F.H.L. da Silva

TL;DR: In this paper, the authors consider epilepsies as dynamical diseases of brain systems since they are manifestations of the property of neuronal networks to display multistable dynamics, and they assume that at least two states of the epileptic brain are possible: the interictal state characterized by a normal, apparently random, steady-state electroencephalography (EEG) ongoing activity, and the seizure state, that is characterized by paroxysmal occurrence of synchronous oscillations and is generally called, in neurology, a seizure.

TL;DR: The analysis showed that in certain cases, the transitions between ictal and interictal states can be modeled by a Poisson process operating in a bistable network.

TL;DR: Preliminary results suggest that the /spl rho//sub skull/ variations over subjects cannot be disregarded in the EEG inverse problem (IP) when a spherical model is used.

TL;DR: This paper reviews various computational models of the brain and insights obtained through their simulations and describes the different levels of neuronal organization at which the model can be set.

TL;DR: It is shown that for linearly coupled signals high associations are always bidirectional, and high asymmetric nonlinear associations are indicators of nonlinear relations, possibly critical, between the dynamic systems underlying the measured signals.