Observed brain dynamics / / Partha P. Mitra, Hemant Bokil

• Record Nr.: UNINA9910953886203321
• Autore: Mitra Partha
• Pubbl/distr/stampa: Oxford ; ; New York, : Oxford University Press, c2008
• ISBN: 0-19-988436-6; 0-19-803963-8; 9786611374624; 1-281-37462-8; 1-4356-3359-8
• Edizione: [1st ed.]
• Descrizione fisica: 1 online resource (xxii, 381 pages) : illustrations
• Disciplina: 612.8/2
• Soggetti: Neural conduction - Mathematical models; Brain - Mathematical models; Brain - Physiology; Neural networks (Neurobiology); Electroencephalography; Neural Conduction - physiology; Models, Theoretical; Brain - physiology
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Note generali: Description based upon print version of record.
• Nota di bibliografia: Includes bibliographical references (p. 349-361) and index.
• Nota di contenuto: Contents; 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; Elementary 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; 7.7 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; 10.3 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; 14.3 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
• Sommario/riassunto: The 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