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The Dynamic Brain: From Spiking Neurons to Neural Masses and Cortical Fields
TLDR
The cortex is a complex system, characterized by its dynamics and architecture, which underlie many functions such as action, perception, learning, language, and cognition. Expand
Dynamics of large-scale brain activity in normal arousal states and epileptic seizures.
Links between electroencephalograms (EEGs) and underlying aspects of neurophysiology and anatomy are poorly understood. Here a nonlinear continuum model of large-scale brain electrical activity isExpand
Comparing hemodynamic models with DCM
TLDR
We show that the best model is a non-linear model with a revised form for the coefficients, in which ε is treated as a free parameter. Expand
Propagation and stability of waves of electrical activity in the cerebral cortex
Nonlinear equations are introduced to model the behavior of the waves of cortical electrical activity that are responsible for signals observed in electroencephalography. These equations incorporateExpand
A unifying explanation of primary generalized seizures through nonlinear brain modeling and bifurcation analysis.
The aim of this paper is to explain critical features of the human primary generalized epilepsies by investigating the dynamical bifurcations of a nonlinear model of the brain's mean field dynamics.Expand
Prediction of electroencephalographic spectra from neurophysiology.
A recent neurophysical model of propagation of electrical waves in the cortex is extended to include a physiologically motivated subcortical feedback loop via the thalamus. TheExpand
Unified neurophysical model of EEG spectra and evoked potentials
TLDR
Evoked response potentials are modelable as an impulse response that is a sum of component responses. Expand
A Quantitative Model of Sleep-Wake Dynamics Based on the Physiology of the Brainstem Ascending Arousal System
A quantitative, physiology-based model of the ascending arousal system is developed, using continuum neuronal population modeling, which involves averaging properties such as firing rates acrossExpand
Evaluating the Performance of Kalman-Filter-Based EEG Source Localization
TLDR
A recently developed inverse solution is introduced, which uses spatiotemporal Kalman filtering tuned through likelihood maximization. Expand
Estimation of multiscale neurophysiologic parameters by electroencephalographic means
TLDR
It is shown that new model‐based electroencephalographic (EEG) methods can quantify neurophysiologic parameters that underlie EEG generation in ways that are complementary to and consistent with standard physiologic techniques. Expand
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