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Title: “Analysis of network dynamics during behavior and neuromodulation with single neuron resolution”

Advisory Committee: Xue Han, PhD – BME (Advisor) Anna Devor, PhD – BME (Chair) Bobak Nazer, PhD – ECE Mark Howe, PhD – Psychological and Brain Sciences Mark Kramer, PhD – Mathematics and Statistics

Abstract: Dynamic interactions of neurons within a network orchestrate cognition, sensation, and motor actions. Over the years, brain networks have been explored using empirical techniques and computational tools of network science, and advanced network analysis approaches have been established for whole brain network analysis with brain-region level resolution. Recent progress in the development of high-performance neural activity indicators provides a unique opportunity to study the interactions between individual neurons during behavior, allowing for network analysis with single cell resolution. For example, it is now possible to image hundreds to thousands of neurons using genetically encoded calcium indicators, or tens of neurons using genetically encoded voltage indicators. This can enable integration of network information at single-cell level to brain-region level giving a more coherent understanding of the brain. However, these neural activity imaging techniques have distinct spatial and temporal resolution from that of the whole brain mapping techniques, and thus network analysis at single cell resolution requires a set of algorithms uniquely suited for the specific data acquisition modalities. In this study, I aim to develop an optimal network analysis approach for datasets collected via large scale calcium imaging and high-speed voltage imaging, with a goal of understanding network dynamics during behavior and neuromodulation. Specifically, I will examine changes in the hippocampal and striatal networks during natural behavior and upon clinically relevant neuromodulation. This study will provide important insights into neural network dynamics that can help design effective therapeutic strategies via targeted modulation of specific network features.