000			01377 a2200205 4500
005			20190930153719.0
008			190927b xxu||||| |||| 00| 0 eng d
020			_a9781107184862
040			_cIIT Kanpur
041			_aeng
082			_a612.82 _bC472b
100			_aChung, Moo K.
245			_aBrain network analysis _cMoo K. Chung
260			_bCambridge University Press _c2019 _aCambridge
300			_axii, 329p
520			_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.
650			_aBrain-physiology
650			_aNerve net-physiology
942			_cBK
999			_c560779 _d560779