Danny R. Rose, Jr., MD
Schulz R, Buchholz A, Frey BM, Bönstrup M, Cheng B, Thomalla G, et al. Enhanced Effective Connectivity Between Primary Motor Cortex and Intraparietal Sulcus in Well-Recovered Stroke Patients. Stroke. 2016
The advent of functional brain imaging has greatly advanced the understanding of how interregional interactions and connectivity in the brain are disrupted by ischemic stroke and are modified in patients as they recover motor function after stroke. Most studies have focused on frontal motor circuits, including the primary motor cortices (M1), dorsal (PMd) and ventral premotor cortices (PMv), and the supplementary motor area (SMA). Studies in healthy subjects suggest that the posterior parietal cortices also play an important role in motor tasks, particularly dexterous hand function which is crucial for functional activities. Data from both resting-state connectivity studies and longitudinal whole-brain analyses suggest a reduced information flow from the ipsilesional parietal brain regions to ipsilesional M1 and secondary motor areas after stroke that are followed by time-dependent changes in neuronal connectivity during recovery. By using functional magnetic resonance imaging (fMRI) and dynamic causal modeling (DCM), Schulz et al. investigated interactions between parietal cortices and frontal motor areas of the ipsilesional hemisphere in stroke patients as compared to healthy controls, as well as whether the degree of neuronal coupling correlates with residual functional deficit.
Fifteen patients (7 male, one left-handed, aged 68±8.5 years) were included roughly three months after first-ever ischemic stroke. Residual motor function was determined by a combination of grip force, the Nine-hole-peg test (NHP), and the Fugl-Meyer score for the upper extremity (UEFM). These assessments were compared to those of seventeen healthy controls of comparable age and sex (10 male, one left-handed, aged aged 64±9.9 years). Participants underwent event-related functional brain imaging while performing 30 isometric visually-guided whole hand grips with the paretic hand using a grip force response device. Controls were pseudo-randomly assigned to move either their right or left hand. All participants underwent functional imaging using a gradient echo-planar imaging sequence with a 3T MRI scanner. Image analysis was performed to identify areas of task-related brain activation for each patient, and these areas were quantified using blood oxygenation level dependent (BOLD) parameter estimates for five ipsilesional areas (M1, PMv, SMA, anterior (aIPS) and caudal part of the intraparietal sulcus (cIPS).
Dynamic causal modeling was utilized to analyze interregional connectivity using a priori assumptions. The coupling parameters were divided into three matrices. The A matrix represented the “resting state” of task-independent interregional coupling. The B matrix represented the changes in coupling parameters elicited by the task input, and the C matrix specified regions receiving exogenous inputs. Group-wise Bayesian model averaging was applied to derive mean coupling estimates for each connection weighted by the model probabilities. Two-tailed Wilcoxon rank sum exact tests were used to determine the significance of differences between stroke patients and controls. Spearman’s correlation coefficient was used to evaluate the relationship between coupling estimates and clinical scores.
In stroke patients, the task studied induced a significant increase in BOLD signal in the ipsilesional M1, PMv, SMA, aIPS, and cIPS both in the ipsilesional and contralesional hemispheres. Accounting for spatial variability in focal brain activation, it was found that both cases and controls had similar subject-specific peak coordinates and Euclidean distances between individual and group-level coordinates. The stroke patients and controls showed comparable grip-related effective connectivity values, with the most prominent increase in information flow being found from SMA to M1 and PMv to M1. Stroke patients also exhibited enhanced facilitatory connectivity from aIPS or M1 and M1 to aIPS (p<0.05). Interestingly, there were no significant correlations between clinical performance and coupling estimates.
This study extends previous findings suggesting that parietal brain region interactions with frontal motor areas may facilitate plastic changes after stroke. It is likely that posterior parietal brain regions act as important nodes for sensorimotor integration, particularly when visual rather proprioceptive feedback was given, as was the case in this study. The lack of association between coupling and residual motor function was unexpected. The authors posit that this may suggest that direct activity of the posterior parietal cortex may be more integrative, relying more on other parameters and less directly reflective of functional motor activity. The issue was also raised that current measures of dexterous hand function may not be adequate to assess minute, nuanced improvements, which has been an issue when relating clinical scoring to functional imaging in multiple areas of research. This study also has many of the other limitations when clinically correlating functional brain imaging data (i.e.. motor tasks not specifically designed to activate the area in question, possibility of “hidden” accessory pathways that were not directly studied, inability to control for differences in cognitive processing when performing task). Regardless, the study provides a valuable insight into the role of the ipsilesional parietofrontal motor network and its importance with respect to motor functioning and recovery after stroke.