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או
There has been a heated debate about whether chaos theory can be applied to the dynamics of the human brain. While it is obvious that nonlinear mechanisms are crucial in neural systems, there has been strong criticism of attempts to identify at strange attractors in brain signals and to measure their fractal dimensions, Lyapunov exponents, etc. Conventional methods analyzing brain dynamics are largely based on linear models and on Fourier spectra. Regardless of the existence of strange attractors in brain activity, the neurosciences should benefit greatly from alternative methods that have bee
| כותר |
Workshop on Chaos in Brain? [electronic resource] : NIC, Forschungszentrum Julich and Dept. of Epileptology, University of Bonn, Germany, March 10-12, 1999 / edited by K. Lehnertz ... [et al.]. |
|---|---|
| מוציא לאור |
Singapore River Edge, N.J. : World Scientific |
| שנה |
c2000 |
| הערות |
"The workshop was organized by the John von Neumann Institute for Computing (NIC) at the Forschungszentrum Julich and the Department of Epileptology of the Bonn University Medical Center"--Preface. Includes bibliographical references. English |
| הערת תוכן ותקציר |
PREFACE CONTENTS LECTURES Cortical dynamics - experiments and models Is nonlinearity evident in time series of brain electrical activity? Finding and characterizing unstable fixed points by controlling system dynamics Detection of phase locking from noisy data: application to magnetoencephalography Dynamical analysis in clinical practice Rhythms of the brain: between randomness and determinism Pre-ictal changes of the EEG dynamics in epileptic patients: clinical and neurobiological implications Spatio-temporal dynamics of epileptogenic networks Pre-ictal changes and EEG analyses within the framework of Lyapunov theoryEpilepsy - when chaos fails Possible clinical and research applications of nonlinear EEG analysis in humans Dynamics of EEG signals during petit-mal epileptic seizures Detection of epileptic dynamics in neuromagnetic signals: spectral analyses versus characteristics of correlation function Nonlinear methods for evoked potential analysis and modeling From slow potentials to chaos: processing in the brain and controlling the brain POSTERS Detection of deterministic dynamics in short discrete time series Characterization of linear and nonlinear structure in high-dimensional spatially extended systems: the algorithm of multichannel nonlinear cross predictionSurrogate data for non-stationary signals Analysis of fluctuating data sets of diffusion processes Complications in applying the method of surrogate data to EEG Spontaneous synchronisation in a discrete neural network model Patterns of complexity and coherent oscillations in a thalamo-cortical network model Non-linear coupling of local field potentials across cortical sites in parvalbumin-deficient mice Analytical proof of chaos in single neurons and consequencesEEG-detected episodes of low-dimensional self-organized cortical activity and the problem of chaos in the brain Correlation dimension as a method to investigate human REM-sleep The application of a non-linear analysis technique to the monitoring of anesthetic effects in the rat Detection of determinism in EEG time series from human sleep by an interspike interval approach Detecting spatio-temporal information flow in the cortex by mutual information analysis of MEG data Evidence of inverse covariation between alpha power and correlation dimension in human brain dynamicsCorrelation sums from EEG time series: a measure to quantify depth of anesthesia Detection of phase synchronization in human MEG data MEG-recordings of syllables perception: perturbations from a stable state in the auditory cortex Measuring changes in cognitive event related potentials Fast subdural signals in humans show task- and event-related changes of conventional and novel coupling measures during cognitive processes Brain activity detected by complexity measurements: a methodological approach |
| היקף החומר |
1 online resource (382 p.) |
| שפה |
אנגלית |
| מספר מערכת |
997010711429105171 |
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