Structurofunctional resting-state networks correlate with motor function in chronic stroke

Abstract

PurposeMotor function and recovery after stroke likely rely directly on the residual anatomical connections in the brain and its resting-state functional connectivity. Both structural and functional properties of cortical networks after stroke are revealed using multimodal magnetic resonance imaging (MRI). Specifically, functional connectivity MRI (fcMRI) can extract functional networks of the brain at rest, while structural connectivity can be estimated from white matter fiber orientations measured with high angular-resolution diffusion imaging (HARDI). A model that marries these two techniques may be the key to understanding functional recovery after stroke. In this study, a novel set of voxel-level measures of structurofunctional correlations (SFC) was developed and tested in a group of chronic stroke subjects.MethodsA fully automated method is presented for modeling the structure-function relationship of brain connectivity in individuals with stroke. Brains from ten chronic stroke subjects and nine age-matched controls were imaged with a structural T1-weighted scan, resting-state fMRI, and HARDI. Each subject's T1-weighted image was nonlinearly registered to a T1-weighted 152-brain MNI template using a local histogram-matching technique that alleviates distortions caused by brain lesions. Fractional anisotropy maps and mean BOLD images of each subject were separately registered to the individual's T1-weighted image using affine transformations. White matter fiber orientations within each voxel were estimated with the q-ball model, which approximates the orientation distribution function (ODF) from the diffusion-weighted measurements. Deterministic q-ball tractography was performed in order to obtain a set of fiber trajectories. The new structurofunctional correlation method assigns each voxel a new BOLD time course based on a summation of its structural connections with a common fiber length interval. Then, the voxel's original time-course was correlated with this fiber-distance BOLD signal to derive a novel structurofunctional correlation coefficient. These steps were repeated for eight fiber distance intervals, and the maximum of these correlations was used to define an intrinsic structurofunctional correlation (iSFC) index. A network-based SFC map (nSFC) was also developed in order to enhance resting-state functional networks derived from conventional functional connectivity analyses. iSFC and nSFC maps were individually compared between stroke subjects and controls using a voxel-based two-tailed Student's t-test (alpha = 0.01). A linear regression was also performed between the SFC metrics and the Box and Blocks Score, a clinical measure of arm motor function.ResultsSignificant decreases (p < 0.01) in iSFC were found in stroke subjects within functional hubs of the brain, including the precuneus, prefrontal cortex, posterior parietal cortex, and cingulate gyrus. Many of these differences were significantly correlated with the Box and Blocks Score. The nSFC maps of prefrontal networks in control subjects r...

Electroencephalography resting‐state networks in people with Stroke

“…Decreased connectivity of the alpha and beta bands in resting‐state paradigms has been reported using other EEG approaches (Dubovik et al., 2012, 2013; Wu et al., 2015). The decreased alpha (10–15 Hz) connectivity within a prefrontal‐cerebellar network in the stroke group is consistent with previous findings from our laboratory indicating decreased fMRI functional connectivity in a similar network after stroke (Kalinosky et al., 2017). The beta (15–20 Hz) band decreased connectivity consisted of prominent nodes in the lesioned hemisphere's sensory/parietal regions indicating it may be a marker of sensorimotor dysfunction that often occurs after stroke (Inman et al., 2012; Platz et al., 2000; Rossiter et al., 2014; Sharma et al., 2009; Wu et al., 2015).…”

Tasked-Based Functional Brain Connectivity in Multisensory Control of Wrist Movement After Stroke

“…The motor cortex and cerebellum together have been shown to be involved in plasticity during motor training and in sensorimotor integration (62). Past imaging studies have shown that the connectivity between the cerebellum and parietofrontal areas are related to post-stroke motor function (63, 64).…”

Prefrontal-Premotor Pathways and Motor Output in Well-Recovered Stroke Patients

“…Third, based on clear a priori hypotheses, we focused on defined prefrontal-premotor connections at the cortical level. The present results are not exhaustive, and the state of other motor networks, such as prefrontal-subcortical (45) or prefrontal-cerebellar circuits, might also influence comparable analyses.…”