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• Original Article •
Changes of positive and negative network connectivity related to hand knob area after stroke: A rs-fMRI study
ZHAN Shuang  YU Qiurong  YIN Dazhi  WANG Hewei  XU Guojun  WANG Xuefei  GUO Miao  SUN Changhui  ZHU Bing  SUN Limin  FAN Mingxia 

Cite this article as: Zhang S, Yu QR, Yin DZ, et al. Changes of positive and negative network connectivity related to hand knob area after stroke: A rs-fMRI study[J]. Chin J Magn Reson Imaging, 2021, 12(6): 44-50. DOI:10.12015/issn.1674-8034.2021.06.009.


[Abstract] Objective To explore the changes of positive and negative network connectivity related to hand knob area and their correlation with motor dysfunction after subcortical stroke. Materials andMethods Eighteen unilateral subcortical stroke patients and 18 healthy volunteers with matched gender and age were examined by resting state functional magnetic resonance imaging (rs-fMRI). The primary motor cotex (M1, corresponding to the lesion side) related to hand knob area was selected as the region of interest (ROI), and the positive and negative network based on the voxel-wise whole brain functional connectivity method were analyzed; the intra-network and inter-network of the two networks based on the ROI-wise functional connectivity method were also analyzed. Finally, the abnormal functional connectivity index were correlated with the upper limb motor scores in stroke patients.Results Compared with healthy controls (HCs), some brain regions with significantly greater FC with the M1 in the stroke group were all within the negative network; while other brain regions with significantly lower FC with the M1 were all within the positive functional network;. and the intra-network and inter-network FC strength of the two networks were significantly decreased. In addition, the FC coefficient of the ipsilesional middle frontal gyrus were negatively correlated with the patient's upper limb motor function scores (r=-0.735, P＜0.01).Conclusions The positive and negative network connectivity strength related to hand knob area both decrease following subcortical stroke. In particular, the FC in the stroke group greater than that in the control group does not mean "functional compensation", but reflects the degradation FC in the brain regions related to hand knob area. It may be helpful for our deep understanding of the neuropathyological mechanism of stroke and provide reference for rehabilitation intervention.
[Keywords] magnetic resonance imaging；stroke；primary motor cortex；functional connectivity；resting-state network

ZHAN Shuang1   YU Qiurong1   YIN Dazhi2   WANG Hewei3   XU Guojun1   WANG Xuefei1   GUO Miao1   SUN Changhui3   ZHU Bing3   SUN Limin3*   FAN Mingxia1*  

1 Shanghai Key Laboratory of Magnetic Resonance, Department of Physics, East China Normal University, Shanghai 200062, China

2 School of Psychology and Cognitive science, East China Normal University, Shanghai 200062, China

3 Huashan Hospital, Fudan University, Shanghai 200040, China

Fan MX, E-mail: mxfan@phy.ecnu.edu.cn Sun LM, E-mail: tracy611@sina.com

Conflicts of interest   None.

This work was part of National Natural Science Foundation of China (No. 81471651, 81974356); Young National Natural Science Foundation of China (No. 81401859); National Key R&D Program of China (No. 2020YFC2004200).
Received  2021-03-26
Accepted  2021-05-08
DOI: 10.12015/issn.1674-8034.2021.06.009
Cite this article as: Zhang S, Yu QR, Yin DZ, et al. Changes of positive and negative network connectivity related to hand knob area after stroke: A rs-fMRI study[J]. Chin J Magn Reson Imaging, 2021, 12(6): 44-50. DOI:10.12015/issn.1674-8034.2021.06.009.

1
Mirzaei G, Adeli H. Resting state functional magnetic resonance imaging processing techniques in stroke studies[J]. Rev Neurosci, 2016, 27(8): 871-885. DOI: 10.1515/revneuro-2016-0052.
2
Li M, Dahmani L, Wang D, et al. Co-activation patterns across multiple tasks reveal robust anti-correlated functional networks[J]. Neuroimage, 2021, 227: 117680. DOI: 10.1016/j.neuroimage.2020.117680.
3
Mitra A, Raichle ME. Principles of cross-network communication in human resting state fMRI[J]. Scand J Psychol, 2018, 59(1): 83-90. DOI: 10.1111/sjop.12422.
4
Avelar-Pereira B, Bäckman L, Wåhlin A, et al. Age-related differences in dynamic interactions among default mode, frontoparietal control, and dorsal attention networks during resting-state and interference resolution[J]. Front Aging Neurosci, 2017, 9: 152. DOI: 10.3389/fnagi.2017.00152.
5
Spreng RN, Stevens WD, Viviano JD, et al. Attenuated anticorrelation between the default and dorsal attention networks with aging: evidence from task and rest[J]. Neurobiol Aging, 2016, 45: 149-160. DOI: 10.1016/j.neurobiolaging.2016.05.020.
6
Ramkiran S, Sharma A, Rao NP. Resting-state anticorrelated networks in Schizophrenia[J]. Psychiatry Res Neuroimaging, 2019, 284: 1-8. DOI: 10.1016/j.pscychresns.2018.12.013.
7
Baldassarre A, Ramsey L, Hacker CL, et al. Large-scale changes in network interactions as a physiological signature of spatial neglect[J]. Brain, 2014, 137(Pt 12): 3267-3283. DOI: 10.1093/brain/awu297.
8
Fox MD, Snyder AZ, Vincent JL, et al. The human brain is intrinsically organized into dynamic, anticorrelated functional networks[J]. Proc Natl Acad Sci U S A, 2005, 102(27): 9673-9678. DOI: 10.1073/pnas.0504136102.
9
Spreng RN, Stevens WD, Viviano JD, et al. Attenuated anticorrelation between the default and dorsal attention networks with aging: evidence from task and rest[J]. Neurobiol Aging, 2016, 45: 149-160. DOI: 10.1016/j.neurobiolaging.2016.05.020.
10
Baldassarre A, Ramsey LE, Siegel JS, et al. Brain connectivity and neurological disorders after stroke[J]. Curr Opin Neurol, 2016, 29(6): 706-713. DOI: 10.1097/WCO.0000000000000396.
11
Park CH, Chang WH, Ohn SH, et al. Longitudinal changes of resting-state functional connectivity during motor recovery after stroke[J]. Stroke, 2011, 42(5): 1357-1362. DOI: 10.1161/STROKEAHA.110.596155.(Park)
12
Yin D, Song F, Xu D, et al. Patterns in cortical connectivity for determining outcomes in hand function after subcortical stroke[J]. PLoS One, 2012, 7(12): e52727. DOI: 10.1371/journal.pone.0052727.
13
Zheng X, Sun L, Yin Det al. The plasticity of intrinsic functional connectivity patterns associated with rehabilitation intervention in chronic stroke patients[J]. Neuroradiology, 2016, 58(4): 417-427. DOI: 10.1007/s00234-016-1647-4.
14
Nijboer TCW, Buma FE, Winters C, et al. No changes in functional connectivity during motor recovery beyond 5 weeks after stroke; A longitudinal resting-state fMRI study[J]. PLoS One, 2017, 12(6): e0178017. DOI: 10.1371/journal.pone.0178017.
15
Rehme AK, Eickhoff SB, Rottschy C, et al. Activation likelihood estimation meta-analysis of motor-related neural activity after stroke[J]. Neuroimage, 2012, 59(3): 2771-2782. DOI: 10.1016/j.neuroimage.2011.10.023.
16
Sahin N, Mohan S, Maralani PJ, et al. Assignment confidence in localization of the hand motor cortex: Comparison of structural imaging with functional MRI[J]. AJR Am J Roentgenol, 2016, 207(6): 1263-1270. DOI: 10.2214/AJR.15.15119.
17
Tran A, MacLean MW, Hadid V, et al. Neuronal mechanisms of motion detection underlying blindsight assessed by functional magnetic resonance imaging (fMRI)[J]. Neuropsychologia, 2019, 128: 187-197. DOI: 10.1016/j.neuropsychologia.2019.02.012.
18
Kravitz DJ, Saleem KS, Baker CI, et al. A new neural framework for visuospatial processing[J]. Nat Rev Neurosci, 2011, 12(4): 217-230. DOI: 10.1038/nrn3008.
19
Sun L, Yin D, Zhu Y, et al. Cortical reorganization after motor imagery training in chronic stroke patients with severe motor impairment: a longitudinal fMRI study[J]. Neuroradiology, 2013, 55(7): 913-925. DOI: 10.1007/s00234-013-1188-z.
20
Lutz K. Functional brain anatomy of exercise regulation[J]. Prog Brain Res, 2018, 240: 341-352. DOI: 10.1016/bs.pbr.2018.07.006.
21
Haar S, Donchin O. A revised computational neuroanatomy for motor control[J]. J Cogn Neurosci, 2020, 32(10): 1823-1836. DOI: 10.1162/jocn_a_01602.
22
Clark SV, Semmel ES, Aleksonis HA, et al. Cerebellar-subcortical-cortical systems as modulators of cognitive functions[J]. Neuropsychol Rev, Published: 29 January 2021. DOI: 10.1007/s11065-020-09465-1.
23
Jumah FR, Dossani RH. Neuroanatomy, Cingulate Cortex[A]. 2020 DOI: . Treasure Island (FL): StatPearls Publishing, 2021 DOI: .
24
Luo J, Niki K, Ding ZG, et al. Precuneus contributes to attentive control of finger movement[J]. Acta Pharmacol Sin, 2004, 25(5): 637-643.
25
Kumar V, Mang S, Grodd W. Direct diffusion-based parcellation of the human thalamus[J]. Brain Struct Funct, 2015, 220(3): 1619-1635. DOI: 10.1007/s00429-014-0748-2.
26
Touroutoglou A, Zhang J, Andreano JM, et al. Dissociable effects of aging on salience subnetwork connectivity mediate age-related changes in executive function and affect[J]. Front Aging Neurosci, 2018, 10: 410. DOI: 10.3389/fnagi.2018.00410.
27
Koen JD, Hauck N, Rugg MD. The relationship between age, neural differentiation, and memory performance[J]. J Neurosci, 2019, 39(1): 149-162. DOI: 10.1523/JNEUROSCI.1498-18.2018.
28
Heuninckx S, Wenderoth N, Swinnen SP. Systems neuroplasticity in the aging brain: recruiting additional neural resources for successful motor performance in elderly persons[J]. J Neurosci, 2008, 28(1): 91-99. DOI: 10.1523/JNEUROSCI.3300-07.2008.
29
Grossner EC, Bernier RA, Brenner EK, et al. Enhanced default mode connectivity predicts metacognitive accuracy in traumatic brain injury[J]. Neuropsychology, 2019, 33(7): 922-933. DOI: 10.1037/neu0000559.
30
Ward NS, Brown MM, Thompson AJ, et al. Neural correlates of outcome after stroke: a cross-sectional fMRI study[J]. Brain, 2003, 126(Pt 6): 1430-1448. DOI: 10.1093/brain/awg145.
31
Zhao Z, Wu J, Fan M, et al. Altered intra- and inter-network functional coupling of resting-state networks associated with motor dysfunction in stroke[J]. Hum Brain Mapp, 2018, 39(8): 3388-3397. DOI: 10.1002/hbm.24183.
32
Wu J, Cheng H, Zhang J, et al. The modulatory effects of bilateral arm training (BAT) on the brain in stroke patients: a systematic review[J]. Neurol Sci, 2021, 42(2): 501-511. DOI: 10.1007/s10072-020-04854-z.
33
Lee J, Lee A, Kim H, et al. Different brain connectivity between responders and nonresponders to dual-mode noninvasive brain stimulation over bilateral primary motor cortices in stroke patients[J]. Neural Plast, 2019, 2019: 3826495. DOI: 10.1155/2019/3826495.
34
Hartwigsen G, Volz LJ. Probing rapid network reorganization of motor and language functions via neuromodulation and neuroimaging[J]. Neuroimage, 2021, 224: 117449. DOI: 10.1016/j.neuroimage.2020.117449.
35
Lin DJ, Cloutier AM, Erler KS, et al. Corticospinal tract injury estimated from acute stroke imaging predicts upper extremity motor recovery after stroke[J]. Stroke, 2019, 50(12): 3569-3577. DOI: 10.1161/STROKEAHA.119.025898.
36
Gong Z, Zhang R, Jiang W, et al. Integrity of the hand fibers of the corticospinal tract shown by diffusion tensor imaging predicts hand function recovery after hemorrhagic stroke[J]. J Stroke Cerebrovasc Dis, 2021, 30(1): 105447. DOI: 10.1016/j.jstrokecerebrovasdis.2020.105447.

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