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Traumatic brain injury (TBI) often results in balance impairment, increasing the risk of falls, and the chances of further injuries. However, the underlying neural mechanisms of postural control after TBI are not well understood. To this end, we conducted a pilot study to explore the neural mechanisms of unpredictable balance perturbations in 17 chronic TBI participants and 15 matched healthy controls (HC) using the EEG, MRI, and diffusion tensor imaging (DTI) data. As quantitative measures of the functional integration and segregation of the brain networks during the postural task, we computed the global graph‐theoretic network measures (global efficiency and modularity) of brain functional connectivity derived from source‐space EEG in different frequency bands. We observed that the TBI group showed a lower balance performance as measured by the center of pressure displacement during the task, and the Berg Balance Scale (BBS). They also showed reduced brain activation and connectivity during the balance task. Furthermore, the decrease in brain network segregation in alpha‐band from baseline to task was smaller in TBI than HC. The DTI findings revealed widespread structural damage. In terms of the neural correlates, we observed a distinct role played by different frequency bands: theta‐band modularity during the task was negatively correlated with the BBS in the TBI group; lower beta‐band network connectivity was associated with the reduction in white matter structural integrity. Our future studies will focus on how postural training will modulate the functional brain networks in TBI., EEG connectivity graph measures were studied in traumatic brain injury (TBI) during the balance perturbation task. TBI group showed altered brain activation and connectivity during the balance task. Graph‐theoretic measures showed that the task modulation of brain network segregation in alpha‐band was reduced in TBI and the network segregation in theta‐band was associated with postural instability in TBI.

Conventional therapy improves motor recovery after stroke. However, 50% of stroke survivors still suffer from a significant level of long-term upper extremity impairment. Identifying a specific biomarker whose magnitude scales with the level of force could help in the development of more effective, novel, highly targeted rehabilitation therapies such as brain stimulation or neurofeedback. Four chronic stroke participants were enrolled in this pilot study to find such a neural marker using an Independent Component Analysis (ICA)-based source analysis approach, and investigate how it has been affected by the injury. Beta band desynchronization in the ipsilesional primary motor cortex was found to be most robustly scaling with force. This activity modulation with force was found to be significantly reduced, and to plateau at higher force than that of the contralesional (unaffected) side. A rehabilitation therapy that would target such a neuromarker could have the potential to strengthen the brain-to-muscle drive and improve motor learning and recovery.Clinical Relevance- This study identifies a neural marker that scales with motor output and shows how this modulation has been affected by stroke.

Repeatedly performing a submaximal motor task for a prolonged period of time leads to muscle fatigue manifested by its reduced capacity to generate force or power. Fatigue resulted from voluntary muscle contractions comprises a central and peripheral component, which demands a gradually increasing effort to perform the task as time elapses. However, we still lack a complete understanding of brain contribution to the enhancement of effort to cope with progressing fatigue because of repeated submaximal muscle contractions. The knowledge of how muscle fatigue modulates brain activities in a healthy population will help rationalize why certain patients experience exacerbated fatigue while carrying out mundane tasks. The intermittent motor tasks closely resemble many activities of daily living (ADL), thus remaining physiologically relevant to study fatigue. The scope of this study is therefore to investigate the EEG-based brain activation patterns in healthy subjects performing intermittent submaximal muscle contractions until self-perceived exhaustion. Fourteen participants (median age 51.5 years; age range 26-72 years; 5 males) repeated elbow flexion contractions at 40% maximum voluntary contraction by following visual cues displayed on an oscilloscope screen until subjective exhaustion. Each contraction lasted ~5 s with a 2-s rest between trials. The force, EEG, and surface EMG (from elbow joint muscles) data were simultaneously collected. After preprocessing, we selected a subset of trials at the beginning, middle, and end of the study session representing brain activities germane to mild, moderate, and severe fatigue conditions, respectively, to compare and contrast the changes in the EEG time-frequency (TF) characteristics across the conditions. The TF analyses were conducted both at the channel and source level. The outcome of the channel- and source-level analyses reveal that the theta, alpha, and beta power spectral densities (PSDs) vary in proportion to fatigue levels in cortical motor areas. Importantly, the pairwise PSD differences between the fatigue conditions survived the statistical inferential tests with a p-value threshold of 0.05. We observed a statistically significant change in the band-specific spectral power in relation to the graded fatigue from both the steady- and post- contraction EEG data. The findings would enhance our understanding of the etiology and physiology of voluntary motor action-related fatigue and provide pointers to counteract the perception of muscle weakness and lack of motor endurance associated with ADL. The study outcome would help evaluate how clinical conditions such as neurological disorders and cancer treatment alter neural mechanisms underlying fatigue in future studies and develop therapeutic strategies for restoring the patients9 ability to participate in ADL by mitigating central and muscle fatigue.

this study examines the relationship between brain structural connectivity, and physical and cognitive performances in individuals with Traumatic Brain Injury (TBI). Nine moderate to severe TBI participants were included in the study, and regression analysis was performed to explore if DTI connectivity of 16 regions of interest can predict individuals' : 1) Maximum Voluntary Contraction (MVC), 2) time component of Wolf Motor Function Test (WMFT), 3) Reaction Time (RT) during bimanual force matching task, 4) Performance Error Measurement (PEM) during bimanual force matching task, and 5) cognitive assessment of task switching using Trail Making (TM) test. Results showed that slower WMFT, PEM, and TM can be predicted by weaker cerebrospinal tract connectivity. Higher Caudate connectivity predicted higher WMFT and slower RT, and higher right Cingulum predicted faster TM. Current results suggest that measures of cognitive-motor interference may be better indicators of functional performance than single cognitive and motor performance tests.

30-60% of traumatic brain injury (TBI) patients suffer from long-term balance deficit. Even though motor preparation and execution are altered and slowed in TBI, their relative contribution and importance to posture instability remain poorly understood. This study investigates the impaired cortical dynamics and neuromuscular response in TBI in response to balance perturbation and its relation to balance deficit. 12 TBI and 6 healthy control (HC) participants took the Berg Balance Scale (BBS) test and participated in a balance perturbation task where they were subjected to random anterior/posterior translation, while brain (EEG), muscle (EMG) activities, and center of pressure (COP) were continuously recorded. Using independent component analysis (ICA), the component most responsible for the N1 component of the perturbation evoked potential (PEP) was selected and its amplitude and latency were extracted. Balance task performance was measured by computing the COP displacement during the task. TBI had a significantly lower BBS, larger COP displacement and lower N1 amplitude compared to the HC group. No group differences was found for N1 latency and muscle activity onset delay to the perturbation. BBS was correlated with the COP displacement and N1 amplitude, and COP displacement was correlated with N1 latency. TBI balance deficit may be associated with more impaired than delayed cortical response to balance perturbation.

The overall goal of this study is to investigate the role of parietal cortex in the control of walking in persons with Multiple Sclerosis (pwMS). We examined within-brain connectivity and cortico-muscular connectivity as pwMS and healthy control (HC) participants walked on an instrumented treadmill. Cortical activity was collected using EEG, muscle activity was collected using wireless EMG modules, and gait data were obtained by using the instrumented treadmill. Results show significant activation of sensorimotor and posterior parietal cortex during walking in both groups. Connectivity between parietal (posterior cingulate cortex PCC) and premotor regions (pars opercularis), and between PCC and contralateral muscles were higher in the healthy control group. Higher connectivity correlated with higher walking speed.

Multiple sclerosis (MS) is one of the neurodegenerative diseases that damage the nervous system and inflicts cognitive and motor deficits. In motor domain, MS mainly causes slower gait resulting in challenges in activities of daily living. Premotor cortices are affected by MS, where several imaging studies have reported re-organization in the activity and connectivity of these regions. Recent advancements in mobile imaging technologies and signal processing techniques have made it possible to study supraspinal modulation of walking in able-bodied individuals and persons with injuries or neurological disorders. Functional near-infrared spectroscopy (fNIRS), for example, was used in studying dual-tasking in MS population. In the current study, we used fNIRS to record activities of premotor and supplementary motor areas in MS and healthy populations during standing and walking. Fourteen healthy controls and 14 persons with MS were tested during overground walking. Results show higher right premotor cortex activities compared with left premotor and bilateral supplementary motor areas in the MS group. In the healthy control group, activity was higher during walking in all the four studied brain regions. These results confirm the role of the premotor cortices in movement planning and in modulating walking activities; they also confirm that individuals with mild MS have a similar premotor control strategy as healthy controls while performing the same physical task.

Brain activity and cortico-muscular connectivity vary during walking in correlation with different phases of the walking cycle; a mechanism that may be disrupted in individuals with incomplete spinal cord injury (iSCI). This exploratory study aims to detect brain signals during walking and determine the effect of exoskeleton-walking robot (EWR) assistance on brain activity using mobile brain imaging techniques (scalp EEG). Acquiring such knowledge in SCI is critical to the development of effective rehabilitation interventions aimed at maximizing gait function recovery. EEG data were collected from 1 able-bodied (AB) and 1 iSCI participant during walking and with and without EWR assistance (using both “Max Assist” and “Free Limb” settings). Results showed our ability to record EEG data and to measure cortico-muscular coherence correlating with walking task and to identify differences in cortical connectivity during different types of EWR assistance.