Computational Neurobiology Data-Driven Computational Neuroscience Machine Learning and Statistical Models
Concha Bielza Universidad Politécnica de Madrid
and Pedro Larrañaga Universidad Politécnica de Madrid
Data-driven computational neuroscience facilitates the transformation of data into insights into the structure and functions of the brain. This modern treatment of real world cases offers neuroscience researchers and graduate students a comprehensive, in-depth guide to statistical and machine learning methods. Contents: 2020 253 x 177 mm c.700pp 210 b/w illus. 40 colour illus. 978-1-108-49370-3 Hardback £69.99 / US$89.99 Publication August 2020 For all formats available, see
www.cambridge.org/9781108493703
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Brain Network Analysis Moo K. Chung University of Wisconsin, Madison
This tutorial reference provides a coherent overview of statistical and mathematical approaches used in brain network analysis. It goes beyond graph theory to explore different models in network science, regression, and algebraic topology, empowering methodological understanding in a manner immediately usable to both researchers and students. ‘This book is a must-read for students and researchers in brain network analysis. It is unique across many fronts. First, it weaves together the important background material in statistics, computational mathematics and algebraic topology. Second, it accomplishes the dual role of a research monograph and a textbook reference. The author, an expert in this field, conveys his enthusiasm for brain network analysis and lays down the most essential mathematical and statistical foundations for future advances.’ Hernando Ombao, King Abdullah University of Science and Technology, Saudi Arabia 2019 228 x 152 mm 338pp 41 colour illus. 978-1-107-18486-2 Hardback £59.99 / US$79.99 For all formats available, see
www.cambridge.org/9781107184862
eBooks available at www.cambridge.org/ebookstore