Hostname: page-component-586b7cd67f-g8jcs Total loading time: 0 Render date: 2024-11-25T22:55:58.127Z Has data issue: false hasContentIssue false

P.125 Discriminating sharp-wave ripples and interictal epileptiform discharges in patients with mesial temporal epilepsy using intracranial EEG recordings

Published online by Cambridge University Press:  05 January 2022

N Mortazavi
Affiliation:
(London)*
M Khaki
Affiliation:
(London)
G Gilmore
Affiliation:
(London)
J Burneo
Affiliation:
(London)
D Steven
Affiliation:
(London)
J Martinez-Trujillo
Affiliation:
(London)
A Suller-Marti
Affiliation:
(London)
Rights & Permissions [Opens in a new window]

Abstract

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.

Background: Interictal epileptiform discharges (IEDs) are known as epilepsy biomarkers for seizure detection, and It is essential for clinicians to detect them from from physiological events with similar temporal frequency characteristics. Methods: We analyzed the SEEG recordings obtained from patients with medically-resistant epilepsy (MRE) implanted with DE at the Western University Hospital Epilepsy Unit. The data were cleaned, denoised, montaged and segmented based on the clinical annotations, such as sleep intervals and observed Ictals. For event detection, the signal waveform and its power were extracted symmetrically in non-overlapping intervals of 500 ms. Each waveform’s power across all detected spikes was computed and clustered based on their energy distributions. Results: The recordings included thirteen sessions of 24 hours of extracellular recordings from two patients, with 312 hours extracted from four hippocampus electrodes anterior and posterior hippocampus. Our results indicate IEDs carrying the most different characteristics in the bands [25-75] Hz; SWR, on the other hand, are distributed between [80-170] Hz. Conclusions: Our algorithm detected and successfully distinguished IED from SWRs based on their carrying energy during non-sleep periods. Also, the most powerful spectral features that they were distinguished from occur in [15-30] Hz and [75-90] Hz.

Type
Poster Presentations
Copyright
© The Author(s), 2021. Published by Cambridge University Press on behalf of Canadian Neurological Sciences Federation