Personalized whole-brain activity patterns predict human corticospinal tract activation in real-time

3Citations
Citations of this article
17Readers
Mendeley users who have this article in their library.

This article is free to access.

Abstract

Background: Transcranial magnetic stimulation (TMS) interventions could feasibly treat stroke-related motor impairments, but their effects are highly variable. Brain state-dependent TMS approaches are a promising solution to this problem, but inter-individual variation in lesion location and oscillatory dynamics can make translating them to the poststroke brain challenging. Personalized brain state-dependent approaches specifically designed to address these challenges are needed. Methods: As a first step towards this goal, we tested a novel machine learning-based EEG-TMS system that identifies personalized brain activity patterns reflecting strong and weak corticospinal tract (CST) activation (strong and weak CST states) in healthy adults in real-time. Participants completed a single-session study that included the acquisition of a TMS-EEG-EMG training dataset, personalized classifier training, and real-time EEG-informed single-pulse TMS during classifier-predicted personalized CST states. Results: MEP amplitudes elicited in real-time during classifier-predicted personalized strong CST states were significantly larger than those elicited during corresponding weak and random CST states. MEP amplitudes elicited in real-time during classifier-predicted personalized strong CST states were also significantly less variable than those elicited during corresponding weak CST states. Personalized CST states lasted for ∼1–2 s at a time and ∼1 s elapsed between consecutive similar states. Individual participants exhibited unique differences in spectro-spatial EEG patterns between classifier-predicted personalized strong and weak CST states. Conclusion: Our results show for the first time that personalized whole-brain EEG activity patterns predict CST activation in real-time in healthy humans. These findings represent a pivotal step towards using personalized brain state-dependent TMS interventions to promote poststroke CST function.

Cite

CITATION STYLE

APA

Khatri, U. U., Pulliam, K., Manesiya, M., Cortez, M. V., Millán, J. del R., & Hussain, S. J. (2025). Personalized whole-brain activity patterns predict human corticospinal tract activation in real-time. Brain Stimulation, 18(1), 64–76. https://doi.org/10.1016/j.brs.2024.12.1193

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free