Altered temporal variability-based functional reorganization of brain networks predicts motor outcome after stroke

 Predicting recovery rather than delivering recovery IS COMPLETE INCOMPETENCE!

I take no prisoners in trying to get stroke solved and that means a lot of dead wood needs to be removed. 

Altered temporal variability-based functional reorganization of brain networks predicts motor outcome after stroke

• Guojun Xu,
• Ling Li,
• Qinyang Li,
• Hewei Wang,
• Mingxia Fan,
• Limin Sun,
• Zhiyong Zhao &
• Hongxing Wang 

We are providing an unedited version of this manuscript to give early access to its findings. Before final publication, the manuscript will undergo further editing. Please note there may be errors present which affect the content, and all legal disclaimers apply.

Abstract

Background

Dynamic functional connectivity (FC) studies have shown that motor recovery after stroke was associated with functional reorganization of brain networks. However, most previous studies have focused on interregional variability rather than the temporal variability (TV) of specific regions or networks. TV quantifies the dynamic reconfiguration of a region’s or network’s functional connectivity profile over time and reflects neural flexibility.

Purpose

This study investigated functional reorganization in chronic subcortical stroke using TV of brain networks derived from resting-state fMRI.

Methods

Thirty-three patients with left subcortical stroke (LSS), thirty with right subcortical stroke (RSS), and fifty-six age- and sex-matched healthy controls (HCs) were enrolled. Stroke patients underwent resting-state fMRI and Upper Extremity Fugl-Meyer Assessment (UE-FMA) at two time points. TV was computed to characterize dynamic functional connectivity at regional, intra-network, and inter-network levels. Group differences were assessed using one-way ANCOVA with post hoc tests. Linear regression was used to examine associations between TV and motor outcomes. The false discovery rate was used to multiple comparisons correction.

Results

Compared with HCs, both LSS and RSS showed significantly reduced TV in the right frontal-cingulate regions, the somatomotor hand network (SSH), and the connections between SSH and higher-order cognitive networks (all p < 0.05, |Cohen’s d| > 0.49). Increased TV was observed in the left postcentral gyrus, inferior frontal gyrus, cerebellar network (CEN), and somatomotor mouth network (all p < 0.05, |Cohen’s d| > 0.48). Relative to LSS, RSS exhibited additional TV reductions in the right middle occipital gyrus, orbital middle frontal gyrus, default mode network (DMN), and interactions among higher-order cognitive networks (all p < 0.05, |Cohen’s d| > 0.65). Notably, TV in the right opercular inferior frontal gyrus (IFGoperc) (β = 102.69, adjusted p = 6.4 × 10^− 5) and CEN (β = 27.87, adjusted p = 0.011) at the first observation positively correlated with UE-FMA scores at follow-up, with effects modulated by lesion laterality.

Conclusion

TV captures multiscale functional reorganization in chronic subcortical stroke involving motor, cognitive, and sensory networks. TV of the right IFGoperc showed potential as a neuroimaging biomarker for predicting post-stroke motor recovery.