Neurodynamics: An Exploration in Mesoscopic Brain Dynamics

Prologue.- Prologue.- I The dynamics of neural interaction and transmission.- 1. Spatial mapping of evoked brain potentials and EEGs to 27 define population state variables.- 2. Linear models of impulse inputs and linear basis functions for measuring impulse responses.- 3. Rational approximations in the complex plane for Laplace transforms of transcendental linear operators.- 4. Root locus analysis of piecewise linearized models with multiple feedback loops and unilateral or bilateral saturation.- 5. Opening feedback loops with surgery and anesthesia; closing them with noise.- 6. Three degrees of freedom in neural populations: Arousal, learning, and bistability.- 7. Analog computation to model responses based on linear integration, modifiable synapses, and nonlinear trigger zones.- 8. Stability analysis to derive and regulate homeostatic set points for negative feedback loops.- II Designation of contents as meaning, not information.- 9. Multichannel recording to reveal the “code” of the cortex: spatial patterns of amplitude modulation (AM) of mesoscopic carrier waves.- 10. Relations between microscopic and mesoscopic levels shown by calculating pulse probability conditional on EEG amplitude, giving the asymmetric sigmoid function.- 11. Euclidean distance in 64-space and the use of behavioral correlates to optimize filters for gamma AM pattern classification.- 12. Simulating gamma waveforms, AM patterns and 1/f? spectra by means of mesoscopic chaotic neurodynamics.- 13. Tuning curves to optimize temporal segmentation and parameter evaluation of adaptive filters for neocortical EEG.- 14. Stochastic differential equations and random number generators minimize numerical instabilities in digital simulations.- Epilogue: Problems for further development in mesoscopic brain dynamics.- Epilogue: Problems for further development in mesoscopic brain dynamics.- References.- Author Index.