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Dynamic Neuroscience = Statistics, Modeling, and Control /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Dynamic Neuroscience/ edited by Zhe Chen, Sridevi V. Sarma.
其他題名:	Statistics, Modeling, and Control /
其他作者:	Chen, Zhe.
面頁冊數:	XXI, 327 p. 80 illus., 62 illus. in color.online resource. :
Contained By:	Springer Nature eBook
標題:	Biomedical engineering. -
電子資源:	https://doi.org/10.1007/978-3-319-71976-4
ISBN:	9783319719764

Dynamic Neuroscience = Statistics, Modeling, and Control /
Dynamic NeuroscienceStatistics, Modeling, and Control /[electronic resource] :edited by Zhe Chen, Sridevi V. Sarma. - 1st ed. 2018. - XXI, 327 p. 80 illus., 62 illus. in color.online resource.

Introduction -- Part I Statistics & Signal Processing -- Characterizing Complex, Multi-scale Neural Phenomena Using State-Space Models -- Latent Variable Modeling of Neural Population Dynamics -- What Can Trial-to-Trial Variability Tell Us? A Distribution-Based Approach to Spike Train Decoding in the Rat Hippocampus and Entorhinal Cortex -- Sparsity Meets Dynamics: Robust Solutions to Neuronal Identification and Inverse Problems -- Artifact Rejection for Concurrent TMS-EEG Data -- Part II Modeling & Control Theory -- Characterizing Complex Human Behaviors and Neural Responses Using Dynamic Models -- Brain-Machine Interfaces -- Control-theoretic Approaches for Modeling, Analyzing and Manipulating Neuronal (In)activity -- From Physiological Signals to Pulsatile Dynamics: A Sparse System Identification Approach -- Neural Engine Hypothesis -- Inferring Neuronal Network Mechanisms Underlying Anesthesia induced Oscillations Using Mathematical Models -- Epilogue.

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.

ISBN: 9783319719764

Standard No.: 10.1007/978-3-319-71976-4doiSubjects--Topical Terms:

588770
Biomedical engineering.

LC Class. No.: R856-857

Dewey Class. No.: 610.28

Dynamic Neuroscience = Statistics, Modeling, and Control /
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