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Neurology. 2012 Oct 2;79(14):1449-57. doi: 10.1212/WNL.0b013e31826d5f10. Epub 2012 Sep 5.

Large-scale neuronal network dysfunction in relapsing-remitting multiple sclerosis.

Author information

1
Department of Neurology, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy.

Abstract

OBJECTIVES:

Given that multiple sclerosis (MS) hits diffusely the brain hemispheres, we hypothesized that this should result in a distributed pattern of functional connectivity (FC) abnormalities. To this aim, we assessed, using resting-state (RS) fMRI, intrinsic FC and functional network connectivity (FNC) of brain large-scale neuronal networks from 85 patients with relapsing-remitting MS (RRMS) and 40 matched controls.

METHODS:

Independent component analysis was used to analyze RS fMRI data. Intrinsic FC of each cluster of each RS network (RSN) was compared between controls and patients (analysis of variance adjusted for age, gender, and gray matter volume). The FNC toolbox was used to assess interactions among RSNs.

RESULTS:

Compared to controls, patients with RRMS experienced a decreased RS FC in regions of the salience (SN), executive control (ECN), working memory (WMN), default mode (DMN), sensorimotor, and visual networks. They also had an increased RS FC in regions of the ECN and auditory RSN. Decreased RS FC was significantly correlated with disability and T2 lesion volumes. In patients with RRMS, when compared to controls, FNC analysis showed that the ECN had an increased connectivity with the SN and a decreased connectivity with the DMN. An abnormal connectivity between the WMNs and sensory networks was also found.

CONCLUSIONS:

Functional abnormalities within and between large-scale neuronal networks occur in patients with RRMS and are related to the extent of T2 lesions and the severity of disability. Longitudinal studies should ascertain whether such functional abnormalities confer a systematic vulnerability to disease progression or, conversely, protect against the onset of clinical deficits.

PMID:
22955126
DOI:
10.1212/WNL.0b013e31826d5f10
[Indexed for MEDLINE]
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