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

doi:10.1109/BioCAS58349.2023.10388917

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

School of Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference 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 language	English
Title of host publication	2023 IEEE Biomedical Circuits and Systems Conference (BioCAS)
Publisher	IEEE
DOIs	https://doi.org/10.1109/BioCAS58349.2023.10388917
Publication status	E-pub ahead of print - 18 Jan 2024
Event	Artificial Intelligence BioMedical Circuits And Systems For Health - Westin Harbour Castle Hotel, Toronto, Canada Duration: 19 Oct 2023 → 21 Oct 2023 https://2023.ieee-biocas.org/

Publication series

Name	IEEE Biomedical Circuits and Systems (BIOCAS)
Publisher	IEEE
ISSN (Print)	2163-4025
ISSN (Electronic)	2766-4465

Conference

Conference	Artificial Intelligence BioMedical Circuits And Systems For Health
Abbreviated title	BIOCAS 2023
Country/Territory	Canada
City	Toronto
Period	19/10/23 → 21/10/23
Internet address	https://2023.ieee-biocas.org/

Keywords / Materials (for Non-textual outputs)

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

Access to Document

10.1109/BioCAS58349.2023.10388917

BIOCAS_2023Accepted author manuscript, 2.56 MBLicence: Creative Commons: Attribution (CC-BY)

FORTE: Functional Oxide Reconfigurable Technologies (FORTE): A Programme Grant
Prodromakis, T., Constandinou, T. G., Dudek, P., Koch, D. & Papavassiliou, C.
1/05/22 → 30/09/23
Project: Research

Cite this

Sbandati, C., Stathopoulos, S., Foster, P., Peer, N., Serb, A., Wang, S., Cohen, D., & Prodromakis, T. (2024). Tone Stimulus Detection in Rats Using RRAM-Based Local Field Potential Monitoring. In 2023 IEEE Biomedical Circuits and Systems Conference (BioCAS) (IEEE Biomedical Circuits and Systems (BIOCAS) ). IEEE. Advance online publication. https://doi.org/10.1109/BioCAS58349.2023.10388917

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title = "Tone Stimulus Detection in Rats Using RRAM-Based Local Field Potential Monitoring",

abstract = "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.",

keywords = "RRAM, bio-signal processing, edge processing, local field potential (LFP), memristor, real-time detection",

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

year = "2024",

month = jan,

day = "18",

doi = "10.1109/BioCAS58349.2023.10388917",

language = "English",

series = "IEEE Biomedical Circuits and Systems (BIOCAS) ",

publisher = "IEEE",

booktitle = "2023 IEEE Biomedical Circuits and Systems Conference (BioCAS)",

note = "Artificial Intelligence BioMedical Circuits And Systems For Health, BIOCAS 2023 ; Conference date: 19-10-2023 Through 21-10-2023",

url = "https://2023.ieee-biocas.org/",

}

Sbandati, C, Stathopoulos, S , Foster, P, Peer, N, Serb, A , Wang, S, Cohen, D & Prodromakis, T 2024, Tone Stimulus Detection in Rats Using RRAM-Based Local Field Potential Monitoring. in 2023 IEEE Biomedical Circuits and Systems Conference (BioCAS). IEEE Biomedical Circuits and Systems (BIOCAS) , IEEE, Artificial Intelligence BioMedical Circuits And Systems For Health, Toronto, Ontario, Canada, 19/10/23. https://doi.org/10.1109/BioCAS58349.2023.10388917

TY - GEN

T1 - Tone Stimulus Detection in Rats Using RRAM-Based Local Field Potential Monitoring

AU - Sbandati, Caterina

AU - Stathopoulos, Spyros

AU - Foster, Patrick

AU - Peer, Noam

AU - Serb, Alex

AU - Wang, Shiwei

AU - Cohen, Dana

AU - Prodromakis, Themis

PY - 2024/1/18

Y1 - 2024/1/18

N2 - 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.

AB - 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.

KW - RRAM

KW - bio-signal processing

KW - edge processing

KW - local field potential (LFP)

KW - memristor

KW - real-time detection

U2 - 10.1109/BioCAS58349.2023.10388917

DO - 10.1109/BioCAS58349.2023.10388917

M3 - Conference contribution

T3 - IEEE Biomedical Circuits and Systems (BIOCAS)

BT - 2023 IEEE Biomedical Circuits and Systems Conference (BioCAS)

PB - IEEE

T2 - Artificial Intelligence BioMedical Circuits And Systems For Health

Y2 - 19 October 2023 through 21 October 2023

ER -

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

Abstract / Description of output

Publication series

Conference

Keywords / Materials (for Non-textual outputs)

Access to Document

Fingerprint

Projects

FORTE: Functional Oxide Reconfigurable Technologies (FORTE): A Programme Grant

Cite this