LEADER 05326nam 2200721 a 450 001 9910792250403321 005 20230721015413.0 010 $a0-19-988436-6 010 $a0-19-803963-8 010 $a9786611374624 010 $a1-281-37462-8 010 $a1-4356-3359-8 035 $a(CKB)2560000000296707 035 $a(EBL)415601 035 $a(OCoLC)476243589 035 $a(SSID)ssj0000088548 035 $a(PQKBManifestationID)11130632 035 $a(PQKBTitleCode)TC0000088548 035 $a(PQKBWorkID)10082426 035 $a(PQKB)11049341 035 $a(StDuBDS)EDZ0000073240 035 $a(MiAaPQ)EBC415601 035 $a(Au-PeEL)EBL415601 035 $a(CaPaEBR)ebr10215750 035 $a(CaONFJC)MIL137462 035 $a(EXLCZ)992560000000296707 100 $a20070507d2008 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aObserved brain dynamics$b[electronic resource] /$fPartha P. Mitra, Hemant Bokil 210 $aOxford ;$aNew York $cOxford University Press$dc2008 215 $a1 online resource (404 p.) 300 $aDescription based upon print version of record. 311 $a0-19-517808-4 311 $a0-19-986482-9 320 $aIncludes bibliographical references (p. 349-361) and index. 327 $aContents; PART I: Conceptual Background; 1 Why Study Brain Dynamics?; 1.1 Why Dynamics? An Active Perspective; 1.2 Quantifying Dynamics: Shared Theoretical Instruments; 1.3 ''Newtonian and Bergsonian Time''; 2 Theoretical Accounts of the Nervous System; 2.1 Three Axes in the Space of Theories; 3 Engineering Theories and Nervous System Function; 3.1 What Do Brains Do?; 3.2 Engineering Theories; 4 Methodological Considerations; 4.1 Conceptual Clarity and Valid Reasoning; 4.2 Nature of Scientific Method; PART II: Tutorials; 5 Mathematical Preliminaries; 5.1 Scalars: Real and Complex Variables 327 $aElementary Functions5.2 Vectors and Matrices: Linear Algebra; 5.3 Fourier Analysis; 5.4 Time Frequency Analysis; 5.5 Probability Theory; 5.6 Stochastic Processes; 6 Statistical Protocols; 6.1 Data Analysis Goals; 6.2 An Example of a Protocol: Method of Least Squares; 6.3 Classical and Modern Approaches; 6.4 Classical Approaches: Estimation and Inference; 7 Time Series Analysis; 7.1 Method of Moments; 7.2 Evoked Potentials and Peristimulus Time Histogram; 7.3 Univariate Spectral Analysis; 7.4 Bivariate Spectral Analysis; 7.5 Multivariate Spectral Analysis; 7.6 Prediction 327 $a7.7 Point Process Spectral Estimation7.8 Higher Order Correlations; PART III: Applications; 8 Electrophysiology: Microelectrode Recordings; 8.1 Introduction; 8.2 Experimental Approaches; 8.3 Biophysics of Neurons; 8.4 Measurement Techniques; 8.5 Analysis Protocol; 8.6 Parametric Methods; 8.7 Predicting Behavior From Neural Activity; 9 Spike Sorting; 9.1 Introduction; 9.2 General Framework; 9.3 Data Acquisition; 9.4 Spike Detection; 9.5 Clustering; 9.6 Quality Metrics; 10 Electro- and Magnetoencephalography; 10.1 Introduction; 10.2 Analysis of Electroencephalographic Signals: Early Work 327 $a10.3 Physics of Encephalographic Signals10.4 Measurement Techniques; 10.5 Analysis; 11 PET and fMRI; 11.1 Introduction; 11.2 Biophysics of PET and fMRI; 11.3 Experimental Overview; 11.4 Analysis; 12 Optical Imaging; 12.1 Introduction; 12.2 Biophysical Considerations; 12.3 Analysis; PART IV: Special Topics; 13 Local Regression and Likelihood; 13.1 Local Regression; 13.2 Local Likelihood; 13.3 Density Estimation; 13.4 Model Assessment and Selection; 14 Entropy and Mutual Information; 14.1 Entropy and Mutual Information for Discrete Random Variables; 14.2 Continuous Random Variables 327 $a14.3 Discrete-Valued Discrete-Time Stochastic Processes14.4 Continuous-Valued Discrete-Time Stochastic Processes; 14.5 Point Processes; 14.6 Estimation Methods; Appendix A: The Bandwagon; Appendix B: Two Famous Papers; Photograph Credits; Bibliography; Index; A; B; C; D; E; F; G; H; I; J; K; L; M; N; O; P; Q; R; S; T; U; V; W; Y 330 $aThe biomedical sciences have recently undergone revolutionary change, due to the ability to digitize and store large data sets. In neuroscience, the data sources include measurements of neural activity measured using electrode arrays, EEG and MEG, brain imaging data from PET, fMRI, and optical imaging methods. Analysis, visualization, and management of these time series data sets is a growing field of research that has become increasingly important both for experimentalists and theorists interested in brain function. Written by investigators who have played an important role in developing the 606 $aBrain$xMathematical models 606 $aBrain$xPhysiology 606 $aNeural networks (Neurobiology) 606 $aElectroencephalography 615 0$aBrain$xMathematical models. 615 0$aBrain$xPhysiology. 615 0$aNeural networks (Neurobiology) 615 0$aElectroencephalography. 676 $a612.8/2 700 $aMitra$b Partha$01535451 701 $aBokil$b Hemant$01535452 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910792250403321 996 $aObserved brain dynamics$93783695 997 $aUNINA