Piotr Suffczynski

TL;DR: It is considered that neuronal networks involved in epilepsy possess multistable dynamics (i.e., they may display several dynamic states), and at least two states are possible: an interictal one characterized by a normal, apparently random, steady ‐state of ongoing activity, and another one that is characterized by the paroxysmal occurrence of a synchronous oscillations (seizure).

TL;DR: A computational model of thalamo-cortical circuits based on relevant (patho)physiological data is developed to provide more insight into the dynamics of the neuronal networks leading to seizure generation in a rat experimental model of absence epilepsy.

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 hypothesis that this basic neurophysiological mechanism can account for the general observation that enhanced attention given to a certain stimulus (the focus) is coupled to inhibition of attention to other stimuli (the surround) is formed.

TL;DR: Experimental evidence for the existence of the two types of alpha rhythm and the bifurcation predicted by the model is found, apparently, during these epochs the activity of the brain has such a high complexity that it cannot be distinguished from a random process.