DocumentCode :
1195332
Title :
Dynamical diseases of brain systems: different routes to epileptic seizures
Author :
Silva, Fernando H Lopes da ; Blanes, Wouter ; Kalitzin, Stiliyan N. ; Parra, Jaime ; Suffczynski, Piotr ; Velis, Demetrios N.
Author_Institution :
Dutch Epilepsy Clinics Found., Heemstede, Netherlands
Volume :
50
Issue :
5
fYear :
2003
fDate :
5/1/2003 12:00:00 AM
Firstpage :
540
Lastpage :
548
Abstract :
In this overview, we consider epilepsies as dynamical diseases of brain systems since they are manifestations of the property of neuronal networks to display multistable dynamics. To illustrate this concept we may 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 ictal state, that is characterized by paroxysmal occurrence of synchronous oscillations and is generally called, in neurology, a seizure. The transition between these two states can either occur: 1) as a continuous sequence of phases, like in some cases of mesial temporal lobe epilepsy (MTLE); or 2) as a sudden leap, like in most cases of absence seizures. In the mathematical terminology of nonlinear systems, we can say that in the first case the system´s attractor gradually deforms from an interictal to an ictal attractor. The causes for such a deformation can be either endogenous or external. In this type of ictal transition, the seizure possibly may be anticipated in its early, preclinical phases. In the second case, where a sharp critical transition takes place, we can assume that the system has at least two simultaneous interictal and ictal attractors all the time. To which attractor the trajectories converge, depends on the initial conditions and the system´s parameters. An essential question in this scenario is how the transition between the normal ongoing and the seizure activity takes place. Such a transition can occur either due to the influence of external or endogenous factors or due to a random perturbation and, thus, it will be unpredictable. These dynamical changes may not be detectable from the analysis of the ongoing EEG, but they may be observable only by measuring the system´s response to externally administered stimuli. In the special cases of reflex epilepsy, the leap between the normal ongoing attractor and the ictal attractor is c- - aused by a well-defined external perturbation. Examples from these different scenarios are presented and discussed.
Keywords :
brain models; diseases; electroencephalography; magnetoencephalography; medical signal detection; neural nets; neurophysiology; nonlinear dynamical systems; MEG signals; absence seizures; biomedical signal analysis; brain modeling; brain systems; dynamical diseases; endogenous factors; epilepsies; epileptic brain states; epileptic seizure; external factors; ictal attractors; ictal state; ictal transition; interictal attractors; interictal state; mesial temporal lobe epilepsy; multistable dynamics; neuronal networks; nonlinear systems; normal ongoing attractor; normal steady-state electroencephalography; paroxysmal occurrence; random perturbation; reflex epilepsy; sharp critical transition; synchronous oscillations; system attractor deformation; Biological neural networks; Diseases; Displays; Electroencephalography; Epilepsy; Nervous system; Nonlinear systems; Steady-state; Temporal lobe; Terminology; Brain; Electroencephalography; Epilepsy; Humans; Magnetoencephalography; Models, Neurological; Nerve Net; Neurons; Nonlinear Dynamics; Seizures; Signal Processing, Computer-Assisted;
fLanguage :
English
Journal_Title :
Biomedical Engineering, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9294
Type :
jour
DOI :
10.1109/TBME.2003.810703
Filename :
1198244
Link To Document :
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