Mathematical Model Insights into EEG Origin under Transcranial Direct Current Stimulation (tDCS) in the Context of Psychosis

Riedinger, Joséphine; Hutt, Axel

doi:10.3390/jcm11071845

Cited by 3 publications

(9 citation statements)

References 111 publications

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“…Moreover, in the case of the brain response to small neurostimulation input, our assumption of the linear brain response is supported by results of [22]. The authors of this study measured the controllability Gramian of their brain model with nonlinear sigmoid transfer function, similar to the cortico-thalamic brain model [31] used in this paper. If the system exhibits nonlinear dynamics far from any linear approximation, such as bistable dynamics and chaotic evolution, the proposed vector fitting technique may yield a too large model error and thus instability of the closed-loop feedback.…”

Section: Model Estimationsupporting

confidence: 63%

“…A different model considers the cortico-thalamic feedback circuit [31]. It describes the cortex layers I-III and the cortico-thalamic loop between cortical layers IV-VI, the thalamic relay cell population and the reticular structure.…”

Section: Cortico-thalamic Brain Modelmentioning

confidence: 99%

“…Moreover, the reticular structure has the mean activity V ret . The fibers between the cortex and thalamus and the cortex and reticular structure exhibit a finite conduction delay τ [31,32]. The 7-dimensional dynamical system of the brain state…”

Section: Cortico-thalamic Brain Modelmentioning

confidence: 99%

“…only the cortical layers are stimulated with weights b i . The observation y captures the activity of the cortical excitatory populations [31,33] with C = (c 1 , 0, c 3 , 0, 0, 0, 0), c i > 0. For more details, please see the Appendix.…”

Section: Cortico-thalamic Brain Modelmentioning

confidence: 99%

“…( 16) are defined as (15). The choice of parameters is for the most part based on the paper in which it was developed [31].…”

Section: Cortico-thalamic Brain Model Detailsmentioning

confidence: 99%

See 4 more Smart Citations

Delayed closed-loop neurostimulation for the treatment of pathological brain rhythms in mental disorders

Wahl¹,

Riedinger²,

Duprez³

et al. 2023

Preprint

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Mental disorders (MD) are among the top most demanding challenges in world-wide health. According to the World Health Organization, the burden of MDs continues to grow with significant impact on health and major social and human rights. A large number of MDs 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. predefined 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 αand 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.

show abstract

Section: Model Estimationsupporting

confidence: 63%

Section: Cortico-thalamic Brain Modelmentioning

confidence: 99%

Section: Cortico-thalamic Brain Modelmentioning

confidence: 99%

Section: Cortico-thalamic Brain Modelmentioning

confidence: 99%

“…( 16) are defined as (15). The choice of parameters is for the most part based on the paper in which it was developed [31].…”

Section: Cortico-thalamic Brain Model Detailsmentioning

confidence: 99%

See 3 more Smart Citations

Delayed closed-loop neurostimulation for the treatment of pathological brain rhythms in mental disorders

Wahl¹,

Riedinger²,

Duprez³

et al. 2023

Preprint

View full text Add to dashboard Cite

show abstract

Induced synchronization by endogenous noise modulation in finite-size random neural networks: A stochastic mean-field study

Lefebvre,

Hutt

2023

Chaos: An Interdisciplinary Journal of Nonlinear Science

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Event-related synchronization and desynchronization (ERS/ERD) are well-known features found experimentally in brain signals during cognitive tasks. Their understanding promises to have much better insights into neural information processes in cognition. Under the hypothesis that neural information affects the endogenous neural noise level in populations, we propose to employ a stochastic mean-field model to explain ERS/ERD in the γ-frequency range. The work extends previous mean-field studies by deriving novel effects from finite network size. Moreover, numerical simulations of ERS/ERD and their analytical explanation by the mean-field model suggest several endogenous noise modulation schemes, which may modulate the system’s synchronization.

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

et al. 2023

Self Cite

View full text Add to dashboard Cite

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.

show abstract

Mathematical Model Insights into EEG Origin under Transcranial Direct Current Stimulation (tDCS) in the Context of Psychosis

Cited by 3 publications

References 111 publications

Delayed closed-loop neurostimulation for the treatment of pathological brain rhythms in mental disorders

Delayed closed-loop neurostimulation for the treatment of pathological brain rhythms in mental disorders

Induced synchronization by endogenous noise modulation in finite-size random neural networks: A stochastic mean-field study

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

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