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

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

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The comprehension of brain activity presents significant challenges in the field of neuroscience. Contrary to spikes, Local Field Potentials (LFPs) present improved stability acquisition 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 publicationBioCAS 2023 - 2023 IEEE Biomedical Circuits and Systems Conference, Conference Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9798350300260
DOIs
StatePublished - 2023
Event2023 IEEE Biomedical Circuits and Systems Conference, BioCAS 2023 - Toronto, Canada
Duration: 19 Oct 202321 Oct 2023

Publication series

NameBioCAS 2023 - 2023 IEEE Biomedical Circuits and Systems Conference, Conference Proceedings

Conference

Conference2023 IEEE Biomedical Circuits and Systems Conference, BioCAS 2023
Country/TerritoryCanada
CityToronto
Period19/10/2321/10/23

Bibliographical note

Publisher Copyright:
© 2023 IEEE.

Funding

This work has been supported by the UK Engineering and Physical Sciences Research Council grant EP/R024642/1 (FORTE) and the EU commission H2020 programme no. 824165 (SYNCH).

FundersFunder number
EU commission H2020824165
Engineering and Physical Sciences Research CouncilEP/R024642/1
Forskningsrådet om Hälsa, Arbetsliv och Välfärd

    Keywords

    • RRAM
    • bio-signal processing
    • edge processing
    • local field potential (LFP)
    • memristor
    • real-time detection

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