# TMS–EEG signatures of motor network dysfunction in multiple sclerosis

## TL;DR

TMS–EEG reveals motor network dysfunction in multiple sclerosis, offering potential biomarkers for disease activity and disability.

## Contribution

TMS–EEG signatures are shown to detect subtle motor network changes in MS not captured by traditional methods.

## Key findings

- MS patients showed reduced P60 amplitude and less gamma-band desynchronization compared to controls.
- Gamma-band desynchronization correlated inversely with manual dexterity test performance.
- P15 amplitude predicted disease stability with 74.4% accuracy over 2 years.

## Abstract

Multiple sclerosis (MS) progressively impairs brain network function, often driving disability even in the absence of overt structural MRI changes. Current clinical and radiological tools frequently fail to capture early, subtle disruptions in cortical activity that may indicate ongoing disease progression. Functional assessment methods capable of detecting these early network alterations are therefore critically needed. This study aimed to determine whether brain responses recorded by combining transcranial magnetic stimulation (TMS) with electroencephalography (EEG) from the primary motor cortex differ in MS, correlate with clinical disability and predict disease activity. Sixty-nine right-handed participants [mean age: MS 38.5 ± 9.1 years, healthy controls (HCs) 36.9 ± 8.8 years; 41 females] were enrolled, including 43 patients with relapsing–remitting MS and 26 HCs matched for age and sex. MS patients were clinically stable and off corticosteroids or CNS-acting medications at least 1 month prior to testing. All underwent single-pulse stimulation over the left primary motor cortex during EEG recording. Transcranial-evoked potentials (TEPs) and spectral perturbations were extracted. Patients were followed for 2 years and classified as active or stable based on ‘No Evidence of Disease Activity-3’ criteria. Patients showed significantly reduced P60 amplitude compared with controls (P = 0.0098, FDR-corrected P adj. = 0.0491), and a trend-level reduction in gamma-band desynchronization (i.e. less negative values) (P = 0.025, P adj. = 0.075), which correlated inversely with 9-Hole Peg Test times (rs = −0.504, P = 0.001). A trend towards lower P15 amplitude was observed in patients with active disease (P = 0.0178, P adj. = 0.0891), and P15 amplitude significantly predicted disease stability at 2 years (accuracy = 74.4%, P = 0.023). TMS combined with EEG detects altered motor cortical network dynamics in MS. Less-pronounced (i.e. less negative) gamma-band desynchronization correlated with preserved fine-motor network efficiency, potentially reflecting a compensatory mechanism. The P15-evoked potential amplitude may predict disease activity. This perturbation-based approach provides a privileged window into network dysfunction in MS, with potential to guide early prognosis and treatment.

Leodori et al. report that transcranial magnetic stimulation combined with electroencephalography (TMS–EEG) captures differences in cortical motor network responses in multiple sclerosis. TMS–EEG measures correlate with manual dexterity and provide modest prediction of 2-year disease stability, highlighting their potential as functional biomarkers.

Graphical Abstract