This tutorial reference serves as a coherent overview of various
statistical and mathematical approaches used in brain network
analysis, where modeling the complex structures and functions of
the human brain often poses many unique computational and
statistical challenges. This book fills a gap as a textbook for
graduate students while simultaneously articulating important and
technically challenging topics. Whereas most available books are
graph theory-centric, this text introduces techniques arising from
graph theory and expands to include other different models in its
discussion on network science, regression, and algebraic topology.
Links are included to the sample data and codes used in generating
the book's results and figures, helping to empower methodological
understanding in a manner immediately usable to both researchers
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