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Structural disconnection is responsible for increased functional connectivity in multiple sclerosis.

ABSTRACT: Increased synchrony within neuroanatomical networks is often observed in neurophysiologic studies of human brain disease. Most often, this phenomenon is ascribed to a compensatory process in the face of injury, though evidence supporting such accounts is limited. Given the known dependence of resting-state functional connectivity (rsFC) on underlying structural connectivity (SC), we examine an alternative hypothesis: that topographical changes in SC, specifically particular patterns of disconnection, contribute to increased network rsFC. We obtain measures of rsFC using fMRI and SC using probabilistic tractography in 50 healthy and 28 multiple sclerosis subjects. Using a computational model of neuronal dynamics, we simulate BOLD using healthy subject SC to couple regions. We find that altering the model by introducing structural disconnection patterns observed in those multiple sclerosis subjects with high network rsFC generates simulations with high rsFC as well, suggesting that disconnection itself plays a role in producing high network functional connectivity. We then examine SC data in individuals. In multiple sclerosis subjects with high network rsFC, we find a preferential disconnection between the relevant network and wider system. We examine the significance of such network isolation by introducing random disconnection into the model. As observed empirically, simulated network rsFC increases with removal of connections bridging a community with the remainder of the brain. We thus show that structural disconnection known to occur in multiple sclerosis contributes to network rsFC changes in multiple sclerosis and further that community isolation is responsible for elevated network functional connectivity.

SUBMITTER: Patel KR

PROVIDER: S-EPMC5970033 | biostudies-literature | 2018 Jun

REPOSITORIES: biostudies-literature

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Structural disconnection is responsible for increased functional connectivity in multiple sclerosis.

Patel Kevin R KR Tobyne Sean S Porter Daria D Bireley John Daniel JD Smith Victoria V Klawiter Eric E

Brain structure & function 20180216 5

Increased synchrony within neuroanatomical networks is often observed in neurophysiologic studies of human brain disease. Most often, this phenomenon is ascribed to a compensatory process in the face of injury, though evidence supporting such accounts is limited. Given the known dependence of resting-state functional connectivity (rsFC) on underlying structural connectivity (SC), we examine an alternative hypothesis: that topographical changes in SC, specifically particular patterns of disconnec ...[more]

PMID: 29453522

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Project description:BackgroundReduced white matter (WM) integrity is a fundamental aspect of pediatric multiple sclerosis (MS), though relations to resting-state functional MRI (fMRI) connectivity remain unknown. The objective of this study was to relate diffusion-tensor imaging (DTI) measures of WM microstructural integrity to resting-state network (RSN) functional connectivity in pediatric-onset MS to test the hypothesis that abnormalities in RSN reflects changes in structural integrity.MethodsThis study enrolled 19 patients with pediatric-onset MS (mean age = 19, range 13-24 years, 14 female, mean disease duration = 65 months, mean age of disease onset = 13 years) and 16 age- and sex-matched healthy controls (HC). All subjects underwent 3.0T anatomical and functional MRI which included DTI and resting-state acquisitions. DTI processing was performed using Tract-Based Spatial Statistics (TBSS). RSNs were identified using Independent Components Analysis, and a dual regression technique was used to detect between-group differences in the functional connectivity of RSNs. Correlations were investigated between DTI measures and RSN connectivity.ResultsLower fractional anisotropy (FA) was observed in the pediatric-onset MS group compared to HC group within the entire WM skeleton, and particularly the corpus callosum, posterior thalamic radiation, corona radiata and sagittal stratum (all p < .01, corrected). Relative to HCs, MS patients showed higher functional connectivity involving the anterior cingulate cortex and right precuneus of the default-mode network, as well as involving the anterior cingulate cortex and left middle frontal gyrus of the frontoparietal network (all p < .005 uncorrected, k?30 voxels). Higher functional connectivity of the right precuneus within the default-mode network was associated with lower FA of the entire WM skeleton (r = -.525, p = .02), genu of the corpus callosum (r = -.553, p = .014), and left (r = -.467, p = .044) and right (r = -.615, p = .005) sagittal stratum.ConclusionsLoss of WM microstructural integrity is associated with increased resting-state functional connectivity in pediatric MS, which may reflect a diffuse and potentially compensatory activation early in MS.

Project description:Background: Advanced imaging techniques such as diffusion and functional MRI can be used to identify pathology-related changes to the brain's structural and functional connectivity (SC and FC) networks and mapping of these changes to disability and compensatory mechanisms in people with multiple sclerosis (pwMS). No study to date performed a comparison study to investigate which connectivity type (SC, static or dynamic FC) better distinguishes healthy controls (HC) from pwMS and/or classifies pwMS by disability status. Aims: We aim to compare the performance of SC, static FC, and dynamic FC (dFC) in classifying (a) HC vs. pwMS and (b) pwMS who have no disability vs. with disability. The secondary objective of the study is to identify which brain regions' connectome measures contribute most to the classification tasks. Materials and Methods: One hundred pwMS and 19 HC were included. Expanded Disability Status Scale (EDSS) was used to assess disability, where 67 pwMS who had EDSS<2 were considered as not having disability. Diffusion and resting-state functional MRI were used to compute the SC and FC matrices, respectively. Logistic regression with ridge regularization was performed, where the models included demographics/clinical information and either pairwise entries or regional summaries from one of the following matrices: SC, FC, and dFC. The performance of the models was assessed using the area under the receiver operating curve (AUC). Results: In classifying HC vs. pwMS, the regional SC model significantly outperformed others with a median AUC of 0.89 (p <0.05). In classifying pwMS by disability status, the regional dFC and dFC metrics models significantly outperformed others with a median AUC of 0.65 and 0.61 (p < 0.05). Regional SC in the dorsal attention, subcortical and cerebellar networks were the most important variables in the HC vs. pwMS classification task. Increased regional dFC in dorsal attention and visual networks and decreased regional dFC in frontoparietal and cerebellar networks in certain dFC states was associated with being in the group of pwMS with evidence of disability. Discussion: Damage to SCs is a hallmark of MS and, unsurprisingly, the most accurate connectomic measure in classifying patients and controls. On the other hand, dynamic FC metrics were most important for determining disability level in pwMS, and could represent functional compensation in response to white matter pathology in pwMS.

Project description:Background and purposeLittle is known about the interactions between the default mode network (DMN) subregions in relapsing-remitting multiple sclerosis (RRMS). This study used diffusion tensor imaging (DTI) and resting-state functional MRI (rs-fMRI) to examine alterations of long white matter tracts in paired DMN subregions and their functional connectivity in RRMS patients.MethodsTwenty-four RRMS patients and 24 healthy subjects participated in this study. The fiber connections derived from DTI tractography and the temporal correlation coefficient derived from rs-fMRI were combined to examine the inter-subregion structural-functional connectivity (SC-FC) within the DMN and its correlations with clinical markers.ResultsCompared with healthy subjects, the RRMS patients showed the following: 1) significantly decreased SC and increased FC in the pair-wise subregions; 2) two significant correlations in SC-FC coupling patterns, including the positive correlation between slightly increased FC value and long white matter tract damage in the PCC/PCUN-MPFC connection, and the negative correlations between significantly increased FC values and long white matter tract damage in the PCC/PCUN-bilateral mTL connections; 3) SC alterations [log(N track) of the PCC/PCUN-left IPL, RD value of the MPFC-left IPL, FA value of the PCC/PCUN-left mTL connections] correlated with EDSS, increases in the RD value of MPFC-left IPL connection was positively correlated to the MFIS; and decreases in the FA value of PCC/PCUN-right IPL connection was negatively correlated with the PASAT; 4) decreased SC (FA value of the MPFC-left IPL, track volume of the PCC/PCUN-MPFC, and log(N track) of PCC/PCUN-left mTL connections) was positively correlated with brain atrophy.ConclusionsIn the connections of paired DMN subregions, we observed decreased SC and increased FC in RRMS patients. The relationship between MS-related structural abnormalities and clinical markers suggests that the disruption of this long-distance "inter-subregion" connectivity (white matter) may significantly impact the integrity of the network's function.

Project description:Effective learning from performance feedback is vital for adaptive behavior regulation necessary for successful cognitive performance. Yet, how this learning operates in clinical groups that experience cognitive dysfunction is not well understood. Multiple sclerosis (MS) is an autoimmune, degenerative disease of the central nervous system characterized by physical and cognitive dysfunction. A highly prevalent impairment in MS is cognitive fatigue (CF). CF is associated with altered functioning within cortico-striatal regions that also facilitate feedback-based learning in neurotypical (NT) individuals. Despite this cortico-striatal overlap, research about feedback-based learning in MS, its associated neural underpinnings, and its sensitivity to CF, are all lacking. The present study investigated feedback-based learning ability in MS, as well as associated cortico-striatal function and connectivity. MS and NT participants completed a functional magnetic resonance imaging (fMRI) paired-word association task during which they received trial-by-trial monetary, non-monetary, and uninformative performance feedback. Despite reporting greater CF throughout the task, MS participants displayed comparable task performance to NTs, suggesting preserved feedback-based learning ability in the MS group. Both groups recruited the ventral striatum (VS), caudate nucleus, and ventromedial prefrontal cortex in response to the receipt of performance feedback, suggesting that people with MS also recruit cortico-striatal regions during feedback-based learning. However, compared to NT participants, MS participants also displayed stronger functional connectivity between the VS and task-relevant regions, including the left angular gyrus and right superior temporal gyrus, in response to feedback receipt. Results indicate that CF may not interfere with feedback-based learning in MS. Nonetheless, people with MS may recruit alternative connections with the striatum to assist with this form of learning. These findings have implications for cognitive rehabilitation treatments that incorporate performance feedback to remediate cognitive dysfunction in clinical populations.

Project description:BackgroundDepression, a condition commonly comorbid with multiple sclerosis (MS), is associated more generally with elevated inflammatory markers and hippocampal pathology. We hypothesized that neuroinflammation in the hippocampus is responsible for depression associated with MS. We characterized the relationship between depressive symptoms and hippocampal microglial activation in patients with MS using the 18-kDa translocator protein radioligand [(18)F]PBR111. To evaluate pathophysiologic mechanisms, we explored the relationships between hippocampal neuroinflammation, depressive symptoms, and hippocampal functional connectivities defined by resting-state functional magnetic resonance imaging.MethodsThe Beck Depression Inventory (BDI) was administered to 11 patients with MS and 22 healthy control subjects before scanning with positron emission tomography and functional magnetic resonance imaging. We tested for higher [(18)F]PBR111 uptake in the hippocampus of patients with MS relative to healthy control subjects and examined the correlations between [(18)F]PBR111 uptake, BDI scores, and hippocampal functional connectivities in the patients with MS.ResultsPatients with MS had an increased hippocampal [(18)F]PBR111 distribution volume ratio relative to healthy control subjects (p = .024), and the hippocampal distribution volume ratio was strongly correlated with the BDI score in patients with MS (r = .86, p = .006). Hippocampal functional connectivities to the subgenual cingulate and prefrontal and parietal regions correlated with BDI scores and [(18)F]PBR111 distribution volume ratio.ConclusionsOur results provide evidence that hippocampal microglial activation in MS impairs the brain functional connectivities in regions contributing to maintenance of a normal affective state. Our results suggest a rationale for the responsiveness of depression in some patients with MS to effective control of brain neuroinflammation. Our findings also lend support to further investigation of the role of inflammatory processes in the pathogenesis of depression more generally.

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Structural disconnection is responsible for increased functional connectivity in multiple sclerosis.

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Structural disconnection is responsible for increased functional connectivity in multiple sclerosis.

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