A Memristor-Inspired Computation for Epileptiform Signals in Spheroids
Iv\'an D\'iez de los R\'ios, John Wesley Ephraim, Gemma Palazzolo,, Teresa Serrano-Gotarredona, Gabriella Panuccio, Bernab\'e Linares-Barranco
TL;DR
This paper introduces a memristor-inspired computational method to generate real-time, low-cost spectrograms of epileptiform activity in rodent hippocampal spheroids, aiding in early detection of seizure events.
Contribution
The paper presents a novel memristor-inspired algorithm for real-time analysis of epileptiform signals in hippocampal spheroids, enhancing detection efficiency and computational simplicity.
Findings
Effective real-time fingerprinting of epileptiform activity
Low computational cost for on-the-fly analysis
Successful illustration with hippocampal spheroid data
Abstract
In this paper we present a memristor-inspired computational method for obtaining a type of running spectrogram or fingerprint of epileptiform activity generated by rodent hippocampal spheroids. It can be used to compute on the fly and with low computational cost an alert-level signal for epileptiform events onset. Here, we describe the computational method behind this fingerprint technique and illustrate it using epileptiform events recorded from hippocampal spheroids using a microelectrode array system.
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