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 patients 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. Author summaryIn this research, we tackled a challenging issue in the field of neurology - disorders of consciousness (DoC). These conditions, which include states like coma and the minimally consciousness state, have been difficult to treat effectively. While traditional brain stimulation treatments have been tried, they do not always work well, and their effects can vary greatly from one person to another. Thus, we set out to find a new way to help these patients. Our approach involves using computer models of the brain to design personalized treatments. We designed a method to generate stimulation signals tailored to individual DoC patients. These signals aim to trigger healthier brain activity patterns, similar to those found in individuals without consciousness disorders. What is exciting is that if the brain begins to produce these healthy-like patterns, it could potentially lead to lasting improvements in the patients consciousness level. We show that this approach works in different simulations, and can be applied in multiple neuromodulation techniques like deep brain stimulation and transcranial magnetic stimulation. This research opens up new possibilities for more effective treatments for people dealing with these challenging disorders. Plus, it might work for other conditions treated with similar brain stimulation therapies.