Frontiers in Aging Neuroscience (Jun 2022)

Task-State Cortical Motor Network Characteristics by Functional Near-Infrared Spectroscopy in Subacute Stroke Show Hemispheric Dominance

  • Ziwen Yuan,
  • Ziwen Yuan,
  • Weiwei Xu,
  • Jiameng Bao,
  • Hui Gao,
  • Wen Li,
  • Yu Peng,
  • Lisha Wang,
  • Lisha Wang,
  • Ye Zhao,
  • Ye Zhao,
  • Siming Song,
  • Jin Qiao,
  • Gang Wang

DOI
https://doi.org/10.3389/fnagi.2022.932318
Journal volume & issue
Vol. 14

Abstract

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BackgroundThere was a reorganization of the brain network after stroke. Some studies have compared the characteristics of activation or functional connectivity (FC) of cortical and subcortical regions between the dominant and non-dominant hemisphere stroke.ObjectivesTo analyze hemispheric dominance differences in task-state motor network properties in subacute stroke by functional near-infrared spectroscopy (fNIRS).Materials and MethodsPatients with first ischemic stroke in the basal ganglia within 1–3 months after onset and age- and sex-matched right-handed healthy subjects (HS) were enrolled. fNIRS with 29 channels was used to detect the oxyhemoglobin concentration changes when performing the hand grasping task. Activation patterns of motor cortex and two macroscale and two mesoscale brain network indicators based on graph theory were compared between dominant and non-dominant hemisphere stroke.ResultsWe enrolled 17 subjects in each of left hemisphere stroke (LHS), right hemisphere stroke (RHS), and HS groups. Both patient groups showed bilateral activation. The average weighted clustering coefficient and global efficiency of patients were lower than those of healthy people, and the inter-density was higher than that of the HS group, but the significance was different between LHS and RHS groups. The intra-density changes in the RHS group were opposite to those in the LHS group. The correlation between mesoscale indicators and motor function differed between dominant and non-dominant hemisphere stroke.ConclusionThe changes in macroscale cortical network indicators were similar between the two patient groups, while those of the mesoscale indicators were different. The mesoscale brain network characteristics were affected by the severity of dysfunction to varying degrees in the LHS and RHS patients.

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