Coupling between motor cortex and striatum increases during sleep over long-term skill learning.

Stefan M Lemke,Dhakshin S Ramanathan,David Darevksy,Karunesh Ganguly,Daniel Egert,Joshua D Berke

doi:10.7554/elife.64303

Stefan M Lemke, Dhakshin S Ramanathan + Show 4 more

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https://doi.org/10.7554/elife.64303

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Abstract

The strength of cortical connectivity to the striatum influences the balance between behavioral variability and stability. Learning to consistently produce a skilled action requires plasticity in corticostriatal connectivity associated with repeated training of the action. However, it remains unknown whether such corticostriatal plasticity occurs during training itself or 'offline' during time away from training, such as sleep. Here, we monitor the corticostriatal network throughout long-term skill learning in rats and find that non-rapid-eye-movement (NREM) sleep is a relevant period for corticostriatal plasticity. We first show that the offline activation of striatal NMDA receptors is required for skill learning. We then show that corticostriatal functional connectivity increases offline, coupled to emerging consistent skilled movements, and coupled cross-area neural dynamics. We then identify NREM sleep spindles as uniquely poised to mediate corticostriatal plasticity, through interactions with slow oscillations. Our results provide evidence that sleep shapes cross-area coupling required for skill learning.

Highlights

IntroductionCortical and basal ganglia circuits regulate behavioral variability, as evidenced in habit development (Gremel et al, 2016; O’Hare et al, 2016; Rueda-Orozco and Robbe, 2015; Malvaez and Wassum, 2018; Lipton et al, 2019; Yin and Knowlton, 2006), skill learning (Santos et al, 2015; Kupferschmidt et al, 2017; Koralek et al, 2012; Yin et al, 2009), as well as the pathophysiology of neuropsychiatric disorders such as obsessive-compulsive disorder and autism spectrum disorder (Vicente et al, 2020; Shepherd, 2013)
During pre- and post-training periods, behavioral states—wake and sleep (NREM and REM) —were classified using standard methods based on cortical local field potential (LFP) power and movement measured from video or electromyography (EMG) activity (Watson et al, 2016)
We quantified day-to-day changes in the velocity profile, as this captured the combination of individual movements into a consistent skilled action and was less constrained by the task than the spatial reaching trajectory

Summary

Introduction

Cortical and basal ganglia circuits regulate behavioral variability, as evidenced in habit development (Gremel et al, 2016; O’Hare et al, 2016; Rueda-Orozco and Robbe, 2015; Malvaez and Wassum, 2018; Lipton et al, 2019; Yin and Knowlton, 2006), skill learning (Santos et al, 2015; Kupferschmidt et al, 2017; Koralek et al, 2012; Yin et al, 2009), as well as the pathophysiology of neuropsychiatric disorders such as obsessive-compulsive disorder and autism spectrum disorder (Vicente et al, 2020; Shepherd, 2013). Skill learning has been associated with striatal NMDA receptor activation (Santos et al, 2015; Koralek et al, 2012; Jin and Costa, 2010; Dang et al, 2006), suggesting that the activitydependent potentiation of cortical inputs to the striatum may be required (Calabresi et al, 1992; Charpier and Deniau, 1997). Little is known about the specific activity patterns that may drive corticostriatal plasticity, or when they occur, during skill learning. One intriguing possibility is that neural activity patterns during ‘offline’ periods, or time away from training such as sleep, play a central role in driving corticostriatal plasticity during skill learning

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