How functional network connectivity changes as a result of lesion and recovery: An investigation of the network phenotype of stroke

Cortex. 2020 Oct:131:17-41. doi: 10.1016/j.cortex.2020.06.011. Epub 2020 Jul 15.

Abstract

This study, through a series of univariate and multivariate (classification) analyses, investigated fMRI task-based functional connectivity (FC) at pre- and post-treatment time-points in 18 individuals with chronic post-stroke dysgraphia. The investigation examined the effects of lesion and treatment-based recovery on functional organization, focusing on both inter-hemispheric (homotopic) and intra-hemispheric connectivity. The work confirmed, in the chronic stage, the "network phenotype of stroke injury" proposed by Siegel et al. (2016) consisting of abnormally low inter-hemispheric connectivity as well as abnormally high intra-hemispheric (ipsilesional) connectivity. In terms of recovery-based changes in FC, this study found overall hyper-normalization of these abnormal inter and intra-hemispheric connectivity patterns, suggestive of over-correction. Specifically, treatment-related homotopic FC increases were observed between left and right dorsal frontal-parietal regions. With regard to intra-hemispheric connections, recovery was dominated by increased ipsilateral connectivity between frontal and parietal regions along with decreased connectivity between the frontal regions and posterior parietal-occipital-temporal areas. Both inter and intra-hemispheric changes were associated with treatment-driven improvements in spelling performance. We suggest an interpretation according to which, with treatment, as posterior orthographic processing areas become more effective, executive control from frontal-parietal networks becomes less necessary.

Keywords: Functional connectivity; Functional network; Language deficit; Neuroplasticity; Stroke recovery.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Brain / diagnostic imaging
  • Brain Mapping*
  • Humans
  • Magnetic Resonance Imaging
  • Phenotype
  • Stroke* / diagnostic imaging