Artikel,
Brain Dynamics and Modeling in Epilepsy - Prediction and Control Studies
Springer Science+Business Media B.V., (2009)
Zusammenfassung
Epilepsy is a major neurological disorder characterized by intermittent
paroxysmal neuronal electrical activity, that may remain localized
or spread, and severely disrupt the brain’s normal operation. Epileptic
seizures are typical manifestations of such pathology. It is in the
last 20 years that prediction and control of epileptic seizures has
been the subject of intensive interdisciplinary research. In this
communication, we investigate epilepsy from the point of view of
pathology of the dynamics of the electrical activity of the brain.
In this framework, we revisit two critical aspects of the dynamics
of epileptic seizures – the seizure predictability
and seizure resetting – that may prove to be the keys for improved
seizure prediction and seizure control schemes. We use human EEG
data and the concepts of spatial synchronization of chaos, phase
and energy to first show that seizures could be predictable in the
order of tens of minutes prior to their onset. We then present additional
statistical evidence that the pathology of the brain dynamics prior
to seizures is reset mostly upon seizures’ occurrence, a phenomenon
we have called seizure resetting. Finally, using a biologically-plausible
neural population mathematical model that can exhibit seizure-like
behavior, we provide evidence for the effectiveness of a recently
devised seizure control scheme we have called “feedback decoupling”.
This scheme also provides an interesting dynamical model for ictogenesis
(generation of seizures).
