Epileptic Disorders


Classification of electrical status epilepticus in sleep based on EEG patterns and spatiotemporal mapping of spikes Volume 24, issue 6, December 2022


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Department of Neurology, Government Medical College, Kozhikode, Kerala, India
Neetha Balaram
Department of Neurology, Government medical college, Calicut, Kozhikode, Kerala, 673008 India


We firstly aimed to describe and classify EEG patterns in electrical status epilepticus in sleep (ESES), and secondly subclassify EEG patterns based on analysis of spikes using spatio-temporal mapping and electrical source analysis.


Overnight EEGs (minimum: eight hours) of 30 children, aged 2-12 years, with ESES (spike-wave index: at least 50%) were selected. Average reference montage was used for dipole analysis and mapping. The location and orientation of the dipoles were determined by mapping positive and negative poles and applying the rules of mapping. The onset and propagation of the spikes and the latency between the two hemispheres (for bisynchronous spikes) were determined (based on source analysis using BESA research 7.1).


(1) ESES was classified as “generalised” (80%) and focal (20%) patterns; (2) the bisynchronous subtype in the “generalised” pattern was due to apparently synchronous bilateral activation of spikes (with lead-in of 20-60 ms from one hemisphere) with a tangential/oblique dipole (source analysis localised these spikes to around the peri-rolandic cortex); (3) the classic description of ESES spikes as “diffuse” spikes with bifrontal maxima is a misinterpretation using the 10-20 EEG system. Using voltage mapping and source analysis, cortical activation in the rolandic cortex was identified which imparts diffuse frontal negativity and parieto-occipital positivity; (4) ESES spikes showed intraspike and interspike dipole instability and the orientation of dipoles changed due to local spike propagation around the source and into the depth of the sulcus (which we refer to herein as “dancing dipoles”); and (5) focal ESES were classified as parietal, occipital and temporo-occipital patterns; a frontal ESES pattern was not seen.


Based on detailed mapping and source analysis of ESES, we have successfully reinterpreted various misconceptions in the literature. We have simplified the interpretation of complicated EEG patterns by extracting the primary and propagated sources which aid the classification of ESES. As the dipole is always stable in self-limited childhood epilepsy with centrotemporal spikes, we believe that the phenomenon of an intrinsically unstable dipole is a reliable qualitative EEG marker of ESES.