scholarly journals Altered connectivity patterns among resting state networks in patients with ischemic white matter lesions

2017 ◽  
Vol 12 (5) ◽  
pp. 1239-1250 ◽  
Author(s):  
Ju-Rong Ding ◽  
Xin Ding ◽  
Bo Hua ◽  
Xingzhong Xiong ◽  
Yuqiao Wen ◽  
...  
2022 ◽  
Author(s):  
Victor Nozais ◽  
Stephanie J Forkel ◽  
Laurent Petit ◽  
Michel Thiebaut de Schotten ◽  
marc joliot

Over the past two decades, the study of resting-state functional magnetic resonance imaging (fMRI) has revealed the existence of multiple brain areas displaying synchronous functional blood oxygen level-dependent signals (BOLD) - resting-state networks (RSNs). The variation in functional connectivity between the different areas of a resting-state network or between multiple networks, have been extensively studied and linked to cognitive states and pathologies. However, the white matter connections supporting each network remain only partially described. In this work, we developed a data-driven method to systematically map the white and grey matter contributing to resting-state networks. Using the Human Connectome Project, we generated an atlas of 30 resting-state networks, each with two maps: white matter and grey matter. By integrating structural and functional neuroimaging data, this method builds an atlas that unlocks the joint anatomical exploration of white and grey matter to resting-state networks. The method also allows highlighting the overlap between networks, which revealed that most (89%) of the brain's white matter is shared amongst multiple networks, with 16% shared by at least 7 resting-state networks. These overlaps, especially the existence of regions shared by numerous networks, suggest that white matter lesions in these areas might strongly impact the correlations and the communication within resting-state networks. We provide an open-source software to explore the joint contribution of white and grey matter to RSNs and facilitate the study of the impact of white matter damage on RSNs.


2021 ◽  
Author(s):  
Dániel Veréb ◽  
Márton Attila Kovács ◽  
Krisztián Kocsis ◽  
Eszter Tóth ◽  
Bence Bozsik ◽  
...  

AbstractLaterality patterns of resting state networks (RSN) change in various neuropsychiatric conditions. Multiple sclerosis (MS) causes neuro-cognitive symptoms involving dysfunctional large-scale brain networks. Yet, whether healthy laterality patterns of RSNs are maintained in MS and whether altered laterality patterns explain disease symptoms has not been explicitly investigated. We analysed functional MRI and diffusion tensor imaging data from 24 relapsing–remitting MS patients and 25 healthy participants. We performed group-level independent component analysis and used dual regression to estimate individual versions of well-established RSNs. Voxelwise laterality indices were calculated for each RSN. Group differences were assessed via a general linear model-based approach. The relationship between functional laterality and white matter microstructural asymmetry was assessed using Tract-Based Spatial Statistics. Spearman’s correlation was calculated between laterality indices and Brief International Cognitive Assessment for Multiple Sclerosis scores. Functional laterality of the dorsal attention network showed a significant leftward shift in the MS group in the posterior intraparietal sulcus (p < 0.033). Default-mode network laterality showed a significant leftward shift in the MS group in the angular gyrus (p < 0.005). Diminished dorsal attention network laterality was associated with increased fractional anisotropy asymmetry in the superior longitudinal fasciculus (p < 0.02). In the default-mode network, leftward laterality of the angular gyrus was associated with higher BVMT-R scores (R = − 0.52, p < 0.023). Our results confirm previous descriptions of RSN dysfunction in relapsing–remitting MS and show that altered functional connectivity lateralisation patterns of RSNs might contibute to cognitive performance and structural remodellation even in patients with mild clinical symptoms.


2021 ◽  
Author(s):  
Tanja Veselinović ◽  
Ravichandran Rajkumar ◽  
Laura Amort ◽  
Jessica Juenger ◽  
N. Jon Shah ◽  
...  

2014 ◽  
Vol 34 (7) ◽  
pp. 1091-1095 ◽  
Author(s):  
Alexander Schaefer ◽  
Eva M Quinque ◽  
Judy A Kipping ◽  
Katrin Arélin ◽  
Elisabeth Roggenhofer ◽  
...  

Cerebral small vessel disease, mainly characterized by white matter lesions and lacunes, has a high clinical impact as it leads to vascular dementia. Recent studies have shown that this disease impairs frontoparietal networks. Here, we apply resting-state magnetic resonance imaging and data-driven whole-brain imaging analysis methods (eigenvector centrality) to investigate changes of the functional connectome in early small vessel disease. We show reduced connectivity in frontoparietal networks, whereas connectivity increases in the cerebellum. These functional changes are closely related to white matter lesions and typical neuropsychological deficits associated with small vessel disease.


Author(s):  
Cheng‐Chih Hsiao ◽  
Nina L. Fransen ◽  
Aletta M.R. den Bosch ◽  
Kim I.M. Brandwijk ◽  
Inge Huitinga ◽  
...  

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