Bihemispheric sensorimotor oscillatory network states determine cortical responses to transcranial magnetic stimulation

Background: Brain responses to external stimuli vary with fluctuating states of neuronal activity. Previous work has demonstrated effects of phase and power of the ongoing local sensorimotor mu-alpha-oscillation on responses to transcranial magnetic stimulation (TMS) of motor cortex (M1). However, M1 is part of a distributed network, and the effects of oscillatory activity in this network on TMS-evoked EEG responses (TEPs) have not been explored. Objectives: To determine the effects of oscillatory activity in the bihemispheric sensorimotor network on TEPs. Methods: 31 healthy subjects received single-pulse TMS of the left M1 hand area during EEG recording. Ongoing bihemispheric sensorimotor cortex oscillatory states were reconstructed from the EEG directly preceding TMS, and inferred by a data-driven method combining a multivariate autoregressive model and a Hidden Markov model. TEP amplitudes (P25, N45, P70, N100 and P180) were then compared between different bihemispheric sensorimotor cortex oscillatory states. Results: Four bihemispheric sensorimotor cortex oscillatory states were identified, with different interhemispheric expressions of theta and alpha oscillations. High alpha-power states in the stimulated sensorimotor cortex increased P25 amplitude. Alpha power in the alpha-alpha state (stimulated - nonstimulated hemisphere) correlated in both hemispheres with N45 amplitude. Theta power in the alphatheta state correlated in the non-stimulated hemisphere with P70 amplitude. Conclusions: Bihemispheric sensorimotor cortex oscillatory states contribute to TEPs, with a relevance shift from stimulated to non-stimulated M1 from P25 over N45 to P70. This significantly extends previous findings: not only ongoing local oscillations but distributed network oscillatory states determine cortical responsiveness to external stimuli. (C) 2021 The Authors. Published by Elsevier Inc.

Automated summary

This study revealed the effects of oscillatory activity in the bihemispheric sensorimotor network on TMS-evoked EEG responses, expanding previous findings on the relevance of distributed network oscillatory states in determining cortical responsiveness to external stimuli.