Regional thalamic RS FC abnormalities with different cortical regions, including the frontal lobe, sensorimotor network, precuneus, insular cortices, and cerebellum contribute to fatigue in MS. Abnormal RS FC of selected thalamo-cortical connections explains different components of fatigue.

Background: The features of functional network connectivity reorganization at the earliest stages of MS have not been investigated yet. Objective: To combine static and dynamic analysis of resting state (RS) functional connectivity (FC) to identify mechanisms of clinical dysfunction and recovery occurring in clinically isolated syndrome (CIS) patients. Methods: RS functional magnetic resonance imaging (fMRI) and clinical data were prospectively acquired from 50 CIS patients and 13 healthy controls (HC) at baseline, month 12 and month 24. Between-group differences and longitudinal evolution of network FC were analysed across 41 functionally relevant networks. Results: At follow-up, 47 patients developed MS. Disability remained stable (and relatively low). CIS and HC exhibited two recurring RS FC states (states 1 and 2, showing low and high internetwork connectivity, respectively). At baseline, patients showed reduced state 2 connectivity strength in the default-mode and cerebellar networks, and no differences in global dynamism versus HC. A selective FC reduction in networks affected by the clinical attack was also detected. At follow-up, increased state 2 connectivity strength and global connectivity dynamism was observed in patients versus HC. Conclusion: Longitudinal FC modifications occurring relatively early in the course of multiple sclerosis may represent a protective mechanism contributing to preserve clinical function over time.

In spite of the well-known importance of thalami in multiple sclerosis (MS), only limited data on whole and subregional thalamic functional connectivity (FC) changes are available. Using diffusion tensor imaging, we performed a structural connectivity based thalamic parcellation and investigated subregional thalamic resting-state (RS) FC alterations and their relationship with clinical/cognitive measures in MS. MRI data from a reference set of healthy controls (HC) were used to parcellate the thalami into five subregions, according to their structural connectivity. For each thalamic subregion, a seed-based RS FC analysis was performed in 187 MS patients and 94 HC. Correlations between thalamic RS FC and clinical/cognitive variables were assessed. Compared to HC, MS patients showed increased intra- and inter-thalamic RS FC for almost all thalamic subregions, and increased RS FC between all thalamic subregions and the left insula. Frontal and motor thalamic subregions also showed reduced RS FC with the caudate nucleus. For the temporal thalamic subregion, we observed reduced RS FC with the ipsilateral thalamus, anterior and middle cingulate cortex, and cerebellum. Compared to cognitively preserved, cognitively impaired MS patients had higher thalamic RS FC with several temporal areas. In MS patients, lower RS FC between thalamic subregions and the caudate and cingulate cortex correlated with worse motor performance, whereas higher RS FC with the insula correlated with better motor performance. The main thalamic subregions have different RS-FC abnormalities in MS patients. Increased thalamic RS FC with the insula may have a compensatory role, whereas increased RS FC with temporal areas, observed in patients with cognitive impairment may reflect maladaptive mechanisms. Hum Brain Mapp 38:6005-6018, 2017. © 2017 Wiley Periodicals, Inc.

Functional magnetic resonance imaging (fMRI) at resting state (RS) has been widely used to characterize the main brain networks. Functional connectivity (FC) has been mostly assessed assuming that FC is static across the whole fMRI examination. However, FC is highly variable at a very fast time-scale, as demonstrated by neurophysiological techniques. Time-varying functional connectivity (TVC) is a novel approach that allows capturing reoccurring patterns of interaction among functional brain networks. Aim of this review is to provide a description of the methods currently used to assess TVC on RS fMRI data, and to summarize the main results of studies applying TVC in healthy controls and patients with multiple sclerosis (MS). An overview of the main results obtained in neurodegenerative and psychiatric conditions is also provided. The most popular TVC approach is based on the so-called “sliding windows,” in which the RS fMRI acquisition is divided in small temporal segments (windows). A window of fixed length is shifted over RS fMRI time courses, and data within each window are used to calculate FC and its variability over time. Sliding windows can be combined with clustering techniques to identify recurring FC states or used to assess global TVC properties of large-scale functional networks or specific brain regions. TVC studies have used heterogeneous methodologies so far. Despite this, similar results have been obtained across investigations. In healthy subjects, the default-mode network (DMN) exhibited the highest degree of connectivity dynamism. In MS patients, abnormal global TVC properties and TVC strengths were found mainly in sensorimotor, DMN and salience networks, and were associated with more severe structural MRI damage and with more severe physical and cognitive disability. Conversely, abnormal TVC measures of the temporal network were correlated with better cognitive performances and less severe fatigue. In patients with neurodegenerative and psychiatric conditions, TVC abnormalities of the DMN, attention and executive networks were associated to more severe clinical manifestations. TVC helps to provide novel insights into fundamental properties of functional networks, and improves the understanding of brain reorganization mechanisms. Future technical advances might help to clarify TVC association with disease prognosis and response to treatment.