Dynamics of sleep spindles and coupling to slow oscillations following motor learning in adult mice

• Published in: Neurobiology of learning and memory Vol. 166; p. 107100
• Main Authors: Kam, Korey, Pettibone, Ward D., Shim, Kaitlyn, Chen, Rebecca K., Varga, Andrew W.
• Format: Journal Article
• Language: English
• Published: United States Elsevier Inc 01.12.2019
• Subjects: Coupling; Delta waves; Motor learning; Rotarod; Slow oscillation; Spindles; Delta waves; Slow oscillation; Coupling; Rotarod; Motor learning; Spindles
• ISSN: 1074-7427; 1095-9564
• DOI: 10.1016/j.nlm.2019.107100

Sleep spindles have been implicated in motor learning in human subjects, but their occurrence, timing in relation to cortical slow oscillations, and relationship to offline gains in motor learning have not been examined in animal models. In this study, we recorded EEG over bilateral primary motor cortex in conjunction with EMG for 24 h following a period of either baseline handling or following rotarod motor learning to monitor sleep. We measured several biophysical properties of sleep spindles and their temporal coupling with cortical slow oscillations (SO, <1 Hz) and cortical delta waves (1–4 Hz). Following motor learning, we found an increase in spindles during an early period of NREM sleep (1–4 h) without changes to biophysical properties such as spindle power, peak frequency and coherence. In this same period of early NREM sleep, both SO and delta power increased after motor learning. Notably, a vast majority of spindles were associated with minimal SO power, but in the subset that were associated with significant SO power (>1 z-score above the population mean), spindle-associated SO power was greater in spindles following motor learning compared to baseline sleep. Also, we did not observe a group-level preferred phase in spindle-SO or spindle-delta coupling. While SO power alone was not predictive of motor performance in early NREM sleep, both spindle density and the difference in the magnitude of the mean resultant vector length of the phase angle for SO-associated spindles, a measure of its coupling precision, were positively correlated with offline change in motor performance. These findings support a role for sleep spindles and their coupling to slow oscillations in motor learning and establish a model in which spindle timing and the brain circuits that support offline plasticity can be mechanistically explored.