Personalized stimulation therapies for disorders of consciousness: a computational approach to inducing healthy-like brain activity based on neural field theory.
Polyakov, Daniel; Robinson, P A; MULLER, Elisaet al.
2025 • In Journal of Neural Engineering, 22 (3), p. 036033
EEG; brain stimulation; disorders of consciousness; neural field theory; Humans; Electroencephalography/methods; Computer Simulation; Consciousness Disorders/therapy; Consciousness Disorders/physiopathology; Precision Medicine/methods; Transcranial Magnetic Stimulation/methods; Brain/physiology; Brain/physiopathology; Deep Brain Stimulation/methods; Models, Neurological; Activity-based; Brain activity; Computational approach; Condition; Disorder of consciousness; Neural activity patterns; Neural field theories; Power-spectra; Stimulus signals; Brain; Consciousness Disorders; Deep Brain Stimulation; Electroencephalography; Precision Medicine; Transcranial Magnetic Stimulation; Biomedical Engineering; Cellular and Molecular Neuroscience
Abstract :
[en] Objective.Disorders of consciousness (DoC) remain a significant challenge in neurology, with traditional brain stimulation therapies showing limited and inconsistent efficacy across patients. This study presents a novel computational approach grounded in neural field theory for constructing personalized stimulus signals designed to induce healthy-like neural activity patterns in individuals with DoC.Approach.We employ a simplified brain model fitted to the electroencephalogram (EEG) power spectrum of a DoC patient, simulating the individual's neural dynamics. Using model equations and fitted parameters, we mathematically derive stimuli time series that cause the model to generate power spectra typical of healthy individuals. These stimuli are tailored for brain regions typically targeted by neuromodulation therapies, such as deep brain stimulation and repetitive transcranial magnetic stimulation.Main results.In silico simulations demonstrate that our method successfully induces healthy-like EEG power spectra in models fitted to DoC patients. Furthermore, when the model parameters were near a stability boundary, stimulation led to a bifurcation and lasting changes in the model's activity beyond the stimulation period.Significance.By inducing healthy-like neural activity, this approach may effectively activate plasticity mechanisms during long-term treatment, potentially leading to sustained improvements in a patient's condition. While further clinical adjustments and validation are needed, this method holds promise for improving therapeutic outcomes in DoC. Moreover, it offers potential extensions to other neurological conditions that could benefit from personalized brain stimulation therapies.
Disciplines :
Neurosciences & behavior
Author, co-author :
Polyakov, Daniel ; Department of Cognitive and Brain Sciences, Ben-Gurion University of the Negev, Be'er-Sheva, Israel
Robinson, P A ; School of Physics, The University of Sydney, Sydney, NSW, Australia
MULLER, Elisa ; Centre Hospitalier Universitaire de Liège - CHU > > Service de parodontologie, chirurgie bucco-dentaire et chirurgie implantaire ; Brain and Mind Centre, The University of Sydney, Sydney, NSW, Australia
Nunez Novo, Pablo ; Université de Liège - ULiège > Département des sciences cliniques ; Biomedical Engineering Group, University of Valladolid, Valladolid, Spain
Annen, Jitka ; Université de Liège - ULiège > GIGA > GIGA Neurosciences - Coma Science Group ; Department of Data Analysis, University of Ghent, Ghent, Belgium
Gosseries, Olivia ; Université de Liège - ULiège > GIGA > GIGA Neurosciences - Coma Science Group
Shriki, Oren ; Department of Cognitive and Brain Sciences, Ben-Gurion University of the Negev, Be'er-Sheva, Israel
Language :
English
Title :
Personalized stimulation therapies for disorders of consciousness: a computational approach to inducing healthy-like brain activity based on neural field theory.
CHIST-ERA FWO - Fonds Wetenschappelijk Onderzoek Vlaanderen ULiège - University of Liège F.R.S.-FNRS - Fonds de la Recherche Scientifique CHU Liège - Central University Hospital of Liege
Funding text :
Funding for this work was provided by a grant from the EU CHIST-ERA program. Additionally, this work was supported by the University and University Hospital of Li\u00E8ge, the Belgian National Funds for Scientific Research (FRS-FNRS), the FNRS PDR Project (T.0134.21), the ERA-Net FLAG-ERA JTC2021 Project ModelDXConsciousness (the Human Brain Project Partnering Project), the DoC-Box project (HORIZON-MSCA-2022-SE-01-01-101131344), and the FNRS MIS Project (F.4521.23), JA is postdoctoral fellow funded (1265522N) by the Fund for Scientific Research-Flanders (FWO), OG is a research associate at FRS-FNRS.We would like to thank Avigail Makbili from the Computational Psychiatry Lab at Ben-Gurion University, who took part in the processing and cleaning of the experimental EEG data. Additionally, we want to thank Prof. Yaniv Zigel from the Department of Biomedical Engineering at Ben-Gurion University, who helped develop the mathematics of this method.
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