Author Of 2 Presentations
LB1195 - Changes in Mobility and Brain Connectivity following over-ground Robotic Exoskeleton Rehabilitation in Persons with MS (ID 2020)
Abstract
Background
Multiple Sclerosis (MS) has an estimated prevalence of 337-362 per 100,000 people[1] and is characterized as an autoimmune disease that causes axonal degradation, leading to mobility and cognitive impairments. While physical rehabilitation has been identified as one of the best methods for restoring function in MS[2], it can be challenging to implement in individuals with severe impaired mobility. One approach is the use of a novel assistive device such as a wearable Robotic exoskeletons (RE). REs have been increasingly used to provide gait rehabilitation for persons with mobility disorders (e.g. spinal cord injury and stroke) [3-7], and more recently for persons with MS[8, 9]. The current study examines potential improvements in mobility, cognitive processing speed, as well as resting-state (RS) functional connectivity of the brain in persons with MS through the use of RE.
Objectives
To determine if gait training using RE improves mobility, cognition, and brain RS functional connectivity in persons with MS.
Methods
Four persons with relapsing-remitting MS (RRMS) participated in this randomized pilot prospective study. Two MS patients received eight 1-hour RE training sessions (Ekso-GT, Ekso Bionics, Berkley, CA, USA) administered by a licensed physical therapist; the other two participants received eight 1-hour Conventional Gait Therapy (CGT) sessions. The 8-seesion interventions occurred over a four week period (2 sessions/week). The Six Minute Walk Test (6MWT), Symbol Digit Modalities Test (SDMT), and RS functional MRI (fMRI) of the brain, acquired using a Siemens Skyra 3 Tesla MRI scanner were assessed at baseline and after the 4-week intervention. A seed-based RS functional connectivity analysis approach was used, with seeds placed in the motor and ventromedial prefrontal cortices (vmPFC).
Results
The RE group improved by 21% in walking distance in the 6MWT while the CGT group showed essentially no change (a 2% decrease in the distance). The RE group also showed improvements in SDMT performance (ZRE = 0.95; ZCGT = - 0.78), as well as improvements in functional connectivity in the motor cortex (ZRE = 0.8; ZCGT = - 0.08) and in the vmPFC (ZRE = 0.8; ZCGT = -0.003).
Conclusions
Improvements in mobility, cognitive processing speed, and resting state functional connectivity in the motor cortex and in the vmPFC were observed for participants in the RE gait training group but not in the CGT group. These pilot results suggest that gait training using RE can be an effective therapy for improving walking ability, cognitive function, and brain connectivity in resting-state networks in persons with MS. Data analysis of a larger sample is underway to confirm the findings.
LB1269 - Higher parietal and premotor cortex activation and connectivity during treadmill walking in Persons with Multiple Sclerosis versus healthy controls (ID 2167)
Abstract
Background
Persons with Multiple Sclerosis (pwMS) experience a decline in cognitive and physical performance, which could affect their walking and their ability to attend to their surrounding environment during walking. Therefore, pwMS may show higher recruitment of brain attention network regions like parietal and premotor areas during walking (WALK), a recruitment that could increase more during obstacle avoidance while walking (OBSAV).
Objectives
This study explored Electroencephalography (EEG) based brain activation and brain connectivity during treadmill walking and during walking while avoiding virtual reality obstacles on the treadmill. The study included a group of pwMS and a health control group (HC) matched by age and gender. We expected higher brain activity and brain connectivity in parietal and premotor cortices in the pwMS group, especially in the OBSAV condition.
Methods
Data of 9 pwMS and 8 healthy controls were collected. Kessler Foundation Institutional Review Board (IRB) approved the protocol. Brain and muscles activations were collected as participants walked on an instrumented treadmill (C-MILL, Motekforce, The Netherlands). The C-MILL CueFor2 software was used to collect loading force of each participant during the walking tasks, and captured the timing of the major events of the gait cycle. EEG data were collected using a 64-channel wireless ActiCap EEG system from Brain Products (Munich, Germany). EEG data collection sampling rate was set to 500Hz and FCz EEG channel was chosen as the reference during data collection. Data were collected for a minimum 100 trials of 30-second walking at self-selected speed. Each WALK trial was followed by a 30-second trial of walking while avoiding randomly projected virtual obstacles (OBSAV). Outcomes measures included EEG signal power within alpha (8-12 Hz) and beta (12-30 Hz) bands in 11 regions of interest that included bilateral parietal, premotor, frontal, and motor cortices and supplementary motor area and coherence between these regions.
Results
In comparison to the HC group, the pwMS group showed higher power of EEG signals within the beta band in the left parietal (F=7.8, p=0.008) and left premotor cortex (F=4.11, p=0.05). They also showed higher coherence between left parietal and left premotor cortices and between left premotor and left motor cortices. There was no difference in these outcomes between WALK and OBS conditions.
Conclusions
Our findings confirm the role of attention network in the control of walking and obstacle avoidance in the MS group. Our group will further investigate this network and connectivity between the brain and muscles to acquire better understanding of the interaction between cognitive and motor performance and cortical control centers and muscles participating in walking in pwMS and how that could affect pwMS daily activity.