Delayed closed-loop neurostimulation for the treatment of pathological brain rhythms in mental disorders: a computational study

Mental disorders are among the top most demanding challenges in world-wide health. A large number of mental disorders exhibit pathological rhythms, which serve as the disorders characteristic biomarkers. These rhythms are the targets for neurostimulation techniques. Open-loop neurostimulation employ...

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Main Authors: Thomas Wahl, Joséphine Riedinger, Michel Duprez, Axel Hutt
Format: Article
Language:English
Published: Frontiers Media S.A. 2023-07-01
Series:Frontiers in Neuroscience
Subjects:
Online Access:https://www.frontiersin.org/articles/10.3389/fnins.2023.1183670/full
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author Thomas Wahl
Joséphine Riedinger
Joséphine Riedinger
Michel Duprez
Axel Hutt
author_facet Thomas Wahl
Joséphine Riedinger
Joséphine Riedinger
Michel Duprez
Axel Hutt
author_sort Thomas Wahl
collection DOAJ
description Mental disorders are among the top most demanding challenges in world-wide health. A large number of mental disorders exhibit pathological rhythms, which serve as the disorders characteristic biomarkers. These rhythms are the targets for neurostimulation techniques. Open-loop neurostimulation employs stimulation protocols, which are rather independent of the patients health and brain state in the moment of treatment. Most alternative closed-loop stimulation protocols consider real-time brain activity observations but appear as adaptive open-loop protocols, where e.g., pre-defined stimulation sets in if observations fulfil pre-defined criteria. The present theoretical work proposes a fully-adaptive closed-loop neurostimulation setup, that tunes the brain activities power spectral density (PSD) according to a user-defined PSD. The utilized brain model is non-parametric and estimated from the observations via magnitude fitting in a pre-stimulus setup phase. Moreover, the algorithm takes into account possible conduction delays in the feedback connection between observation and stimulation electrode. All involved features are illustrated on pathological α- and γ-rhythms known from psychosis. To this end, we simulate numerically a linear neural population brain model and a non-linear cortico-thalamic feedback loop model recently derived to explain brain activity in psychosis.
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spelling doaj.art-9e72fe0411994d89acfe3be529c6bdb22023-07-05T14:54:46ZengFrontiers Media S.A.Frontiers in Neuroscience1662-453X2023-07-011710.3389/fnins.2023.11836701183670Delayed closed-loop neurostimulation for the treatment of pathological brain rhythms in mental disorders: a computational studyThomas Wahl0Joséphine Riedinger1Joséphine Riedinger2Michel Duprez3Axel Hutt4ICube, MLMS, MIMESIS Team, Inria Nancy - Grand Est, University of Strasbourg, Strasbourg, FranceICube, MLMS, MIMESIS Team, Inria Nancy - Grand Est, University of Strasbourg, Strasbourg, FranceINSERM U1114, Neuropsychologie Cognitive et Physiopathologie de la Schizophrénie, Strasbourg, FranceICube, MLMS, MIMESIS Team, Inria Nancy - Grand Est, University of Strasbourg, Strasbourg, FranceICube, MLMS, MIMESIS Team, Inria Nancy - Grand Est, University of Strasbourg, Strasbourg, FranceMental disorders are among the top most demanding challenges in world-wide health. A large number of mental disorders exhibit pathological rhythms, which serve as the disorders characteristic biomarkers. These rhythms are the targets for neurostimulation techniques. Open-loop neurostimulation employs stimulation protocols, which are rather independent of the patients health and brain state in the moment of treatment. Most alternative closed-loop stimulation protocols consider real-time brain activity observations but appear as adaptive open-loop protocols, where e.g., pre-defined stimulation sets in if observations fulfil pre-defined criteria. The present theoretical work proposes a fully-adaptive closed-loop neurostimulation setup, that tunes the brain activities power spectral density (PSD) according to a user-defined PSD. The utilized brain model is non-parametric and estimated from the observations via magnitude fitting in a pre-stimulus setup phase. Moreover, the algorithm takes into account possible conduction delays in the feedback connection between observation and stimulation electrode. All involved features are illustrated on pathological α- and γ-rhythms known from psychosis. To this end, we simulate numerically a linear neural population brain model and a non-linear cortico-thalamic feedback loop model recently derived to explain brain activity in psychosis.https://www.frontiersin.org/articles/10.3389/fnins.2023.1183670/fullneurostimulationclosed-loopcontrolreal-timedelayEEG
spellingShingle Thomas Wahl
Joséphine Riedinger
Joséphine Riedinger
Michel Duprez
Axel Hutt
Delayed closed-loop neurostimulation for the treatment of pathological brain rhythms in mental disorders: a computational study
Frontiers in Neuroscience
neurostimulation
closed-loop
control
real-time
delay
EEG
title Delayed closed-loop neurostimulation for the treatment of pathological brain rhythms in mental disorders: a computational study
title_full Delayed closed-loop neurostimulation for the treatment of pathological brain rhythms in mental disorders: a computational study
title_fullStr Delayed closed-loop neurostimulation for the treatment of pathological brain rhythms in mental disorders: a computational study
title_full_unstemmed Delayed closed-loop neurostimulation for the treatment of pathological brain rhythms in mental disorders: a computational study
title_short Delayed closed-loop neurostimulation for the treatment of pathological brain rhythms in mental disorders: a computational study
title_sort delayed closed loop neurostimulation for the treatment of pathological brain rhythms in mental disorders a computational study
topic neurostimulation
closed-loop
control
real-time
delay
EEG
url https://www.frontiersin.org/articles/10.3389/fnins.2023.1183670/full
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