A Memristor-Inspired Computation for Epileptiform Signals in Spheroids
This addresses the need for real-time, low-cost monitoring of epileptiform signals in brain spheroid models, but appears incremental as it adapts memristor concepts to a specific domain.
The paper tackles the problem of detecting epileptiform activity in rodent hippocampal spheroids by developing a memristor-inspired computational method that generates a running spectrogram or fingerprint, enabling on-the-fly computation with low cost to alert for event onset.
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.