Exploring Electrocortical Signatures of Gait Adaptation: Differential Neural Dynamics in Slow and Fast Gait Adapters.

Individuals exhibit significant variability in their ability to adapt locomotor skills, with some adapting quickly and others more slowly. Differences in brain activity likely contribute to this variability, but direct neural evidence is lacking. We investigated individual differences in electrocortical activity that led to faster locomotor adaptation rates. We recorded high-density electroencephalography while young, neurotypical adults adapted their walking on a split-belt treadmill and grouped them based on how quickly they restored their gait symmetry. Results revealed unique spectral signatures within the posterior parietal, bilateral sensorimotor, and right visual cortices that differ between fast and slow adapters. Specifically, fast adapters exhibited lower alpha power in the posterior parietal and right visual cortices during early adaptation, associated with quicker attainment of steady-state step length symmetry. Decreased posterior parietal alpha may reflect enhanced spatial attention, sensory integration, and movement planning to facilitate faster locomotor adaptation. Conversely, slow adapters displayed greater alpha and beta power in the right visual cortex during late adaptation, suggesting potential differences in visuospatial processing. Additionally, fast adapters demonstrated reduced spectral power in the bilateral sensorimotor cortices compared with slow adapters, particularly in the theta band, which may suggest variations in perception of the split-belt perturbation. These findings suggest that alpha and beta oscillations in the posterior parietal and visual cortices and theta oscillations in the sensorimotor cortex are related to the rate of gait adaptation.

Resting state brain network segregation is associated with walking speed and working memory in older adults.

Older adults exhibit larger individual differences in walking ability and cognitive function than young adults. Characterizing intrinsic brain connectivity differences in older adults across a wide walking performance spectrum may provide insight into the mechanisms of functional decline in some older adults and resilience in others. Thus, the objectives of this study were to: (1) determine whether young adults and high- and low-functioning older adults show group differences in brain network segregation, and (2) determine whether network segregation is associated with working memory and walking function in these groups. The analysis included 21 young adults and 81 older adults. Older adults were further categorized according to their physical function using a standardized assessment; 54 older adults had low physical function while 27 were considered high functioning. Structural and functional resting state magnetic resonance images were collected using a Siemens Prisma 3T scanner. Working memory was assessed with the NIH Toolbox list sorting test. Walking speed was assessed with a 400 m-walk test at participants' self-selected speed. We found that network segregation in mobility-related networks (sensorimotor, vestibular, and visual networks) was higher in younger adults compared to older adults. There were no group differences in laterality effects on network segregation. We found multivariate associations between working memory and walking speed with network segregation scores. Higher right anterior cingulate cortex network segregation was associated with higher working memory function. Higher right sensorimotor, right vestibular, right anterior cingulate cortex, and lower left anterior cingulate cortex network segregation was associated with faster walking speed. These results are unique and significant because they demonstrate higher network segregation is largely related to higher physical function and not age alone.

Mobile neuroimaging: What we have learned about the neural control of human walking, with an emphasis on EEG-based research.

Our understanding of the neural control of human walking has changed significantly over the last twenty years and mobile brain imaging methods have contributed substantially to current knowledge. High-density electroencephalography (EEG) has the advantages of being lightweight and mobile while providing temporal resolution of brain changes within a gait cycle. Advances in EEG hardware and processing methods have led to a proliferation of research on the neural control of locomotion in neurologically intact adults. We provide a narrative review of the advantages and disadvantages of different mobile brain imaging methods, then summarize findings from mobile EEG studies quantifying electrocortical activity during human walking. Contrary to historical views on the neural control of locomotion, recent studies highlight the widespread involvement of many areas, such as the anterior cingulate, posterior parietal, prefrontal, premotor, sensorimotor, supplementary motor, and occipital cortices, that show active fluctuations in electrical power during walking. The electrocortical activity changes with speed, stability, perturbations, and gait adaptation. We end with a discussion on the next steps in mobile EEG research.

Prefrontal cortical activity during uneven terrain walking in younger and older adults.

Introduction: Walking in complex environments increases the cognitive demand of locomotor control; however, our understanding of the neural mechanisms contributing to walking on uneven terrain is limited. We used a novel method for altering terrain unevenness on a treadmill to investigate the association between terrain unevenness and cortical activity in the prefrontal cortex, a region known to be involved in various cognitive functions. Methods: Prefrontal cortical activity was measured with functional near infrared spectroscopy while participants walked on a novel custom-made terrain treadmill surface across four different terrains: flat, low, medium, and high levels of unevenness. The assessments were conducted in younger adults, older adults with better mobility function and older adults with worse mobility function. Mobility function was assessed using the Short Physical Performance Battery. The primary hypothesis was that increasing the unevenness of the terrain would result in greater prefrontal cortical activation in all groups. Secondary hypotheses were that heightened prefrontal cortical activation would be observed in the older groups relative to the younger group, and that prefrontal cortical activation would plateau at higher levels of terrain unevenness for the older adults with worse mobility function, as predicted by the Compensation Related Utilization of Neural Circuits Hypothesis. Results: The results revealed a significant main effect of terrain, indicating a significant increase in prefrontal cortical activation with increasing terrain unevenness during walking in all groups. A significant main effect of group revealed that prefrontal cortical activation was higher in older adults with better mobility function compared to younger adults and older adults with worse mobility function in all pooled terrains, but there was no significant difference in prefrontal cortical activation between older adults with worse mobility function and younger adults. Contrary to our hypothesis, the older group with better mobility function displayed a sustained increase in activation but the other groups did not, suggestive of neural compensation. Additional findings were that task-related increases in prefrontal cortical activation during walking were lateralized to the right hemisphere in older adults with better mobility function but were bilateral in older adults with worse mobility function and younger adults. Discussion: These findings support that compared to walking on a flat surface, walking on uneven terrain surfaces increases demand on cognitive control resources as measured by prefrontal cortical activation.

Dual-layer electroencephalography data during real-world table tennis.

Real-world settings are necessary to improve the ecological validity of neuroscience research, and electroencephalography (EEG) facilitates mobile electrocortical recordings because of its easy portability and high temporal resolution. Table tennis is a whole-body, goal-directed sport that requires constant visuomotor feedback, anticipation, strategic decision-making, object interception, and performance monitoring - making it an interesting testbed for a variety of neuroscience studies. Although traditionally plagued by artifact contamination, recent advances in signal processing and hardware approaches, such as the dual-layer approach, have allowed high fidelity EEG recordings during whole-body maneuvers. Here, we present a dual-layer EEG dataset from 25 healthy human participants playing table tennis with a human opponent and a ball machine. Our dataset includes synchronized, multivariate time series recordings from 120 scalp electrodes, 120 noise electrodes, 8 neck electromyography electrodes, and inertial measurement units on the participant, paddles, and ball machine to record hit events. We also include de-identified T1 anatomical MR images and digitized electrode locations to create subject-specific head models for source localization. In addition, we provide anonymized video recordings and Adobe Premiere project files with hit events labeled (originally used to mark successful/missed hits). Researchers could use the videos to mark their own events of interest. We formatted our dataset in the Brain Imaging Data Structure (BIDS) format to facilitate data reuse and to adhere to the scientific community's new organization standard.

A table tennis serve versus rally hit elicits differential hemispheric electrocortical power fluctuations.

Human visuomotor control requires coordinated interhemispheric interactions to exploit the brain's functional lateralization. In right-handed individuals, the left hemisphere (right arm) is better for dynamic control and the right hemisphere (left arm) is better for impedance control. Table tennis is a game that requires precise movements of the paddle, whole body coordination, and cognitive engagement, providing an ecologically valid way to study visuomotor integration. The sport has many different types of strokes (e.g., serve, return, and rally shots), which should provide unique cortical dynamics given differences in the sensorimotor demands. The goal of this study was to determine the hemispheric specialization of table tennis serving - a sequential, self-paced, bimanual maneuver. We used time-frequency analysis, event-related potentials, and functional connectivity measures of source-localized electrocortical clusters and compared serves with other types of shots, which varied in the types of movement required, attentional focus, and other task demands. We found greater alpha (8-12 Hz) and beta (13-30 Hz) power in the right sensorimotor cortex than in the left sensorimotor cortex, and we found a greater magnitude of spectral power fluctuations in the right sensorimotor cortex for serve hits than return or rally hits, in all right-handed participants. Surprisingly, we did not find a difference in interhemispheric functional connectivity between a table tennis serve and return or rally hits, even though a serve could arguably be a more complex maneuver. Studying real-world brain dynamics of table tennis provides insight into bilateral sensorimotor integration.NEW & NOTEWORTHY We found different spectral power fluctuations in the left and right sensorimotor cortices during table tennis serves, returns, and rallies. Our findings contribute to the basic science understanding of hemispheric specialization in a real-world context.

Individual differences in cooperative and competitive play strategies.

INTRODUCTION: Cooperation and competition are common in social interactions. It is not clear how individual differences in personality may predict performance strategies under these two contexts. We evaluated whether instructions to play cooperatively and competitively would differentially affect dyads playing a Pong video game. We hypothesized that instructions to play cooperatively would result in lower overall points scored and differences in paddle control kinematics relative to when participants were instructed to play competitively. We also predicted that higher scores in prosociality and Sportspersonship would be related to better performance during cooperative than competitive conditions. METHODS: Pairs of participants played a Pong video game under cooperative and competitive instructions. During competitive trials, participants were instructed to score more points against one another to win the game. During the cooperative trials, participants were instructed to work together to score as few points against one another as possible. After game play, each participant completed surveys so we could measure their trait prosociality and Sportspersonship. RESULTS: Condition was a significant predictor of where along the paddle participants hit the ball, which controlled ball exit angles. Specifically, during cooperation participants concentrated ball contacts on the paddle towards the center to produce more consistent rebound angles. We found a significant correlation of Sex and the average points scored by participants during cooperative games, competitive games, and across all trials. Sex was also significantly correlated with paddle kinematics during cooperative games. The overall scores on the prosociality and Sportspersonship surveys were not significantly correlated with the performance outcomes in cooperative and competitive games. The dimension of prosociality assessing empathic concern was significantly correlated with performance outcomes during cooperative video game play. DISCUSSION: No Sportspersonship survey score was able to predict cooperative or competitive game performance, suggesting that Sportspersonship personality assessments are not reliable predictors of cooperative or competitive behaviors translated to a virtual game setting. Survey items and dimensions probing broader empathic concern may be more effective predictors of cooperative and competitive performance during interactive video game play. Further testing is encouraged to assess the efficacy of prosocial personality traits as predictors of cooperative and competitive video game behavior.

iCanClean Removes Motion, Muscle, Eye, and Line-Noise Artifacts from Phantom EEG.

The goal of this study was to test a novel approach (iCanClean) to remove non-brain sources from scalp EEG data recorded in mobile conditions. We created an electrically conductive phantom head with 10 brain sources, 10 contaminating sources, scalp, and hair. We tested the ability of iCanClean to remove artifacts while preserving brain activity under six conditions: Brain, Brain + Eyes, Brain + Neck Muscles, Brain + Facial Muscles, Brain + Walking Motion, and Brain + All Artifacts. We compared iCanClean to three other methods: Artifact Subspace Reconstruction (ASR), Auto-CCA, and Adaptive Filtering. Before and after cleaning, we calculated a Data Quality Score (0-100%), based on the average correlation between brain sources and EEG channels. iCanClean consistently outperformed the other three methods, regardless of the type or number of artifacts present. The most striking result was for the condition with all artifacts simultaneously present. Starting from a Data Quality Score of 15.7% (before cleaning), the Brain + All Artifacts condition improved to 55.9% after iCanClean. Meanwhile, it only improved to 27.6%, 27.2%, and 32.9% after ASR, Auto-CCA, and Adaptive Filtering. For context, the Brain condition scored 57.2% without cleaning (reasonable target). We conclude that iCanClean offers the ability to clear multiple artifact sources in real time and could facilitate human mobile brain-imaging studies with EEG.

Visual Occlusions Result in Phase Synchrony Within Multiple Brain Regions Involved in Sensory Processing and Balance Control.

There is a need to develop appropriate balance training interventions to minimize the risk of falls. Recently, we found that intermittent visual occlusions can substantially improve the effectiveness and retention of balance beam walking practice (Symeonidou & Ferris, 2022). We sought to determine how the intermittent visual occlusions affect electrocortical activity during beam walking. We hypothesized that areas involved in sensorimotor processing and balance control would demonstrate spectral power changes and inter-trial coherence modulations after loss and restoration of vision. Ten healthy young adults practiced walking on a treadmill-mounted balance beam while wearing high-density EEG and experiencing reoccurring visual occlusions. Results revealed spectral power fluctuations and inter-trial coherence changes in the visual, occipital, temporal, and sensorimotor cortex as well as the posterior parietal cortex and the anterior cingulate. We observed a prolonged alpha increase in the occipital, temporal, sensorimotor, and posterior parietal cortex after the occlusion onset. In contrast, the anterior cingulate showed a strong alpha and theta increase after the occlusion offset. We observed transient phase synchrony in the alpha, theta, and beta bands within the sensory, posterior parietal, and anterior cingulate cortices immediately after occlusion onset and offset. Intermittent visual occlusions induced electrocortical spectral power and inter-trial coherence changes in a wide range of frequencies within cortical areas relevant for multisensory integration and processing as well as balance control. Our training intervention could be implemented in senior and rehabilitation centers, improving the quality of life of elderly and neurologically impaired individuals.

Electrical Brain Activity during Human Walking with Parametric Variations in Terrain Unevenness and Walking Speed.

Mobile brain imaging with high-density electroencephalography (EEG) can provide insight into the cortical processes involved in complex human walking tasks. While uneven terrain is common in the natural environment and poses challenges to human balance control, there is limited understanding of the supraspinal processes involved with traversing uneven terrain. The primary objective of this study was to quantify electrocortical activity related to parametric variations in terrain unevenness for neurotypical young adults. We used high-density EEG to measure brain activity when thirty-two young adults walked on a novel custom-made uneven terrain treadmill surface with four levels of difficulty at a walking speed tailored to each participant. We identified multiple brain regions associated with uneven terrain walking. Alpha (8 - 13 Hz) and beta (13 - 30 Hz) spectral power decreased in the sensorimotor and posterior parietal areas with increasing terrain unevenness while theta (4 - 8 Hz) power increased in the mid/posterior cingulate area with terrain unevenness. We also found that within stride spectral power fluctuations increased with terrain unevenness. Our secondary goal was to investigate the effect of parametric changes in walking speed (0.25 m/s, 0.5m/s, 0.75 m/s, 1.0 m/s) to differentiate the effects of walking speed from uneven terrain. Our results revealed that electrocortical activities only changed substantially with speed within the sensorimotor area but not in other brain areas. Together, these results indicate there are distinct cortical processes contributing to the control of walking over uneven terrain versus modulation of walking speed on smooth, flat terrain. Our findings increase our understanding of cortical involvement in an ecologically valid walking task and could serve as a benchmark for identifying deficits in cortical dynamics that occur in people with mobility deficits.

Electrocortical activity correlated with locomotor adaptation during split-belt treadmill walking.

Locomotor adaptation is crucial for daily gait adjustments to changing environmental demands and obstacle avoidance. Mobile brain imaging with high-density electroencephalography (EEG) now permits quantification of electrocortical dynamics during human locomotion. To determine the brain areas involved in human locomotor adaptation, we recorded high-density EEG from healthy, young adults during split-belt treadmill walking. We incorporated a dual-electrode EEG system and neck electromyography to decrease motion and muscle artefacts. Voluntary movement preparation and execution have been linked to alpha (8-13 Hz) and beta band (13-30 Hz) desynchronizations in the sensorimotor and posterior parietal cortices, whereas theta band (4-7 Hz) modulations in the anterior cingulate have been correlated with movement error monitoring. We hypothesized that relative to normal walking, split-belt walking would elicit: (1) decreases in alpha and beta band power in sensorimotor and posterior parietal cortices, reflecting enhanced motor flexibility; and (2) increases in theta band power in anterior cingulate cortex, reflecting instability and balance errors that will diminish with practice. We found electrocortical activity in multiple regions that was associated with stages of gait adaptation. Data indicated that sensorimotor and posterior parietal cortices had decreased alpha and beta band spectral power during early adaptation to split-belt treadmill walking that gradually returned to pre-adaptation levels by the end of the adaptation period. Our findings emphasize that multiple brain areas are involved in adjusting gait under changing environmental demands during human walking. Future studies could use these findings on healthy, young participants to identify dysfunctional supraspinal mechanisms that may be impairing gait adaptation. KEY POINTS: Identifying the location and time course of electrical changes in the brain correlating with gait adaptation increases our understanding of brain function and provides targets for brain stimulation interventions. Using high-density EEG in combination with 3D biomechanics, we found changes in neural oscillations localized near the sensorimotor, posterior parietal and cingulate cortices during split-belt treadmill adaptation. These findings suggest that multiple cortical mechanisms may be associated with locomotor adaptation, and their temporal dynamics can be quantified using mobile EEG. Results from this study can serve as a reference model to examine brain dynamics in individuals with movement disorders that cause gait asymmetry and reduced gait adaptation.

Practice walking on a treadmill-mounted balance beam modifies beam walking sacral movement and alters performance in other balance tasks.

The goals of this study were to determine if a single 30-minute session of practice walking on a treadmill mounted balance beam: 1) altered sacral marker movement kinematics during beam walking, and 2) affected measures of balance during treadmill walking and standing balance. Two groups of young, healthy human subjects practiced walking on a treadmill mounted balance beam for thirty minutes. One group trained with intermittent visual occlusions and the other group trained with unperturbed vision. We hypothesized that the subjects would show changes in sacrum movement kinematics after training and that there would be group differences due to larger improvements in beam walking performance by the visual occlusions group. We also investigated if there was any balance transfer from training on the beam to treadmill walking (margin of stability) and to standing static balance (center of pressure excursion). We found significant differences in sacral marker maximal velocity after training for both groups, but no significant differences between the two groups from training. There was limited evidence of balance transfer from beam-walking practice to gait margin of stability for treadmill walking and for single leg standing balance, but not for tandem stance balance. The number of step-offs while walking on a narrow beam had the largest change with training (partial η2 = 0.7), in accord with task specificity. Other balance metrics indicative of transfer had lower effect sizes (partial η2<0.5). Given the limited transfer across balance training tasks, future work should examine how intermittent visual occlusions during multi-task training improve real world functional outcomes.

Comparison of EEG Source Localization Using Simplified and Anatomically Accurate Head Models in Younger and Older Adults.

Accuracy of electroencephalography (EEG) source localization relies on the volume conduction head model. A previous analysis of young adults has shown that simplified head models have larger source localization errors when compared with head models based on magnetic resonance images (MRIs). As obtaining individual MRIs may not always be feasible, researchers often use generic head models based on template MRIs. It is unclear how much error would be introduced using template MRI head models in older adults that likely have differences in brain structure compared to young adults. The primary goal of this study was to determine the error caused by using simplified head models without individual-specific MRIs in both younger and older adults. We collected high-density EEG during uneven terrain walking and motor imagery for 15 younger (22±3 years) and 21 older adults (74±5 years) and obtained [Formula: see text]-weighted MRI for each individual. We performed equivalent dipole fitting after independent component analysis to obtain brain source locations using four forward modeling pipelines with increasing complexity. These pipelines included: 1) a generic head model with template electrode positions or 2) digitized electrode positions, 3) individual-specific head models with digitized electrode positions using simplified tissue segmentation, or 4) anatomically accurate segmentation. We found that when compared to the anatomically accurate individual-specific head models, performing dipole fitting with generic head models led to similar source localization discrepancies (up to 2 cm) for younger and older adults. Co-registering digitized electrode locations to the generic head models reduced source localization discrepancies by  âˆ¼  6 mm. Additionally, we found that source depths generally increased with skull conductivity for the representative young adult but not as much for the older adult. Our results can help inform a more accurate interpretation of brain areas in EEG studies when individual MRIs are unavailable.

A Human Lower Limb Mechanical Phantom for the Testing of Knee Exoskeletons.

The development of assistive lower-limb exoskeletons can be time-consuming. Testing prototype medical devices on vulnerable populations such as children also has safety concerns. Mechanical phantoms replicating the lower-limb kinematics provide an alternative for the fast validation and iteration of exoskeletons. However, most phantoms treat the limbs as rigid bodies and fail to capture soft tissue deformation at the human/exoskeleton interface. Human soft tissue can absorb and dissipate energy when compressed, leading to a mismatch between simulated and human exoskeleton testing outcomes. We have developed a methodology for quickly testing and validating the performance of knee exoskeletons using a mechanical phantom capable of emulating knee kinematics soft-tissue deformation of the lower-limb. Our phantom consisted of 3D-printed bones surrounded by ballistic gel. A motorized hexapod moved the knee to follow a walking trajectory. A custom inverse dynamics model estimated the knee assistance moment from marker and load cell data. We applied this methodology to quantify the effects of soft-tissue deformation on exoskeleton assistance by loading the phantom knee with a torsional spring exoskeleton interfacing and bypassing the ballistic gel. We found that including soft-tissue deformation led to a lower knee assistance moment and stiffness. Some but not all of this difference could be explained by the deflection of the exoskeleton relative to the knee angle, suggesting energy absorption within soft tissue. The direct measurements of exoskeleton assistance provide insight into increasing the assistive moment transmission efficacy. The phantom provided a relatively accurate framework for knee exoskeleton testing, aiding future exoskeleton design.

Parieto-Occipital Electrocortical Dynamics during Real-World Table Tennis.

Traditional human electroencephalography (EEG) experiments that study visuomotor processing use controlled laboratory conditions with limited ecological validity. In the real world, the brain integrates complex, dynamic, multimodal visuomotor cues to guide the execution of movement. The parietal and occipital cortices are especially important in the online control of goal-directed actions. Table tennis is a whole-body, responsive activity requiring rapid visuomotor integration that presents a myriad of unanswered neurocognitive questions about brain function during real-world movement. The aim of this study was to quantify the electrocortical dynamics of the parieto-occipital cortices while playing a sport with high-density electroencephalography. We included analysis of power spectral densities (PSDs), event-related spectral perturbations, intertrial phase coherences (ITPCs), event-related potentials (ERPs), and event-related phase coherences of parieto-occipital source-localized clusters while participants played table tennis with a ball machine and a human. We found significant spectral power fluctuations in the parieto-occipital cortices tied to hit events. Ball machine trials exhibited more fluctuations in θ power around hit events, an increase in intertrial phase coherence and deflection in the event-related potential, and higher event-related phase coherence between parieto-occipital clusters as compared with trials with a human. Our results suggest that sport training with a machine elicits fundamentally different brain dynamics than training with a human.

EMG-informed neuromuscular model assesses the effects of varied bodyweight support on muscles during overground walking.

Bodyweight supported walking is a common gait rehabilitation method that can be used as an experimental approach to better understand walking biomechanics. Neuromuscular modeling can provide an analytical means to gain insight into how muscles coordinate to produce walking and other movements. To better understand how muscle length and velocity affect muscle force during overground walking with bodyweight support, we used an electromyography (EMG)-informed neuromuscular model to investigate changes in muscle parameters (muscle force, activation and fiber length) at varying bodyweight support levels: 0%, 24%, 45% and 69% bodyweight. Coupled constant force springs provided a vertical support force while we collected biomechanical data (EMG, motion capture and ground reaction forces) from healthy, neurologically intact participants walking at 1.20 ± 0.06 m/s. The lateral and medial gastrocnemius demonstrated a significant decrease in muscle force (lateral: p = 0.002 and medial: p < 0.001) and activation (lateral: p = 0.007 and medial: p < 0.001) through push-off at higher levels of support. The soleus, in contrast, had no significant change in muscle activation through push-off (p = 0.652) regardless of bodyweight support level even though soleus muscle force decreased with increasing support (p < 0.001). During push-off, the soleus had shorter muscle fiber lengths and faster shortening velocities as bodyweight support levels increased. These results provide insight into how muscle force can be decoupled from effective bodyweight during bodyweight supported walking due to changes in muscle fiber dynamics. The findings contribute evidence that clinicians and biomechanists should not expect a reduction in muscle activation and force when using bodyweight support to assist gait during rehabilitation.

Uneven terrain versus dual-task walking: differential challenges imposed on walking behavior in older adults are predicted by cognitive and sensorimotor function.

Aging is associated with declines in walking function. To understand these mobility declines, many studies have obtained measurements while participants walk on flat surfaces in laboratory settings during concurrent cognitive task performance (dual-tasking). This may not adequately capture the real-world challenges of walking at home and around the community. Here, we hypothesized that uneven terrains in the walking path impose differential changes to walking speed compared to dual-task walking. We also hypothesized that changes in walking speed resulting from uneven terrains will be better predicted by sensorimotor function than cognitive function. Sixty-three community-dwelling older adults (65-93 yrs old) performed overground walking under varying walking conditions. Older adults were classified into two mobility function groups based on scores of the Short Physical Performance Battery. They performed uneven terrain walking across four surface conditions (Flat, Low, Medium, and High unevenness) and performed single and verbal dual-task walking on flat ground. Participants also underwent a battery of cognitive (cognitive flexibility, working memory, inhibition) and sensorimotor testing (grip strength, 2-pt discrimination, pressure pain threshold). Our results showed that walking speed decreased during both dual-task walking and across uneven terrain walking conditions compared to walking on flat terrain. Participants with lower mobility function had even greater decreases in uneven terrain walking speeds. The change in uneven terrain speed was associated with attention and inhibitory function. Changes in both dual-task and uneven terrain walking speeds were associated with 2-point tactile discrimination. This study further documents associations between mobility, executive functions, and somatosensation, highlights the differential costs to walking imposed by uneven terrains, and identifies that older adults with lower mobility function are more likely to experience these changes to walking function.

iCanClean Improves Independent Component Analysis of Mobile Brain Imaging with EEG.

Motion artifacts hinder source-level analysis of mobile electroencephalography (EEG) data using independent component analysis (ICA). iCanClean is a novel cleaning algorithm that uses reference noise recordings to remove noisy EEG subspaces, but it has not been formally tested in a parameter sweep. The goal of this study was to test iCanClean's ability to improve the ICA decomposition of EEG data corrupted by walking motion artifacts. Our primary objective was to determine optimal settings and performance in a parameter sweep (varying the window length and r2 cleaning aggressiveness). High-density EEG was recorded with 120 + 120 (dual-layer) EEG electrodes in young adults, high-functioning older adults, and low-functioning older adults. EEG data were decomposed by ICA after basic preprocessing and iCanClean. Components well-localized as dipoles (residual variance < 15%) and with high brain probability (ICLabel > 50%) were marked as 'good'. We determined iCanClean's optimal window length and cleaning aggressiveness to be 4-s and r2 = 0.65 for our data. At these settings, iCanClean improved the average number of good components from 8.4 to 13.2 (+57%). Good performance could be maintained with reduced sets of noise channels (12.7, 12.2, and 12.0 good components for 64, 32, and 16 noise channels, respectively). Overall, iCanClean shows promise as an effective method to clean mobile EEG data.

Neuromechanical Adaptation to Walking With Electromechanical Ankle Exoskeletons Under Proportional Myoelectric Control.

OBJECTIVE: To determine if robotic ankle exoskeleton users decrease triceps surae muscle activity when using proportional myoelectric control, we studied healthy young participants walking with commercially available electromechanical ankle exoskeletons (Dephy Exoboot) with a novel controller. The vast majority of robotic lower limb exoskeletons do not have direct neural input from the user which makes adaptation of exoskeleton dynamics based on user intent difficult. Proportional myoelectric control has proven to allow considerable adaptation in muscle activation and gait kinematics in pneumatic, tethered ankle exoskeletons. In this study we quantified the changes in muscle activity and joint biomechanics of twelve participants walking for 30 minutes on a treadmill. RESULTS: The exoskeletons provided 29% of the peak total ankle power and 18% of the peak total ankle moment by the end of the practice session. There was a decrease of 12% in soleus, 17% in lateral gastrocnemius and 5% in medial gastrocnemius electromyography (EMG) root mean square (root mean squared) after walking with the exoskeleton for 30 minutes compared to not wearing the exoskeleton, but this difference was not statistically significant. There were no differences in joint biomechanics of the ankle, hip, or knee between the end of training compared to walking without the exoskeletons. CONCLUSIONS: Contrary to expectations, triceps surae muscle activity showed only small non-significant decreases in 30 minutes of walking with portable, electromechanical ankle exoskeletons under proportional myoelectric control. The commercially available ankle exoskeletons were likely too weak to produce a statistically meaningful decline in triceps surae recruitment. Future research should include a wider variety of tasks, including measurements of metabolic energy expenditure, and provide a longer period of adaptation to evaluate the ankle exoskeletons.