Dynamic Neuroscience Statistics, Modeling, and Control /

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 computatio...

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Bibliographic Details
Corporate Author: SpringerLink (Online service)
Other Authors: Chen, Zhe (Editor), Sarma, Sridevi V. (Editor)
Format: e-Book
Language:English
Published: Cham : Springer International Publishing : 2018.
Imprint: Springer,
Edition:1st ed. 2018.
Subjects:
Biomedical engineering.
Signal processing.
Bioinformatics.
Neurosciences.
Statistics .
Neural networks (Computer science) .
Biomedical Engineering and Bioengineering.
Signal, Speech and Image Processing .
Computational and Systems Biology.
Neuroscience.
Statistics in Engineering, Physics, Computer Science, Chemistry and Earth Sciences.
Mathematical Models of Cognitive Processes and Neural Networks.
Online Access:Full-text access
Description
Summary: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. Presents innovative methodological and algorithmic development in statistics, modeling, control, and signal processing for neural data analysis; Includes a coherent framework for a broad class of neural signal processing and control problems in neuroscience; Covers a wide range of representative case studies in neuroscience applications.
Physical Description:XXI, 327 p. 80 illus., 62 illus. in color. online resource.
ISBN:9783319719764
DOI:10.1007/978-3-319-71976-4

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