01528 2200217 450000500170000000800410001702000180005804000150007604100080009108200180009910000180011724500410013526000480017630000140022452008610023865000210109965000250112094200070114599900190115295201390117120190930153719.0190927b xxu||||| |||| 00| 0 eng d a9781107184862 cIIT Kanpur aeng a612.82bC472b aChung, Moo K. aBrain network analysiscMoo K. Chung bCambridge University Pressc2019aCambridge axii, 329p aThis 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 and students. aBrain-physiology aNerve net-physiology cBK c560779d560779 0010406612_820000000000000_C472B708GEN9900027aIITKbIITKd2019-10-09e2g4281.37o612.82 C472bpA184825r2019-09-26v5351.71yBK