UCSF

Specialized sensorimotor systems allow us to perform dexterous, graceful movements in complicated, dynamic environments. One remarkable feature of the sensorimotor system is its ability to learn new skills. The neural underpinnings of sensorimotor learning have traditionally been studied at two levels: low-level changes between individual neurons, and high-level changes in behavior. Directly connecting these distant levels of study is challenging. In this thesis, I try to bridge this gap by focusing on plasticity at an intermediate level that considers how neuron populations change with respect to each other, i.e., meso-scale plasticity.

In Chapter 2, I study changes in meso-scale connectivity in response to neurostimulation. A large-scale optogenetic interface enabled us to simultaneously stimulate and record population activity across primary somatosensory (S1) and primary motor (M1) cortex. We tracked two measures of network connectivity—one based on responses to focal stimulation and the other based on spontaneous activity patterns. Within minutes of stimulation, the inter-area functional connectivity strengthened. At a finer scale, stimulation led to heterogeneous changes across the network, which reflected the correlations introduced by stimulation-evoked activity, consistent with Hebbian models of synaptic plasticity. This work extends Hebbian plasticity models to meso-scale circuits.

In Chapter 3, I connect low-level changes in M1 spiking structure to two meso-scale oscillations—spindles and slow oscillations (SOs), which are thought to support sensorimotor learning and memory consolidation. During spindles, individual neurons fired at a preferred phase of spindle cycles and neuron pairs synchronized activity during spindle peaks, signifying an increase in pairwise correlations and local functional connectivity. We found a direct relationship between the temporal proximity of SO and spindles (which are thought to interact), and changes to the distribution of spike correlations; closer oscillations were associated with narrowing of the distribution of correlations, with a reduction in low- and high-correlation pairs. Such narrowing is consistent with exploration of novel neural states and may be a key mechanism through which the interaction of meso-scale oscillations can support sensorimotor consolidation.

Throughout this thesis I advocate for studying and modeling neuron populations. I provide insight into meso-scale plasticity through a direct study of meso-scale connectivity changes and by relating the meso-scale to coordinated spiking activity.