Targeted cortical reorganization using optogenetics in non-human primates.

Brain stimulation modulates the excitability of neural circuits and drives neuroplasticity. While the local effects of stimulation have been an active area of investigation, the effects on large-scale networks remain largely unexplored. We studied stimulation-induced changes in network dynamics in two macaques. A large-scale optogenetic interface enabled simultaneous stimulation of excitatory neurons and electrocorticographic recording across primary somatosensory (S1) and motor (M1) cortex (Yazdan-Shahmorad et al., 2016). We tracked two measures of network connectivity, the network response to focal stimulation and the baseline coherence between pairs of electrodes; these were strongly correlated before stimulation. Within minutes, stimulation in S1 or M1 significantly strengthened the gross functional connectivity between these areas. At a finer scale, stimulation led to heterogeneous connectivity changes across the network. These changes reflected the correlations introduced by stimulation-evoked activity, consistent with Hebbian plasticity models. This work extends Hebbian plasticity models to large-scale circuits, with significant implications for stimulation-based neurorehabilitation

An Exploration of Meso-scale Plasticity

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

Compartmentalized dynamics within a common multi-area mesoscale manifold represent a repertoire of human hand movements

The human hand is unique in the animal kingdom for unparalleled dexterity, ranging from complex prehension to fine finger individuation. How does the brain represent such a diverse repertoire of movements? We evaluated mesoscale neural dynamics across the human "grasp network," using electrocorticography and dimensionality reduction methods, for a repertoire of hand movements. Strikingly, we found that the grasp network represented both finger and grasping movements alike. Specifically, the manifold characterizing the multi-areal neural covariance structure was preserved during all movements across this distributed network. In contrast, latent neural dynamics within this manifold were surprisingly specific to movement type. Aligning latent activity to kinematics further uncovered distinct submanifolds despite similarities in synergistic coupling of joints between movements. We thus find that despite preserved neural covariance at the distributed network level, mesoscale dynamics are compartmentalized into movement-specific submanifolds; this mesoscale organization may allow flexible switching between a repertoire of hand movements

The Degree of Nesting between Spindles and Slow Oscillations Modulates Neural Synchrony

Spindles and slow oscillations (SOs) both appear to play an important role in memory consolidation. Spindle and SO "nesting," or the temporal overlap between the two events, is believed to modulate consolidation. However, the neurophysiological processes modified by nesting remain poorly understood. We thus recorded activity from the primary motor cortex of 4 male sleeping rats to investigate how SO and spindles interact to modulate the correlation structure of neural firing. During spindles, primary motor cortex neurons fired at a preferred phase, with neural pairs demonstrating greater neural synchrony, or correlated firing, during spindle peaks. We found a direct relationship between the temporal proximity between SO and spindles, and changes to the distribution of neural correlations; nesting was associated with narrowing of the distribution, with a reduction in low- and high-correlation pairs. Such narrowing may be consistent with greater exploration of neural states. Interestingly, after animals practiced a novel motor task, pairwise correlations increased during nested spindles, consistent with targeted strengthening of functional interactions. These findings may be key mechanisms through which spindle nesting supports memory consolidation.SIGNIFICANCE STATEMENT Our analysis revealed changes in cortical spiking structure that followed the waxing and waning of spindles; firing rates increased, spikes were more phase-locked to spindle-band local field potential, and synchrony across units peaked during spindles. Moreover, we showed that the degree of nesting between spindles and slow oscillations modified the correlation structure across units by narrowing the distribution of pairwise correlations. Finally, we demonstrated that engaging in a novel motor task increased pairwise correlations during nested spindles. These phenomena suggest key mechanisms through which the interaction of spindles and slow oscillations may support sensorimotor learning. More broadly, this work helps link large-scale measures of population activity to changes in spiking structure, a critical step in understanding neuroplasticity across multiple scales