Background and Purpose—: Functional MRI (fMRI) studies could provide crucial information on the neural mechanisms of motor recovery in patients with stroke. Resting-state fMRI is applicable to patients with stroke who are not capable of proper performance of the motor task. In this study, we explored neural correlates of motor recovery in patients with stroke by investigating longitudinal changes in resting-state functional connectivity of the ipsilesional primary motor cortex (M1). Methods—: A longitudinal observational study using repeated fMRI experiments was conducted in 12 patients with stroke. Resting-state fMRI data were acquired 4 times over a period of 6 months. Patients participated in the first session of fMRI shortly after onset and thereafter in subsequent sessions at 1, 3, and 6 months after onset. Resting-state functional connectivity of the ipsilesional M1 was assessed and compared with that of healthy subjects. Results—: Compared with healthy subjects, patients demonstrated higher functional connectivity with the ipsilesional frontal and parietal cortices, bilateral thalamus, and cerebellum. Instead, functional connectivity with the contralesional M1 and occipital cortex were decreased in patients with stroke. Functional connectivity between the ipsilesional and contralesional M1 showed the most asymmetry at 1 month after onset to the ipsilesional side. Functional connectivity of the ipsilesional M1 with the contralesional thalamus, supplementary motor area, and middle frontal gyrus at onset was positively correlated with motor recovery at 6 months after stroke. Conclusions—: Resting-state fMRI elicited distinctive but comparable results with previous task-based fMRI, presenting complementary and practical values for use in the study of patients with stroke.

Chang WH, et al. J Stroke. 2013 Sep;15(3):174-181. http://dx.doi.org/10.5853/jos.2013.15.3.174

Background. Robot-assisted gait training has the potential to improve cardiopulmonary fitness after stroke, even for patients who are in the early stages of recovery and not independent ambulators. The authors compared the effects of robot-assisted gait training and conventional physical therapy on cardiopulmonary fitness. Methods. A prospective single-blinded, randomized controlled study of 37 patients receiving inpatient rehabilitation was performed within 1 month after stroke onset. The robot-assisted gait training group (n = 20) received 40 minutes of gait training with Lokomat and 60 minutes of conventional physical therapy each day, whereas the control group (n = 17) received 100 minutes of conventional physical therapy daily. Using a semirecumbent cycle ergometer, changes in cardiopulmonary fitness were investigated using incremental exercise testing. Motor and gait functional recovery was measured according to changes in the lower-extremity score of the Fugl-Meyer Assessment Scale (FMA-L), leg score of the Motricity Index (MI-L), and the Functional Ambulation Category (FAC). Results. Compared with the control group, the robot group showed 12.8% improvement in peak VO₂ after training ( P < .05). Compared with the control group, the robot group also improved in FMA-L score ( P < .05). Conclusion. Patients can be trained to increase their VO₂ and lower-extremity strength using a robotic device for stepping during inpatient rehabilitation. This training has the potential to improve cardiopulmonary fitness in patients who are not yet independent ambulators, but that may require more than 2 weeks of continued, progressive training.

Recent studies of functional or effective connectivity in the brain have reported that motor-related brain regions were activated during motor execution and motor imagery, but the relationship between motor and cognitive areas has not yet been completely understood. The objectives of our study were to analyze the effective connectivity between motor and cognitive networks in order to define network dynamics during motor execution and motor imagery in healthy individuals. Second, we analyzed the differences in effective connectivity between correct and incorrect responses during motor execution and imagery using dynamic causal modeling (DCM) of electroencephalography (EEG) data. Twenty healthy subjects performed a sequence of finger tapping trials using either motor execution or motor imagery, and the performances were recorded. Changes in effective connectivity between the primary motor cortex (M1), supplementary motor area (SMA), premotor cortex (PMC), and dorsolateral prefrontal cortex (DLPFC) were estimated using dynamic causal modeling. Bayesian model averaging with family-level inference and fixed-effects analysis was applied to determine the most likely connectivity model for these regions. Motor execution and imagery showed inputs to distinct brain regions, the premotor cortex and the supplementary motor area, respectively. During motor execution, the coupling strength of a feedforward network from the DLPFC to the PMC was greater than that during motor imagery. During motor imagery, the coupling strengths of a feedforward network from the PMC to the SMA and of a feedback network from M1 to the PMC were higher than that during motor execution. In imagined movement, although there were connectivity differences between correct and incorrect task responses, each motor imagery task that included correct and incorrect responses showed similar network connectivity characteristics. Correct motor imagery responses showed connectivity from the PMC to the DLPFC, while the incorrect responses had characteristic connectivity from the SMA to the DLPFC. These findings provide an understanding of effective connectivity between motor and cognitive areas during motor execution and imagery as well as the basis for future connectivity studies for patients with stroke.

Background. This study aimed to delineate the cerebral attentional network in patients with traumatic brain injury (TBI) and assess for adaptations in this network in response to a rehabilitation intervention. Methods. Seventeen patients with TBI and 15 healthy subjects underwent functional magnetic resonance imaging (fMRI) using a visuospatial attention task. Ten TBI patients who successfully completed attentional training had a follow-up fMRI. Results. In the TBI patients, fMRI analysis showed more activation in the frontal and temporoparietal lobes, as well as less activation in the anterior cingulated gyrus, SMA, and temporooccipital regions compared to the healthy subjects. Following cognitive training, the TBI patients improved performance of attention tasks accompanied by changes in attentional network activation; the activity of the frontal lobe decreased, whereas activation of the anterior cingulate cortices and precuneus increased. Conclusions. These findings demonstrate the plasticity and training induced redistribution of the visuospatial attentional network in TBI patients.