Related Experiment Video
Updated: May 5, 2026
08:23
A Multimodal Imaging- and Stimulation-based Method of Evaluating Connectivity-related Brain Excitability in Patients with Epilepsy
Published on: November 13, 2016
10.1K
TMS-EEG signatures of motor network dysfunction in multiple sclerosis.
Giorgio Leodori1,2, Marco Mancuso1, Davide Maccarrone1
1Department of Human Neurosciences, Sapienza University of Rome, Rome 00189, Italy.
Brain Communications
|February 20, 2026
Summary
Transcranial magnetic stimulation combined with electroencephalography reveals altered brain network function in multiple sclerosis (MS). This technique may predict disease activity and disability progression in MS patients.
Area of Science:
- Neuroscience
- Clinical Neurology
- Biomedical Engineering
Background:
- Multiple sclerosis (MS) causes progressive brain network dysfunction and disability, often without obvious MRI changes.
- Existing clinical and radiological tools struggle to detect early, subtle cortical activity disruptions in MS.
- Functional assessment methods are needed to identify early network alterations for better MS management.
Purpose of the Study:
- To investigate differences in brain responses using TMS-EEG in the primary motor cortex of MS patients compared to healthy controls.
- To determine if these responses correlate with clinical disability in MS.
- To assess the predictive value of TMS-EEG measures for future MS disease activity.
Main Methods:
- Sixty-nine participants (43 MS patients, 26 healthy controls) underwent single-pulse TMS over the left primary motor cortex during EEG recording.
- Transcranial-evoked potentials (TEPs) and spectral perturbations were analyzed.
- MS patients were followed for 2 years to assess disease activity using 'No Evidence of Disease Activity-3' criteria.
Main Results:
- MS patients exhibited significantly reduced P60 amplitude compared to controls (P=0.0491).
- A trend towards reduced gamma-band desynchronization was observed in MS patients, correlating inversely with fine-motor function (P=0.001).
- Lower P15 amplitude showed a trend in patients with active disease and predicted disease stability with 74.4% accuracy (P=0.023).
Conclusions:
- TMS combined with EEG effectively detects altered motor cortical network dynamics in MS.
- Reduced gamma-band desynchronization may reflect preserved network efficiency, potentially a compensatory mechanism.
- The P15-evoked potential amplitude shows potential as a predictor of MS disease activity, aiding prognosis and treatment guidance.
