Seizure prediction in hippocampal and neocortical epilepsy using a model-based approach.

ABSTRACT:

Objectives

The aim of this study is to develop a model based seizure prediction method.

Methods

A neural mass model was used to simulate the macro-scale dynamics of intracranial EEG data. The model was composed of pyramidal cells, excitatory and inhibitory interneurons described through state equations. Twelve model's parameters were estimated by fitting the model to the power spectral density of intracranial EEG signals and then integrated based on information obtained by investigating changes in the parameters prior to seizures. Twenty-one patients with medically intractable hippocampal and neocortical focal epilepsy were studied.

Results

Tuned to obtain maximum sensitivity, an average sensitivity of 87.07% and 92.6% with an average false prediction rate of 0.2 and

SUBMITTER: Aarabi A 

PROVIDER: S-EPMC3994166 | biostudies-literature | 2014 May

REPOSITORIES: biostudies-literature