Movement-activated cortical myoclonus in Dravet syndrome

Laura Canafoglia, Francesca Ragona, Ferruccio Panzica, Elena Piazza, Elena Freri, Simona Binelli, Vidmer Scaioli, Giuliano Avanzini, Tiziana Granata, Silvana Franceschetti

Research output: Contribution to journalArticle

Abstract

© 2017 Elsevier B.V. Purpose we characterized multifocal myoclonus in Dravet syndrome (DS) that was never systematically typified before. Methods we studied EEG-EMG recordings of 19 consecutive patients, aged 2–29 years, with DS associated with SCN1A gene mutations to detect and evaluate myoclonus based on the spectrum of EMG activity on antagonist muscle pairs and cortico-muscular coherence (CMC). Results multifocal action myoclonus was detected in all patients corresponding to brief EMG bursts, which occurred synchronously on antagonist muscles at a frequency peaking in beta band. There was significant CMC in beta band, and a cortico-muscular transfer time consistent with a cortical origin of the jerks. The somatosensory evoked potentials (SSEPs) were giant in only one patient who also showed exaggerated long-loop reflexes (LLRs). The nine patients who had experienced myoclonic seizures showed greater CMC. Conclusions The cortical myoclonus consistently observed in patients with DS shows features that are similar to those characterizing progressive myoclonus epilepsy, but differs because it does not have a severely worsening course and is not commonly associated with increased SSEPs or enhanced LLRs. This kind of myoclonus is an intrinsic feature of DS associated with SCN1A mutations, and may be a cause of disability. Significance We hypothesize that myoclonus is generated in cortical motor areas by hyper-synchronous oscillations, which are possibly due to sodium channel dysfunction.
Original languageEnglish
Pages (from-to)47-52
Number of pages6
JournalEpilepsy Research
Volume130
DOIs
Publication statusPublished - Feb 1 2017

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Keywords

  • Cortical myoclonus
  • Cortico-muscolar coherence
  • Dravet syndrome
  • SCN1A mutations
  • Somatosensory evoked potentials
  • Spectral analysis

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