Objective: Excitation/inhibition balance (EIB) is typically assessed in vivo using EEG, MEG, or magnetic resonance spectroscopy (MRS), but no established method exists to estimate EIB from functional MRI (fMRI). Given the abundance of fMRI data in multiple sclerosis (MS)—often collected as an extension of routine clinical scans—developing an fMRI-based approach could facilitate large-scale studies of EIB alterations in MS. To our knowledge, this is the first study to apply an MRI-based multimodal framework to estimate EIB from fMRI data in MS. We aimed to assess EIB both globally (across the whole brain) and within two resting-state networks commonly affected by MS: the default mode network (DMN) and the somatomotor network.Method: We employed the resting-state structural connectivity (rsSC) framework [1], integrating resting-state fMRI and diffusion-weighted imaging to infer macroscale excitation and inhibition. EIB was defined as the ratio of positive (excitatory) to negative (inhibitory) connections in a hybrid connectivity matrix. Data from 24 female MS patients and 13 healthy female controls were analyzed using the Schaefer functional atlas, with validation in the Desikan-Killiany and AAL atlases.Results: Global EIB did not differ between groups. However, MS patients showed significantly lower intra-network EIB in the DMN and somatomotor networks, with medium to large effect sizes.Conclusions: These findings reveal network-specific reductions in EIB in MS. The rsSC framework offers a promising fMRI-based tool to assess E/I balance, complementing EEG and MRS approaches.
Zin, G, Nagels, G, Van Schependom, J & Manos, T 2025, 'Network-specific Alterations In Excitation/Inhibition Balance In Multiple Sclerosis, A Multimodal MRI Approach', National Day of Biomedical Engineering, Brussels, Belgium, 5/12/25.
Zin, G., Nagels, G., Van Schependom, J., & Manos, T. (2025). Network-specific Alterations In Excitation/Inhibition Balance In Multiple Sclerosis, A Multimodal MRI Approach. Poster session presented at National Day of Biomedical Engineering, Brussels, Belgium.
@conference{cc8cd24b8e4e4c44aff6b2d2fb8b4077,
title = "Network-specific Alterations In Excitation/Inhibition Balance In Multiple Sclerosis, A Multimodal MRI Approach",
abstract = "Objective: Excitation/inhibition balance (EIB) is typically assessed in vivo using EEG, MEG, or magnetic resonance spectroscopy (MRS), but no established method exists to estimate EIB from functional MRI (fMRI). Given the abundance of fMRI data in multiple sclerosis (MS)—often collected as an extension of routine clinical scans—developing an fMRI-based approach could facilitate large-scale studies of EIB alterations in MS. To our knowledge, this is the first study to apply an MRI-based multimodal framework to estimate EIB from fMRI data in MS. We aimed to assess EIB both globally (across the whole brain) and within two resting-state networks commonly affected by MS: the default mode network (DMN) and the somatomotor network.Method: We employed the resting-state structural connectivity (rsSC) framework [1], integrating resting-state fMRI and diffusion-weighted imaging to infer macroscale excitation and inhibition. EIB was defined as the ratio of positive (excitatory) to negative (inhibitory) connections in a hybrid connectivity matrix. Data from 24 female MS patients and 13 healthy female controls were analyzed using the Schaefer functional atlas, with validation in the Desikan-Killiany and AAL atlases.Results: Global EIB did not differ between groups. However, MS patients showed significantly lower intra-network EIB in the DMN and somatomotor networks, with medium to large effect sizes.Conclusions: These findings reveal network-specific reductions in EIB in MS. The rsSC framework offers a promising fMRI-based tool to assess E/I balance, complementing EEG and MRS approaches.",
keywords = "Excitation Inhibition balance, functional MRI, Multiple Sclerosis, resting-state structural connectivity",
author = "Gaia Zin and Guy Nagels and {Van Schependom}, Jeroen and Manos, {Thanos (Athanasios)}",
year = "2025",
month = oct,
day = "5",
language = "English",
note = "National Day of Biomedical Engineering ; Conference date: 05-12-2025",
}