Changes in brain functional connectivity patterns are driven by an individual lesion in MS: a resting-state fMRI study

Diffuse inflammation in multiple sclerosis (MS) extends beyond focal lesion sites, affecting interconnected regions; however, little is known about the impact of an individual lesion affecting major white matter (WM) pathways on brain functional connectivity (FC). Here, we longitudinally assessed the effects of acute and chronic lesions on FC in relapsing-remitting MS (RRMS) patients using resting-state fMRI. 45 MRI data sets from 9 RRMS patients were recorded using 3T MR scanner over 5 time points at 8 week intervals. Patients were divided into two groups based on the presence (n = 5; MS+) and absence (n = 4; MS-) of a lesion at a predilection site for MS. While FC levels were found not to fluctuate significantly in the overall patient group, the MS+ patient group showed increased FC in the contralateral cuneus and precuneus and in the ipsilateral precuneus (p < 0.01, corrected). This can be interpreted as the recruitment of intact cortical regions to compensate for tissue damage. During the study, one patient developed an acute WM lesion in the left posterior periventricular space. A marked increase in FC in the right pre-, post-central gyrus, right superior frontal gyrus, the left cuneus, the vermis and the posterior and anterior lobes of the cerebellum was noted following the clinical relapse, which gradually decreased in subsequent follow-ups, suggesting short-term functional reorganization during the acute phase. This strongly suggests that the lesion-related network changes observed in patients with chronic lesions occur as a result of reorganization processes following the initial appearance of an acute lesion

Secondary Progressive and Relapsing Remitting Multiple Sclerosis Leads to Motor-Related Decreased Anatomical Connectivity

Multiple sclerosis (MS) damages central white matter pathways which has considerable impact on disease-related disability. To identify disease-related alterations in anatomical connectivity, 34 patients (19 with relapsing remitting MS (RR-MS), 15 with secondary progressive MS (SP-MS) and 20 healthy subjects underwent diffusion magnetic resonance imaging (dMRI) of the brain. Based on the dMRI, anatomical connectivity mapping (ACM) yielded a voxel-based metric reflecting the connectivity shared between each individual voxel and all other brain voxels. To avoid biases caused by inter-individual brain-shape differences, they were estimated in a spatially normalized space. Voxel-based statistical analyses using ACM were compared with analyses based on the localized microstructural indices of fractional anisotropy (FA). In both RR-MS and SP-MS patients, considerable portions of the motor-related white matter revealed decreases in ACM and FA when compared with healthy subjects. Patients with SP-MS exhibited reduced ACM values relative to RR-MS in the motor-related tracts, whereas there were no consistent decreases in FA between SP-MS and RR-MS patients. Regional ACM statistics exhibited moderate correlation with clinical disability as reflected by the expanded disability status scale (EDSS). The correlation between these statistics and EDSS was either similar to or stronger than the correlation between FA statistics and the EDSS. Together, the results reveal an improved relationship between ACM, the clinical phenotype, and impairment. This highlights the potential of the ACM connectivity indices to be used as a marker which can identify disease related-alterations due to MS which may not be seen using localized microstructural indices

Toward discovery science of human brain function

Although it is being successfully implemented for exploration of the genome, discovery science has eluded the functional neuroimaging community. The core challenge remains the development of common paradigms for interrogating the myriad functional systems in the brain without the constraints of a priori hypotheses. Resting-state functional MRI (R-fMRI) constitutes a candidate approach capable of addressing this challenge. Imaging the brain during rest reveals large-amplitude spontaneous low-frequency (<0.1 Hz) fluctuations in the fMRI signal that are temporally correlated across functionally related areas. Referred to as functional connectivity, these correlations yield detailed maps of complex neural systems, collectively constituting an individual's “functional connectome.” Reproducibility across datasets and individuals suggests the functional connectome has a common architecture, yet each individual's functional connectome exhibits unique features, with stable, meaningful interindividual differences in connectivity patterns and strengths. Comprehensive mapping of the functional connectome, and its subsequent exploitation to discern genetic influences and brain–behavior relationships, will require multicenter collaborative datasets. Here we initiate this endeavor by gathering R-fMRI data from 1,414 volunteers collected independently at 35 international centers. We demonstrate a universal architecture of positive and negative functional connections, as well as consistent loci of inter-individual variability. Age and sex emerged as significant determinants. These results demonstrate that independent R-fMRI datasets can be aggregated and shared. High-throughput R-fMRI can provide quantitative phenotypes for molecular genetic studies and biomarkers of developmental and pathological processes in the brain. To initiate discovery science of brain function, the 1000 Functional Connectomes Project dataset is freely accessible at www.nitrc.org/projects/fcon_1000/.National Institute of Mental Health (U.S.) (Grant R01MH083246) (Grant R01MH081218)National Institute of Drug Abuse (Grant R03DA024775) (Grant R01DA016979)Autism Speaks (Organization)National Institute of Neurological Disorders and Stroke (U.S.) (Grant (R01NS049176