Neurodynamics : an exploration in mesoscopic brain dynamics /

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Bibliographic Details
Author / Creator:Freeman, Walter J.
Imprint:London ; New York : Springer, c2000.
Description:ix, 397 p. : ill. ; 24 cm.
Language:English
Series:Perspectives in neural computing
Subject:
Format: Print Book
URL for this record:http://pi.lib.uchicago.edu/1001/cat/bib/4653356
Hidden Bibliographic Details
ISBN:1852336161 (acid-free paper)
Notes:Includes bibliographical references and index.

MARC

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505 0 0 |g Pt. I.  |t The dynamics of neural interaction and transmission --  |g 1.  |t Spatial mapping of evoked brain potentials and EEGs to define population state variables --  |g 2.  |t Linear models of impulse inputs and linear basis functions for measuring impulse responses --  |g 3.  |t Rational approximations in the complex plane for Laplace transforms of transcendental linear operators --  |g 4.  |t Root locus analysis of piecewise linearized models with multiple feedback loops and unilateral or bilateral saturation --  |g 5.  |t Opening feedback loops with surgery and anesthesia; closing them with noise --  |g 6.  |t Three degrees of freedom in neural populations: Arousal, learning, and bistability --  |g 7.  |t Analog computation to model responses based on linear integration, modifiable synapses, and nonlinear trigger zones --  |g 8.  |t Stability analysis to derive and regulate homeostatic set points for negative feedback loops --  |g Pt. II.  |t Designation of contents as meaning, not information --  |g 9.  |t Multichannel recording to reveal the "code" of the cortex: spatial patterns of amplitude modulation (AM) of mesoscopic carrier waves --  |g 10.  |t Relations between microscopic and mesoscopic levels shown by calculating pulse probability conditional of EEG amplitude, giving the asymmetric sigmoid function --  |g 11.  |t Euclidean distance in 64-space and the use of behavioral correlates to optimize filters for gamma AM pattern classification --  |g 12.  |t Simulating gamma waveforms, AM patterns and 1/f[superscript [alpha]] spectra by means of mesoscopic chaotic neurodynamics --  |g 13.  |t Tuning curves to optimize temporal segmentation and parameter evaluation of adaptive filters for neocortical EEG --  |g 14.  |t Stochastic differential equations and random number generators minimize numerical instabilities in digital simulations.  |t Epilogue: Problems for further development in mesoscopic brain dynamics. 
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