Increased default-mode network centrality in cognitively impaired multiple sclerosis patients

Eijlers, A. J. C.; Meijer, Kim; Wassenaar, Thomas; Steenwijk, Martijn D.; Uitdehaag, Bernard M. J.; Barkhof, Frederik; Wink, Alle Meije; Geurts, Jeroen J. G.; Schoonheim, Menno M.

doi:10.1212/wnl.0000000000003689

Cited by 94 publications

(120 citation statements)

References 37 publications

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“…To better visualize areas with most pronounced cortical thinning, we lowered the statistical threshold to a p value of < 0.05 family-wise error corrected at the voxel level revealing eight areas: bilateral parahippocampal gyrus (1 and 2), left superior frontal gyrus (3), rostral middle frontal gyrus (4), left middle superior temporal gyrus including transverse temporal gyrus (5), right precentral gyrus (6), right middle temporal gyrus (7), and right supramarginal gyrus (8).…”

Section: Voxel-wise and Surface-based Analysesmentioning

confidence: 99%

“…One of the earliest magnetic resonance imaging (MRI) studies on CI in MS [2] reported a strong relationship between CI and white matter lesions (WML) compatible with the classic idea of a disconnection syndrome [3]. In later MRI studies, relations of CI to deep and cortical grey matter (GM) atrophy were reported [4][5][6][7][8][9][10][11]. When we, to the best of our knowledge, reviewed the ten structural brain MRI studies on CI in MS, with the highest numbers of CI patients included [4][5][6][7][8][9][10][11][12][13], we observed inconsistent results with regard to the contribution of WML load and GM atrophy to CI in MS.…”

Section: Introductionmentioning

confidence: 99%

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Cognitive impairment in early MS: contribution of white matter lesions, deep grey matter atrophy, and cortical atrophy

et al. 2020

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Background Cognitive impairment (CI) is a frequent and debilitating symptom in MS. To better understand the neural bases of CI in MS, this magnetic resonance imaging (MRI) study aimed to identify and quantify related structural brain changes and to investigate their relation to each other. Methods We studied 51 patients with CI and 391 patients with cognitive preservation (CP). We analyzed three-dimensional T1-weighted and FLAIR scans at 3 Tesla. We determined mean cortical thickness as well as volumes of cortical grey matter (GM), deep GM including thalamus, cerebellar cortex, white matter, corpus callosum, and white matter lesions (WML). We also analyzed GM across the whole brain by voxel-wise and surface-based techniques. Results Mean disease duration was 5 years. Comparing MS patients with CI and CP, we found higher volumes of WML, lower volumes of deep and cortical GM structures, and lower volumes of the corpus callosum (all corrected p values < 0.05). Effect sizes were largest for WML and thalamic volume (standardized ß values 0.25 and − 0.25). By logistic regression analysis including both WML and thalamic volume, we found a significant effect only for WML volume. Inclusion of the interaction term of WML and thalamic volume increased the model fit and revealed a highly significant interaction of WML and thalamic volume. Moreover, voxel-wise and surface-based comparisons of MS patients with CI and CP showed regional atrophy of both deep and cortical GM independent of WML volume and overall disability, but effect sizes were lower. Conclusion Although several mechanisms contribute to CI already in the early stage of MS, WML seem to be the main driver with thalamic atrophy primarily intensifying this effect.

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Section: Voxel-wise and Surface-based Analysesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Cognitive impairment in early MS: contribution of white matter lesions, deep grey matter atrophy, and cortical atrophy

et al. 2020

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“…Increased voxel-wise DC in a brain region indicates an elevated degree of its global connectivity, and decreased voxelwise DC in a brain region suggests a reduced degree of its global connectivity. Voxel-wise DC has been applied to reveal the abnormal brain networks in various types of neurological or psychiatric diseases (16)(17)(18)(19)(20)(21)(22). This method has also been used to compare the brain network features of different psychiatric diseases with potentially similar neural pathology, such as autism and attention-deficit hyperactivity disorder (23), or to examine the brain-network difference between the subtypes of a disease such as the Parkinson's disease patients with depression and those without depression (24).…”

Section: Introductionmentioning

confidence: 99%

Abnormal Voxel-Wise Degree Centrality in Patients With Late-Life Depression: A Resting-State Functional Magnetic Resonance Imaging Study

Gong

et al. 2020

Front. Psychiatry

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Objectives: Late-life depression (LLD) has negative impacts on somatic, emotional and cognitive domains of the lives of patients. Elucidating the abnormality in the brain networks of LLD patients could help to strengthen the understanding of LLD pathophysiology, however, the studies exploring the spontaneous brain activity in LLD during the resting state remain limited. This study aimed at identifying the voxel-level whole-brain functional connectivity changes in LLD patients. Methods: Fifty patients with late-life depression (LLD) and 33 healthy controls were recruited. All participants underwent a resting-state functional magnetic resonance imaging scan to assess the voxel-wise degree centrality (DC) changes in the patients. Furthermore, DC was compared between two patient subgroups, the late-onset depression (LOD) and the early-onset depression (EOD). Results: Compared with the healthy controls, LLD patients showed increased DC in the inferior parietal lobule, parahippocampal gyrus, brainstem and cerebellum (p < 0.05, AlphaSim-corrected). LLD patients also showed decreased DC in the somatosensory and motor cortices and cerebellum (p < 0.05, AlphaSim-corrected). Compared with EOD patients, LOD patients showed increased centrality in the superior and middle temporal gyrus and decreased centrality in the occipital region (p < 0.05, AlphaSim-corrected). No significant correlation was found between the DC value and the symptom severity or disease duration in the patients after the correction for multiple comparisons. Conclusions: These findings indicate that the intrinsic abnormality of network centrality exists in a wide range of brain areas in LLD patients. LOD patients differ with EOD patients

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“…Despite this, due to computational limitations only few studies have explored FC at the voxel resolution with direct assessment of the FC matrix [11][12][13][14][15][16][17]. Others [18,19] circumvented the problem by investigating eigenvector centrality of functional networks, with a fast computation method introduced by [20] that avoids the explicit calculation of the FC matrix.…”

Section: Introductionmentioning

confidence: 99%

Fine-scale patterns driving dynamic functional connectivity provide meaningful brain parcellations

Preti

Ville

2017

2017 25th European Signal Processing Conference (EUSIPCO)

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Dynamic functional connectivity (dFC) derived from restingstate functional magnetic resonance imaging (fMRI) allows identifying large-scale functional brain networks based on spontaneous activity and their temporal reconfigurations. Due to limited memory and computational resources, these pairwise measures are typically computed for a set of brain regions from a pre-defined brain atlas, which choice is nontrivial and might influence results. Here, we first leverage the availability of dynamic information and new computational methods to retrieve dFC at the finest voxel level in terms of dominant patterns of fluctuations, and, second, we demonstrate that this new representation is informative to derive meaningful brain parcellations that capture both long-range interactions and fine-scale local organization. We analyzed resting-state fMRI of 54 healthy participants from the Human Connectome Project. For each position of a temporal window, we determined eigenvector centrality of the windowed fMRI data at the voxel level. These were then concatenated across time and subjects and clustered into the most representative dominant patterns (RDPs). Each voxel was then labeled according to a binary code indicating positive or negative contribution to each of the RDPs. We obtained a 36-label parcellation displaying long-range interactions with remarkable hemispherical symmetry. By separating contiguous regions, a finer-scale parcellation of 448 areas was also retrieved, showing consistency with known connectivity of cortical/subcortical structures including thalamus. Our contribution bridges the gap between voxel-based approaches and graph theoretical analysis.Index Terms-functional MRI, dynamic functional connectivity, brain networks, fine-scale brain parcellation.

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Increased default-mode network centrality in cognitively impaired multiple sclerosis patients

Abstract: Patients with MS with cognitive impairment show hallmark alterations in functional network hierarchy with increased relative importance (centrality) of the default-mode network.

Cited by 94 publications

References 37 publications

Cognitive impairment in early MS: contribution of white matter lesions, deep grey matter atrophy, and cortical atrophy

Cognitive impairment in early MS: contribution of white matter lesions, deep grey matter atrophy, and cortical atrophy

Abnormal Voxel-Wise Degree Centrality in Patients With Late-Life Depression: A Resting-State Functional Magnetic Resonance Imaging Study

Fine-scale patterns driving dynamic functional connectivity provide meaningful brain parcellations

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