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Band power modulation through intracranial EEG stimulation and its cross-session consistency

Lookup NU author(s): Christoforos Papasavvas, Gabrielle Schroeder, Professor Peter TaylorORCiD, Professor Yujiang WangORCiD

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This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).


Abstract

OBJECTIVE: Direct electrical stimulation of the brain through intracranial electrodes is currently used to probe the epileptic brain as part of pre-surgical evaluation, and it is also being considered for therapeutic treatments through neuromodulation. In order to effectively modulate neural activity, a given neuromodulation design must elicit similar responses throughout the course of treatment. However, it is unknown whether intracranial electrical stimulation responses are consistent across sessions. The objective of this study was to investigate the within-subject, cross-session consistency of the electrophysiological effect of electrical stimulation delivered through intracranial electroencephalography (iEEG). APPROACH: We analysed data from 79 epilepsy patients implanted with iEEG who underwent brain stimulation as part of a memory experiment. We quantified the effect of stimulation in terms of band power modulation and compared this effect from session to session. As a reference, we made the same measurements during baseline periods. MAIN RESULTS: In most sessions, the effect of stimulation on band power could not be distinguished from baseline fluctuations of band power. Stimulation effect was consistent in a third of the session pairs, while the rest had a consistency measure not exceeding the baseline standards. Cross-session consistency was highly correlated with the degree of band power increase, and it also tended to be higher when the baseline conditions were more similar between sessions. SIGNIFICANCE: These findings can inform our practices for designing neuromodulation with greater efficacy when using direct electrical brain stimulation as a therapeutic treatment.


Publication metadata

Author(s): Papasavvas CA, Schroeder GM, Diehl B, Baier G, Taylor PN, Wang Y

Publication type: Article

Publication status: Published

Journal: Journal of Neural Engineering

Year: 2020

Volume: 17

Issue: 5

Online publication date: 28/10/2020

Acceptance date: 01/10/2020

Date deposited: 22/03/2021

ISSN (print): 1741-2560

ISSN (electronic): 1741-2552

Publisher: IOP

URL: https://doi.org/10.1088/1741-2552/abbecf

DOI: 10.1088/1741-2552/abbecf

PubMed id: 33022661


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Funding

Funder referenceFunder name
210109/Z/18/ZWellcome Trust
208940/Z/17/ZWellcome Trust

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