UCSF

Circadian rhythms have been observed across all three kingdoms of life: from the simplest of cyanobacteria to complex vertebrates, such as rodents and humans. Despite the necessity and ubiquity of sleep, surprisingly little is known about the spatio-temporal organization of electrical activity in the sleeping brain. Several decades of research in humans and other animals has suggested that non-rapid eye movement (NREM) sleep has as its hallmark biomarker two distinct classes of electrical waves: low frequency, high amplitude Slow Oscillations (SOs) and higher frequency, lower amplitude waxing-and-waning oscillations known as sleep spindles. Despite extensive work demonstrating the correlational and causational role that the interaction between SOs and spindles plays in strengthening of procedural memory, little mechanistic insight has been gleaned as to how SOs are 1) spatially coordinated across distant brain regions and 2) how spatial coordination of SOs changes the temporal dynamics of sleep spindles.

I thus begin this thesis by introducing the sleep neuroscience literature in its historical context, including work previously done showing the benefits of NREM sleep for skilled motor learning. I then provide an overview of findings demonstrating the importance of SOs and sleep spindles to memory consolidation while also introducing more recent work demonstrating the growing importance of 1) cross-area interactions in motor memory consolidation and 2) emerging evidence for temporal clustering in NREM sleep oscillations. I then present my work where we perform paired electrophysiological recordings in rat medial prefrontal cortex (PFC) and primary motor cortex (M1) as animals engage in the learning of a long-term skilled reach-to-grasp task. Using these recordings, I demonstrate that cross-area SO coupling exhibits an unexpected bimodal temporal pattern. Finally, I show that cross-area SO temporal coupling between PFC and M1 regulates the local nesting of M1 sleep spindles to M1 SOs and also modulates spiking rates of M1 neurons during M1 SOs. Together, my work provides evidence for “top down” regulation of SO-spindle nesting thus supporting the systems consolidation theory for memory and learning.