MEP and TEP features variability: is it just the brain-state?

Abstract

Objective: The literature investigating the effects of alpha oscillations on corticospinal excitability is divergent. We believe inconsistency in the findings may arise, among others, from the EEG processing for brain-state determination. Here, we provide further insights in the effects of the brain-state on cortical and corticospinal excitability and quantify the impact of different EEG processing. 
Approach: Corticospinal excitability was measured using motor evoked potential (MEP) peak-to-peak amplitudes elicited with transcranial magnetic stimulation (TMS); cortical responses were studied through TMS-evoked potentials’ (TEPs) features. A TMS-EEG-EMG dataset of 18 young healthy subjects who received 180 single-pulse and 180 paired pulses to determine short-intracortical inhibition was investigated. To study the effect of different EEG processing, we compared the brain-state estimation deriving from three published methods. The influence of presence of neural oscillations was also investigated. To evaluate the effect of the brain-state on MEP and TEP features variability, we defined the brain-state based on specific EEG phase and power combinations, only in trials where neural oscillations were present. The relationship between TEPs and MEPs was further evaluated.
Main results: The presence of neural oscillations resulted in more consistent results regardless of the EEG processing approach. Nonetheless, the latter still critically affected the outcomes, making conclusive claims complex. With our approach, the MEP amplitude was positively modulated by the alpha power and phase, with stronger responses during the trough phase and high power. Power and phase also affected TEP features. Importantly, similar effects were observed in both TMS conditions. 
Significance: These findings support the view that the brain state of alpha oscillations is associated with the variability observed in cortical and corticospinal responses to TMS, with a tight correlation between the two. The results further highlight the importance of closed-loop stimulation approaches while underlining that care is needed in designing experiments and choosing the analytical approaches, which should be based on knowledge from offline studies to control for the heterogeneity originating from different EEG processing strategies.

Motor sequence learning elicits mu peak-specific corticospinal plasticity

“…Given the PHASE x POWER interaction identified in our previous work and that of others (Bigoni et al, 2024;Ozdemir et al, 2022;Suresh & Hussain, 2023) and our primary interest in evaluating phase-dependent corticospinal plasticity, we included the PHASE x natural log-transformed POWER interaction as a covariate in all our LMMs to control for this known interaction effect Suresh & Hussain, 2023). Furthermore, it is well established that pre-stimulus voluntary muscle activation can increase MEP amplitudes (Hess et al, 1996).…”