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

Abstract

Disorders of consciousness (DoC) pose significant challenges in neurology. Conventional neuromodulation therapies for DoC have exhibited limited success, with varying effectiveness among patients. In this study, we introduce a computational approach for constructing personalized stimulus signals capable of inducing healthy-like neural activity patterns in DoC patients. Leveraging a simplified brain model based on neural field theory, we fit this model to the power spectrum of a patient with DoC and derive a personalized stimulus time series to induce a healthy-like power spectrum. By applying this stimulus to brain regions typically targeted by stimulation therapies such as deep brain stimulation and repetitive transcranial magnetic stimulation, we demonstrate in silico, the ability of our method to elicit EEG power spectra resembling those of healthy individuals. We speculate that in the course of a long-term treatment, when the brain produces healthy-like activity, it may trigger intrinsic plasticity mechanisms, potentially leading to sustained improvements in the patient's condition. While further clinical adjustments and validation are needed, this novel approach offers promise in tailoring brain stimulation therapies for DoC patients. Moreover, it presents potential extensions to other conditions that could also benefit from brain stimulation therapies.