consolidation and offline improvements of a recently learned motor skill are linked to synchronous reactivation of task-related neural ensembles.

          Author Summary

          Sleep has been shown to help in consolidating learned motor tasks. In other words, sleep can induce “offline” gains in a new motor skill even in the absence of further training. However, how sleep induces this change has not been clearly identified. One hypothesis is that consolidation of memories during sleep occurs by “reactivation” of neurons engaged during learning. In this study, we tested this hypothesis by recording populations of neurons in the motor cortex of rats while they learned a new motor skill and during sleep both before and after the training session. We found that subsets of task-relevant neurons formed highly synchronized ensembles during learning. Interestingly, these same neural ensembles were reactivated during subsequent sleep blocks, and the degree of reactivation was correlated with several metrics of motor memory consolidation. Specifically, after sleep, the speed at which animals performed the task while maintaining accuracy was increased, and the activity of the neuronal assembles were more tightly bound to motor action. Further analyses showed that reactivation events occurred episodically and in conjunction with spindle-oscillations—common bursts of brain activity seen during sleep. This observation is consistent with previous findings in humans that spindle-oscillations correlate with consolidation of learned tasks. Our study thus provides insight into the neuronal network mechanism supporting consolidation of motor memory during sleep and may lead to novel interventions that can enhance skill learning in both healthy and injured nervous systems.

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          Most cited references 61

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          Learning-induced LTP in neocortex.

          The hypothesis that learning occurs through long-term potentiation (LTP)- and long-term depression (LTD)-like mechanisms is widely held but unproven. This hypothesis makes three assumptions: Synapses are modifiable, they modify with learning, and they strengthen through an LTP-like mechanism. We previously established the ability for synaptic modification and a synaptic strengthening with motor skill learning in horizontal connections of the rat motor cortex (MI). Here we investigated whether learning strengthened these connections through LTP. We demonstrated that synapses in the trained MI were near the ceiling of their modification range, compared with the untrained MI, but the range of synaptic modification was not affected by learning. In the trained MI, LTP was markedly reduced and LTD was enhanced. These results are consistent with the use of LTP to strengthen synapses during learning.
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            Replay of neuronal firing sequences in rat hippocampus during sleep following spatial experience.

            The correlated activity of rat hippocampal pyramidal cells during sleep reflects the activity of those cells during earlier spatial exploration. Now the patterns of activity during sleep have also been found to reflect the order in which the cells fired during spatial exploration. This relation was reliably stronger for sleep after the behavioral session than before it; thus, the activity during sleep reflects changes produced by experience. This memory for temporal order of neuronal firing could be produced by an interaction between the temporal integration properties of long-term potentiation and the phase shifting of spike activity with respect to the hippocampal theta rhythm.
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              Replay of rule-learning related neural patterns in the prefrontal cortex during sleep.

              Slow-wave sleep (SWS) is important for memory consolidation. During sleep, neural patterns reflecting previously acquired information are replayed. One possible reason for this is that such replay exchanges information between hippocampus and neocortex, supporting consolidation. We recorded neuron ensembles in the rat medial prefrontal cortex (mPFC) to study memory trace reactivation during SWS following learning and execution of cross-modal strategy shifts. In general, reactivation of learning-related patterns occurred in distinct, highly synchronized transient bouts, mostly simultaneous with hippocampal sharp wave/ripple complexes (SPWRs), when hippocampal ensemble reactivation and cortico-hippocampal interaction is enhanced. During sleep following learning of a new rule, mPFC neural patterns that appeared during response selection replayed prominently, coincident with hippocampal SPWRs. This was learning dependent, as the patterns appeared only after rule acquisition. Therefore, learning, or the resulting reliable reward, influenced which patterns were most strongly encoded and successively reactivated in the hippocampal/prefrontal network.

                Author and article information

                Role: Academic Editor
                PLoS Biol
                PLoS Biol
                PLoS Biology
                Public Library of Science (San Francisco, CA USA )
                18 September 2015
                September 2015
                : 13
                : 9
                [1 ]Neurology and Rehabilitation Service, San Francisco VA Medical Center, San Francisco, California, United States of America
                [2 ]Psychiatry Service, San Francisco VA Medical Center, San Francisco, California, United States of America
                [3 ]Department of Psychiatry, University of California, San Francisco, San Francisco, California, United States of America
                [4 ]Department of Neurology, University of California, San Francisco, San Francisco, California, United States of America
                University of Minnesota, UNITED STATES
                Author notes

                The authors have declared that no competing interests exist.

                Conceived and designed the experiments: DSR KG. Performed the experiments: DSR. Analyzed the data: DSR. Contributed reagents/materials/analysis tools: TG KG. Wrote the paper: DSR KG.


                This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication

                Page count
                Figures: 7, Tables: 0, Pages: 25
                This work was supported by fellowship awards from the Department of Veterans Affairs, Veterans Health Administration ( to DSR and from the American Heart Association ( to TG. This work was also supported by awards to KG from the Department of Veterans Affairs, Veterans Health Administration (, CDA B6674W); from the Northern California Institute for Research and Education (NCIRE, and start-up funds from the UCSF Department of Neurology ( KG also holds a Career Award for Medical Scientists from the Burroughs Wellcome Fund ( The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
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