Dynamic neuroscience: Statistics, modeling, and control

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Abstract

This book shows how to develop efficient quantitative methods to characterize neural data and extra information that reveals underlying dynamics and neurophysiological mechanisms. Written by active experts in the field, it contains an exchange of innovative ideas among researchers at both computational and experimental ends, as well as those at the interface. Authors discuss research challenges and new directions in emerging areas with two goals in mind: to collect recent advances in statistics, signal processing, modeling, and control methods in neuroscience; and to welcome and foster innovative or cross-disciplinary ideas along this line of research and discuss important research issues in neural data analysis. Making use of both tutorial and review materials, this book is written for neural, electrical, and biomedical engineers; computational neuroscientists; statisticians; computer scientists; and clinical engineers.

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Chen, Z., & Sarma, S. V. (2017). Dynamic neuroscience: Statistics, modeling, and control. Dynamic Neuroscience: Statistics, Modeling, and Control (pp. 1–328). Springer International Publishing. https://doi.org/10.1007/978-3-319-71976-4

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