Dynamic Neuroscience
-15%
portes grátis
Dynamic Neuroscience
Statistics, Modeling, and Control
Chen, Zhe; Sarma, Sridevi V.
Springer International Publishing AG
03/2018
327
Dura
Inglês
9783319719757
15 a 20 dias
694
Descrição não disponível.
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.
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Neural signal processing;Neuronal coding theories;Neural engineering;Neural activity;State-space paradigm;Hippocampal replay;Oscillatory and multivariate data;Gaussian approximation;Applications to neuronal data;Dynamical system model of behavior;Neuronal population theories;Brain-machine interface systems;Enteric nervous system;High-resolution electrogastrogram;Theoretical neuroscience;Statistical neuroscience
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.
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
Neural signal processing;Neuronal coding theories;Neural engineering;Neural activity;State-space paradigm;Hippocampal replay;Oscillatory and multivariate data;Gaussian approximation;Applications to neuronal data;Dynamical system model of behavior;Neuronal population theories;Brain-machine interface systems;Enteric nervous system;High-resolution electrogastrogram;Theoretical neuroscience;Statistical neuroscience
