Explaining the heterogeneity of functional connectivity findings in multiple sclerosis: An empirically informed modeling study.

To understand the heterogeneity of functional connectivity results reported in the literature, we analyzed the separate effects of grey and white matter damage on functional connectivity and networks in multiple sclerosis. For this, we employed a biophysical thalamo-cortical model consisting of interconnected cortical and thalamic neuronal populations, informed and amended by empirical diffusion MRI tractography data, to simulate functional data that mimic neurophysiological signals. Grey matter degeneration was simulated by decreasing within population connections and white matter degeneration by lowering between population connections, based on lesion predilection sites in multiple sclerosis. For all simulations, functional connectivity and functional network organization are quantified by phase synchronization and network integration, respectively. Modeling results showed that both cortical and thalamic grey matter damage induced a global increase in functional connectivity, whereas white matter damage induced an initially increased connectivity followed by a global decrease. Both white and especially grey matter damage, however, induced a decrease in network integration. These empirically informed simulations show that specific topology and timing of structural damage are nontrivial aspects in explaining functional abnormalities in MS. Insufficient attention to these aspects likely explains contradictory findings in multiple sclerosis functional imaging studies so far.

High-resolution T1-relaxation time mapping displays subtle, clinically relevant, gray matter damage in long-standing multiple sclerosis.

BACKGROUND: Gray matter (GM) pathology has high clinical relevance in multiple sclerosis (MS), but conventional magnetic resonance imaging (MRI) is insufficiently sensitive to visualize the rather subtle damage. OBJECTIVE: To investigate whether high spatial resolution T1-relaxation time (T1-RT) measurements can detect changes in the normal-appearing GM of patients with long-standing MS and whether these changes are associated with physical and cognitive impairment. METHODS: High spatial resolution (1.05 × 1.05 × 1.2 mm(3)) T1-RT measurements were performed at 3 T in 156 long-standing MS patients and 54 healthy controls. T1-RT histogram parameters in several regions were analyzed to investigate group differences. Stepwise linear regression analyses were used to assess the relation of T1-RT with physical and cognitive impairment. RESULTS: In both thalamus and cortex, T1-RT histogram skewness was higher in patients than controls. In the cortex, this was driven by the frontal and temporal lobes. No differences were found in other GM histogram parameters. Cortical skewness, thalamus volume, and average white matter (WM) lesion T1-RT emerged as the strongest predictors for cognitive performance (adjusted R(2) = 0.39). CONCLUSION: Subtle GM damage was present in the cortex and thalamus of MS patients, as indicated by increased T1-RT skewness. Increased cortical skewness emerged as an independent predictor of cognitive dysfunction.