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Personalized stimulation therapies for disorders of consciousness: a computational approach to inducing healthy-like brain activity based on neural field theory.

Daniel Polyakov, P A Robinson, Eli J Müller, Glenn van der Lande, Pablo Núñez, Jitka Annen, Olivia Gosseries, Oren Shriki

Journal of neural engineering June 10, 2025 DOI: 10.1088/1741-2552/addd48 via PubMed

Summary

AI-generated from the abstract

A computational method uses a simplified brain model fitted to a patient's EEG power spectrum to design personalized electrical stimulation signals. In computer simulations, these signals induce healthy-like brain activity patterns in models of people with disorders of consciousness. When the model's parameters were near a stability boundary, stimulation caused a lasting change in activity beyond the stimulation period. The approach may activate plasticity mechanisms during long-term treatment, potentially leading to sustained improvements. Further clinical adjustments and validation are needed, but the method holds promise for improving therapeutic outcomes in disorders of consciousness and may extend to other neurological conditions.

Study at a glance

Characteristics In silico simulation Peer reviewed
Population Simulated brain models fitted to EEG data from a patient with disorders of consciousness
Keywords EEG Brain stimulation Disorders of consciousness Neural field theory Neuroscience
Citations 2
Key finding In silico simulations show that personalized stimulus signals derived from a neural field model can induce healthy-like EEG power spectra in models fitted to patients with disorders of consciousness, and near stability boundaries the stimulation can produce lasting changes in model activity.

Abstract

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.

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