Seizure anticipation in human neocortical partial epilepsy
Open Access
- 1 March 2002
- journal article
- research article
- Published by Oxford University Press (OUP) in Brain
- Vol. 125 (3) , 640-655
- https://doi.org/10.1093/brain/awf048
Abstract
The transition of brain activity towards an epileptic seizure is still a poorly understood phenomenon. Dynamic changes in brain activity have been detected several minutes before seizure emergence in populations of patients with mesial temporal lobe epilepsy (MTLE), using non‐linear analysis of intracranial EEG recordings. Similar detection of a pre‐ictal state has been obtained with standard scalp EEG recordings using a modified non‐linear method. Here we applied this strategy to the seizures of patients with neocortical partial epilepsy. Results obtained by non‐linear similarity analysis of 41 seizures from 11 patients with refractory partial epilepsy originating from various sites of the neocortex showed that (i) a pre‐ictal state was detected in 90% of the patients and in 83% of the seizures whatever their location, with a mean anticipation time of 7.5 min; (ii) similar pre‐ictal dynamic changes were detected when non‐linear analysis methods were applied to either intracranial or scalp EEG recordings; (iii) the recording sites exhibiting these pre‐ictal changes were distributed both within the epileptogenic focus and at remote locations; (iv) most pre‐ictal dynamic changes were not correlated with linear changes in the frequency spectrum or with changes in the visually inspected EEG and the patients’ behaviour. Hypotheses on the neuronal mechanisms underlying the pre‐ictal period are discussed. The present results, together with those recently obtained in an MTLE population, suggest that changes in pre‐ictal dynamics are a general phenomenon associated with seizure emergence in a wide population of patients with partial epilepsy, wherever the epileptogenic focus is located. The possibility of anticipating the onset of seizures has considerable therapeutic implications.Keywords
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