LEADER 05305nam 22007215 450 001 9910299577403321 005 20251116194833.0 010 $a3-319-71976-9 024 7 $a10.1007/978-3-319-71976-4 035 $a(CKB)4100000001381508 035 $a(DE-He213)978-3-319-71976-4 035 $a(MiAaPQ)EBC5210893 035 $a(PPN)222230835 035 $a(EXLCZ)994100000001381508 100 $a20171228d2018 u| 0 101 0 $aeng 135 $aurnn#008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aDynamic Neuroscience $eStatistics, Modeling, and Control /$fedited by Zhe Chen, Sridevi V. Sarma 205 $a1st ed. 2018. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2018. 215 $a1 online resource (XXI, 328 p. 80 illus., 71 illus. in color.) 311 08$a3-319-71975-0 320 $aIncludes bibliographical references and index. 327 $aIntroduction -- 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. 330 $aThis 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. 606 $aBiomedical engineering 606 $aSignal processing 606 $aImage processing 606 $aSpeech processing systems 606 $aBioinformatics 606 $aNeurosciences 606 $aStatistics 606 $aNeural networks (Computer science) 606 $aBiomedical Engineering and Bioengineering$3https://scigraph.springernature.com/ontologies/product-market-codes/T2700X 606 $aSignal, Image and Speech Processing$3https://scigraph.springernature.com/ontologies/product-market-codes/T24051 606 $aComputational Biology/Bioinformatics$3https://scigraph.springernature.com/ontologies/product-market-codes/I23050 606 $aNeurosciences$3https://scigraph.springernature.com/ontologies/product-market-codes/B18006 606 $aStatistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences$3https://scigraph.springernature.com/ontologies/product-market-codes/S17020 606 $aMathematical Models of Cognitive Processes and Neural Networks$3https://scigraph.springernature.com/ontologies/product-market-codes/M13100 615 0$aBiomedical engineering. 615 0$aSignal processing. 615 0$aImage processing. 615 0$aSpeech processing systems. 615 0$aBioinformatics. 615 0$aNeurosciences. 615 0$aStatistics. 615 0$aNeural networks (Computer science) 615 14$aBiomedical Engineering and Bioengineering. 615 24$aSignal, Image and Speech Processing. 615 24$aComputational Biology/Bioinformatics. 615 24$aNeurosciences. 615 24$aStatistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences. 615 24$aMathematical Models of Cognitive Processes and Neural Networks. 676 $a610.28 702 $aChen$b Zhe$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aSarma$b Sridevi V$4edt$4http://id.loc.gov/vocabulary/relators/edt 906 $aBOOK 912 $a9910299577403321 996 $aDynamic Neuroscience$92538873 997 $aUNINA