Automatic Detection of High-Frequency Oscillations With Neuromorphic Spiking Neural Networks.

ABSTRACT: Interictal high-frequency oscillations (HFO) detected in electroencephalography recordings have been proposed as biomarkers of epileptogenesis, seizure propensity, disease severity, and treatment response. Automatic HFO detectors typically analyze the data offline using complex time-consuming algorithms, which limits their clinical application. Neuromorphic circuits offer the possibility of building compact and low-power processing systems that can analyze data on-line and in real time. In this review, we describe a fully automated detection pipeline for HFO that uses, for the first time, spiking neural networks and neuromorphic technology. We demonstrated that our HFO detection pipeline can be applied to recordings from different modalities (intracranial electroencephalography, electrocor

SUBMITTER: Burelo K 

PROVIDER: S-EPMC9205405 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature