Abstract
Seizure semiology represents the dynamic clinical expression of seizures and is an important behavioral data source providing clues to cerebral organization. It is produced through interactions between electrical seizure discharge and physiologic and pathologic brain networks. Semiology is described in spatial and temporal terms; its expression depends on spatial (localization) and temporal (eg, discharge frequency, synchrony) characteristics of cerebral electrical activity. Stereoelectroencephalography studies of electroclinical correlations, including with quantified signal analysis, have helped elucidate several semiological patterns. Future research could help improve pattern recognition of complex semiological patterns, possibly using deep learning methods in a multiscale, multimodal modelization framework.
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