Literature DB >> 30940453

White matter lesion loads associated with dynamic functional connectivity within attention network in patients with relapsing-remitting multiple sclerosis.

Muhua Huang1, Fuqing Zhou2, Lin Wu1, Bo Wang1, Linghong Guo1, Yanlin Zhao1, Hui Wan3, Fangjun Li3, Xianjun Zeng1, Honghan Gong1.   

Abstract

Using time-variant of blood oxygenation level dependent (BOLD) signal to investigate the temporal changes in functional connectivity (FC) between key nodes may shed light on the dynamic characteristics of network. Twenty-two relapsing-remitting multiple sclerosis (RRMS) and 22 well-matched healthy control subjects (HCs) participated in this study. Previously validated key nodes of attention network seeds were defined as spherical regions of interests (ROIs); then, we captured the pattern of dFC using sliding window correlation of ROIs in the RRMS and HCs during rest. Furthermore, correlation analysis between altered dFC of paired-ROIs with clinical measures in RRMS were performed. Compared with the HCs, the RRMS showed: a certain specificity transient pattern of FC of attention network at time window levels, including decreased dFC within dorsal attention network [connections of left intraparietal sulcus (LIPS)-right intraparietal sulcus (RIPS), LIPS-right frontal eye field (RFEF) and left frontal eye field (LFEF)-RIPS] and ventral attention network [connection of right ventral frontal cortex (RVFC)-right temporal parietal junction (RTPJ)], increased dFC between dorsal and ventral attention network (connections of LIPS-RTPJ and LIPS-RVFC). Secondary analysis indicated that the dFC coefficients of the connections of LIPS-RIPS (r = -0.467, P = 0.023) and RVFC-RTPJ (r = -0.452, P = 0.043) were significant negative correlated with the total white matter lesion load. In conclusion, we found that the instantaneous configuration pattern of FC in attention network of RRMS are relate to lesions loads.
Copyright © 2019 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Attention network; Dynamic functional connectivity; Multiple sclerosis; Resting-state functional MRI

Mesh:

Year:  2019        PMID: 30940453     DOI: 10.1016/j.jocn.2019.03.034

Source DB:  PubMed          Journal:  J Clin Neurosci        ISSN: 0967-5868            Impact factor:   1.961


  5 in total

1.  Dynamic Functional Connectivity Better Predicts Disability Than Structural and Static Functional Connectivity in People With Multiple Sclerosis.

Authors:  Ceren Tozlu; Keith Jamison; Susan A Gauthier; Amy Kuceyeski
Journal:  Front Neurosci       Date:  2021-12-13       Impact factor: 4.677

2.  Multi-dynamic modelling reveals strongly time-varying resting fMRI correlations.

Authors:  Usama Pervaiz; Diego Vidaurre; Chetan Gohil; Stephen M Smith; Mark W Woolrich
Journal:  Med Image Anal       Date:  2022-01-29       Impact factor: 8.545

3.  Diffusion Tensor Imaging Revealed Microstructural Changes in Normal-Appearing White Matter Regions in Relapsing-Remitting Multiple Sclerosis.

Authors:  Jianfeng Bao; Hui Tu; Yijia Li; Jubao Sun; Zhigang Hu; Fengshou Zhang; Jinghua Li
Journal:  Front Neurosci       Date:  2022-03-02       Impact factor: 4.677

4.  Distributed causality in resting-state network connectivity in the acute and remitting phases of RRMS.

Authors:  Lin Wu; Muhua Huang; Fuqing Zhou; Xianjun Zeng; Honghan Gong
Journal:  BMC Neurosci       Date:  2020-09-15       Impact factor: 3.288

5.  Longitudinal Network Changes and Conversion to Cognitive Impairment in Multiple Sclerosis.

Authors:  Marijn Huiskamp; Anand J C Eijlers; Tommy A A Broeders; Jasmin Pasteuning; Iris Dekker; Bernard M J Uitdehaag; Frederik Barkhof; Alle-Meije Wink; Jeroen J G Geurts; Hanneke E Hulst; Menno M Schoonheim
Journal:  Neurology       Date:  2021-06-07       Impact factor: 9.910

  5 in total

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