Tone Stimulus Detection in Rats Using RRAM-Based Local Field Potential Monitoring

Caterina Sbandati, Spyros Stathopoulos, Patrick Foster, Noam Peer, Alex Serb, Shiwei Wang, Dana Cohen, Themis Prodromakis

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract / Description of output

The comprehension of brain activity presents signif-icant challenges in the field of neuroscience. Contrary to spikes, Local Field Potentials (LFPs) present improved stability acqui-sition in chronic implant scenarios and potential reductions in sampling and processing rates. While existing electrophysiology acquisition systems focus predominantly on spike detection and sorting, there is a lack of real-time tools for exploiting LFPs. To address this gap, we present a Resistive-RAM (RRAM) based approach to process LFP traces. Our method follows an improved Memristive Integrating Sensor (MIS) protocol to effectively detect LFP events recorded from the deep-brain of an awake rat, while externally stimulated by a tone. Experimental results demonstrate the feasibility of real-time neural activity processing, offering insights into detecting meaningful external stimuli and facilitating efficient neural state estimation.
Original languageEnglish
Title of host publication2023 IEEE Biomedical Circuits and Systems Conference (BioCAS)
Publication statusE-pub ahead of print - 18 Jan 2024
EventArtificial Intelligence BioMedical Circuits And Systems For Health - Westin Harbour Castle Hotel, Toronto, Canada
Duration: 19 Oct 202321 Oct 2023

Publication series

NameIEEE Biomedical Circuits and Systems (BIOCAS)
ISSN (Print)2163-4025
ISSN (Electronic)2766-4465


ConferenceArtificial Intelligence BioMedical Circuits And Systems For Health
Abbreviated titleBIOCAS 2023
Internet address


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