Resting-state functional connectivity and its association with multiple domains of upper-extremity function in chronic stroke

Abstract

Background: Recent work has shown that resting-state functional connectivity (rsFC) between homotopic, motor-related brain regions is associated with upper-extremity control early after stroke.

Objectives: This study examined various patterns of rsFC in chronic stroke, a time at which extensive neural reorganization has occurred. Associations between homotopic somatomotor connectivity and clinical measures, representing separate domains of upper-extremity function, were determined.

Methods: A total of 19 persons ≥6 months poststroke participated. Four connectivity patterns within a somatomotor network were quantified using functional magnetic resonance imaging. Upper-extremity gross muscle activation, control, and real-world use were evaluated with the Motricity Index, Action Research Arm Test, and accelerometry, respectively.

Results: Connectivity between homotopic regions was stronger than that in the contralesional and ipsilesional hemispheres. No differences in connectivity strength were noted between homotopic pairs, indicating that a specific brain structure was not driving somatomotor network connectivity. Homotopic connectivity was significantly associated with both upper-extremity control (r = 0.53; P= .02) and real-world use (r = 0.54; P= .02); however, there was no association with gross muscle activation (r = 0.23; P=.34). The combination of clinical measures accounted for 40% of the variance in rsFC (= .05).

Conclusions: The results reported here expand on previous findings, indicating that homotopic rsFC persists in chronic stroke and discriminates between varying levels of upper-extremity control and real-world use. Further work is needed to evaluate its adequacy as a biomarker of motor recovery following stroke.

Keywords: hemiparesis; motor control; resting-state functional connectivity; stroke.

© The Author(s) 2014.

Figures

Figure 1

A representative functional connectivity map of the somatomotor network in a control participant generated by the 25 ROIs. Individual maps from each ROI seed were thresholded and then summed.

Figure 2

Distribution of stroke lesions. Color scale indicates number of participants with lesioned voxel.

Figure 3

Strength of resting-state functional connectivity patterns. (* indicates a significant difference relative to homotopic, † indicates a significant difference relative to ipsilesional, ‡ indicates a significant difference relative to contralesional.)

Figure 4

Comparison of a) resting-state connectivity pattern strength and b) homotopic regions of interest between stroke and control participants. (*p

Figure 5

Correlations between interhemispheric, homotopic connectivity and each domain of upper extremity function: a) gross muscle activation, b) control, and c) real-world use.