Mirrored feedback in chronic stroke: recruitment and effective connectivity of ipsilesional sensorimotor networks

Abstract

Background: Mirrored feedback has potential as a therapeutic intervention to restore hand function after stroke. However, the functional (effective) connectivity of neural networks involved in processing mirrored feedback after stroke is not known.

Objective: To determine if regions recruited by mirrored feedback topographically overlap with those involved in control of the paretic hand and to identify the effective connectivity of activated nodes within the mirrored feedback network.

Methods: Fifteen patients with chronic stroke performed a finger flexion task with their unaffected hand during event-related functional magnetic resonance imaging (fMRI). Real-time hand kinematics was recorded during fMRI and used to actuate hand models presented in virtual reality (VR). Visual feedback of the unaffected hand motion was manipulated pseudorandomly by either actuating the VR hand corresponding to the moving unaffected side (veridical feedback) or the affected side (mirrored feedback). In 2 control conditions, the VR hands were replaced with moving nonanthropomorphic shapes.

Results: Mirrored feedback was associated with significant activation of regions within and outside the ipsilesional sensorimotor cortex, overlapping with areas engaged when patients performed the task with their affected hand. Effective connectivity analysis showed a significantly interconnected ipsilesional somatosensory and motor cortex in the mirrored feedback condition.

Conclusions: Mirrored feedback recruits ipsilesional brain areas relevant for control of the affected hand. These data provide a neurophysiological basis by which mirrored feedback may be beneficial as a therapy for restoring function after stroke.

Keywords: fMRI; mirrored feedback; motor control; virtual reality; visuomotor integration.

Figures

Figure 1

(A) Mapping of each patient’s lesion. Each row shows 5 different patients with lesions filled in with color. Blue horizontal lines in the midsagittal slice mark the levels of the axial slices to the left. (B) The experimental setup and feedback conditions in virtual reality (VR), viewed from the patient’s perspective. Motion of the right unaffected hand (upper left inset) would actuate the right (veridical) or left (mirrored) VR hand or a left/right nonanthropomorphic shape (control). All conditions were randomly interleaved within a functional magnetic resonance imaging run.

Figure 2

Group mean of the main effect of mirrored feedback (contrast 2) (family-wise error corrected P < .05; minimal cluster size k = 10). For averaging purposes, left-sided lesions were flipped to the right (see Methods) such that the right hemisphere (R) represents the ipsilesional hemisphere. Surface plots were generated using render and canonical templates in SPM8. Note that mirrored feedback activation was observed in the ipsilesional precentral gyrus, corresponding to the hand area of the motor cortex, along with other distributed frontal and parietal areas.

Figure 3

Group mean of the conjunction analysis between contrast 2 (experiment 1) and contrast 3 (experiment 2) to identify topographic overlap between brain regions recruited during motion of the unaffected hand with mirrored feedback and those controlling motion of the affected hand.

Figure 4

(A) Effective connectivity of the psychophysiological interaction between the Brodmann area (BA1) seed region (white circle) (Montreal Neurological Institute space: 63, −18, 39) and the rest of the brain (family-wise error corrected P < .05; minimal cluster size k = 10) overlaid on a partially inflated cortical surface (Caret software, http://www.nitrc.org/projects/caret/, St. Louis, MO) from the right lateral and top view. (B) Bar plots showing the strength of effective connectivity between the BA1 seed and BA4 (39, −12, 48) and between the BA1 seed and BA3 (51, −15, 36) in each of the 4 conditions. (C) Linear regression between the t values corresponding to the strength of effective connectivity (y-axis) and level of hand function (x-axis). Hand function is plotted as the lognormed distal subtest of the Wolf Motor Function Test (dWMFT) score (1-log10 dWMFT), with larger values indicating better hand function.