Mapping and assessment of epileptogenic foci using frequency-entropy templates

Much effort has been devoted to developing analysis methods of subdural electroencephalogram and depth electrode recordings of epileptic patients being evaluated for surgical resection. The general approach is to investigate the brain activity at different locations as recorded by the different electrodes in an attempt to localize the epileptogenic focus or foci. Currently, most of the methods are based on the notion that epileptogenic brain activity is associated with changes in synchronization and in complexity. Here we present a method that is based on the temporal dynamics combined with the spectral distribution of energy in terms of frequency-entropy (FE) templates. The FE templates are based upon maximum information partitioning into a set of frequency bands. The FE template is calculated by wavelet packet decomposition followed by an application of the best basis algorithm minimizing the entropy cost function. A comparison between two FE templates is performed by a special quantitative similarity measure according to the overlap in the partitioning into frequency bands and weighted by the bands' entropy. For localization of the epileptogenic foci, the templates of each electrode during the interictal period are compared with a representative template evaluated from the ensemble of all electrodes during the ictal period. We suggest associating the locations that reveal high template similarity to the ictal template with the epileptogenic foci. To test the method and the underlying assumptions, we perform retrospective analysis of the recorded brain activity, from both grid and depth electrodes, from 11 patients suffering from medically intractable epilepsy. Application of the ictal-interictal FE template similarity analysis revealed regions in the epileptic brain in which the interictal characteristics are highly similar to those of the ictal period. To asses the foci we compared the interictal templates of the different electrodes to each other, forming interelectrode similarity matrices. Investigation of these similarity matrices revealed the existence of a single distinct subcluster of electrodes with high interelectrode similarity in the brain activity of seven patients (type-I activity), and the existence of multiple high interelectrode similarity subclusters in the activity of four patients (type-II activity). Comparisons of the analysis results to the medical presurgical evaluations and the outcomes of the surgical resections suggest that the method may be helpful in the chronic evaluation of the epileptogenic zone before operation, and in some cases (type-I activity) without the need to wait for seizures to occur.