Altered Cortical Activity during a Finger Tap in People with Stroke.

This study describes electroencephalography (EEG) measurements during a simple finger movement in people with stroke to understand how temporal patterns of cortical activation and network connectivity align with prolonged muscle contraction at the end of a task. We investigated changes in the EEG temporal patterns in the beta band (13-26 Hz) of people with chronic stroke (N = 10, 7 F/3 M) and controls (N = 10, 7 F/3 M), during and after a cued movement of the index finger. We quantified the change in beta band EEG power relative to baseline as activation at each electrode and the change in task-based phase-locking value (tbPLV) and beta band task-based coherence (tbCoh) relative to baseline coherence as connectivity between EEG electrodes. Finger movements were associated with a decrease in beta power (event related desynchronization (ERD)) followed by an increase in beta power (event related resynchronization (ERS)). The ERS in the post task period was lower in the stroke group (7%), compared to controls (44%) (p < 0.001) and the transition from ERD to ERS was delayed in the stroke group (1.43 s) compared to controls (0.90 s) in the C3 electrode (p = 0.007). In the same post movement period, the stroke group maintained a heightened tbPLV (p = 0.030 for time to baseline of the C3:Fz electrode pair) and did not show the decrease in connectivity in electrode pair C3:Fz that was observed in controls (tbPLV: p = 0.006; tbCoh: p = 0.023). Our results suggest that delays in cortical deactivation patterns following movement coupled with changes in the time course of connectivity between the sensorimotor and frontal cortices in the stroke group might explain clinical observations of prolonged muscle activation in people with stroke. This prolonged activation might be attributed to the combination of cortical reorganization and changes to sensory feedback post-stroke.

Role of the cortex in visuomotor control of arm stability.

Whereas numerous motor control theories describe the control of arm trajectory during reach, the control of stabilization in a constant arm position (i.e., visuomotor control of arm posture) is less clear. Three potential mechanisms have been proposed for visuomotor control of arm posture: 1) increased impedance of the arm through co-contraction of antagonistic muscles, 2) corrective muscle activity via spinal/supraspinal reflex circuits, and/or 3) intermittent voluntary corrections to errors in position. We examined the cortical mechanisms of visuomotor control of arm posture and tested the hypothesis that cortical error networks contribute to arm stabilization. We collected electroencephalography (EEG) data from 10 young healthy participants across four experimental planar movement tasks. We examined brain activity associated with intermittent voluntary corrections of position error and antagonist co-contraction during stabilization. EEG beta-band (13-26 Hz) power fluctuations were used as indicators of brain activity, and coherence between EEG electrodes was used as a measure of functional connectivity between brain regions. Cortical activity in the sensory, motor, and visual areas during arm stabilization was similar to activity during volitional arm movements and was larger than activity during co-contraction of the arm. However, cortical connectivity between the sensorimotor and visual regions was higher during arm stabilization compared with volitional arm movements and co-contraction of the arm. The difference in cortical activity and connectivity between tasks might be attributed to an underlying visuomotor error network used to update motor commands for visuomotor control of arm posture.NEW & NOTEWORTHY We examined cortical activity and connectivity during control of stabilization in a constant arm position (i.e., visuomotor control of arm posture). Our findings provide evidence for cortical involvement during control of stabilization in a constant arm position. A visuomotor error network appears to be active and may update motor commands for visuomotor control of arm posture.

Cortical effects of wrist tendon vibration during an arm tracking task in chronic stroke survivors: An EEG study.

The purpose of this study was to characterize changes in cortical activity and connectivity in stroke survivors when vibration is applied to the wrist flexor tendons during a visuomotor tracking task. Data were collected from 10 chronic stroke participants and 10 neurologically-intact controls while tracking a target through a figure-8 pattern in the horizontal plane. Electroencephalography (EEG) was used to measure cortical activity (beta band desynchronization) and connectivity (beta band task-based coherence) with movement kinematics and performance error also being recorded during the task. All participants came into our lab on two separate days and performed three blocks (16 trials each, 48 total trials) of tracking, with the middle block including vibration or sham applied at the wrist flexor tendons. The order of the sessions (Vibe vs. Sham) was counterbalanced across participants to prevent ordering effects. During the Sham session, cortical activity increased as the tracking task progressed (over blocks). This effect was reduced when vibration was applied to controls. In contrast, vibration increased cortical activity during the vibration period in participants with stroke. Cortical connectivity increased during vibration, with larger effect sizes in participants with stroke. Changes in tracking performance, standard deviation of hand speed, were observed in both control and stroke groups. Overall, EEG measures of brain activity and connectivity provided insight into effects of vibration on brain control of a visuomotor task. The increases in cortical activity and connectivity with vibration improved patterns of activity in people with stroke. These findings suggest that reactivation of normal cortical networks via tendon vibration may be useful during physical rehabilitation of stroke patients.

Electroencephalography resting-state networks in people with Stroke.

INTRODUCTION: The purpose of this study was to characterize resting-state cortical networks in chronic stroke survivors using electroencephalography (EEG). METHODS: Electroencephalography data were collected from 14 chronic stroke and 11 neurologically intact participants while they were in a relaxed, resting state. EEG power was normalized to reduce bias and used as an indicator of network activity. Correlations of orthogonalized EEG activity were used as a measure of functional connectivity between cortical regions. RESULTS: We found reduced cortical activity and connectivity in the alpha (p < .05; p = .05) and beta (p < .05; p = .03) bands after stroke while connectivity in the gamma (p = .031) band increased. Asymmetries, driven by a reduction in the lesioned hemisphere, were also noted in cortical activity (p = .001) after stroke. CONCLUSION: These findings suggest that stroke lesions cause a network alteration to more local (higher frequency), asymmetric networks. Understanding changes in cortical networks after stroke could be combined with controllability models to identify (and target) alternate brain network states that reduce functional impairment.