Explore the intersection of mathematics and neuroscience in this 59-minute lecture by Ram Murty from Queens University, presented at the Fields Lab for Network Science. Delve into the application of Markov processes to understand brain network hubs, examining how these mathematical models can help explain neural connectivity and information flow in the brain. The talk illuminates how stochastic processes contribute to our understanding of critical brain structures and their functions within complex neural networks.
Overview
Syllabus
Markov Processes and Brain Network Hubs
Taught by
Fields Institute
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Introduction to Probability Theory and Stochastic Processes
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The Connected Brain: Network and Communication in Neuroscience
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Certainty Equivalent Control of Markov Processes with Average Reward Functional
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Optimal Stopping of Gauss-Markov Processes with Random Terminal Value
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Complex Systems and the Brain: From Networks to Dynamics and Function
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Wasserstein Convergence of Penalized Markov Processes
