title: EEG-EMG coherence estimated using time-varying autoregressive models in movement-activated myoclonus in patients with progressive myoclonic epilepsies.
abstract: We aimed this study at verifying the appropriateness of bivariate time-varying autoregressive models in detecting EEG-EMG relationships and identifying the characteristics of myoclonus-related EEG changes in patients with two forms of progressive myoclonus epilepsy (PME). Our results indicate that TVAR analysis was able to detect the presence of prominent peaks of EEG-EMG coherence between the EMG and contralateral frontocentral EEG derivation in all patients, revealing differences in time-frequency spectral profiles associated to the two different forms of PMEs, possibly correlated with the severity of myoclonus.
authors.affiliation: Dept. of Neurophysiology and Diagnostic Epileptology, Fondazione IRCCS Istituto Neurologico C. Besta Milano, Italy. panzica@istiuto-besta.it
authors.forename: Ferruccio
authors.initials: F
authors.lastname: Panzica
authors.forename: Giulia
authors.initials: G
authors.lastname: Varotto
authors.forename: Laura
authors.initials: L
authors.lastname: Canafoglia
authors.forename: Davide
authors.initials: D
authors.lastname: Rossi Sebastiano
authors.forename: Elisa
authors.initials: E
authors.lastname: Visani
authors.forename: Silvana
authors.initials: S
authors.lastname: Franceschetti
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D004569:Electroencephalography / Q000379:methods*; D004576:Electromyography / Q000379:methods*; D006801:Humans; D008954:Models, Biological; D008959:Models, Neurological; D009068:Movement; D020191:Myoclonic Epilepsies, Progressive / Q000175:diagnosis* / Q000503:physiopathology*; D012044:Regression Analysis; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity