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Walking patterns are adaptable in response to different environmental demands, which requires neural input from spinal and supraspinal structures. With an increase in age, there are changes in walking adaptation and in the neural control of locomotion, but the age-related changes in the neural control of locomotor adaptation is unclear. The purpose of this narrative review is to establish a framework where the age-related changes of neural control of human locomotor adaptation can be understood in terms of reactive feedback and predictive feedforward control driven by sensory feedback during locomotion. We parse out the effects of aging on (a) reactive adaptation to split-belt walking, (b) predictive adaptation to split-belt walking, (c) reactive visuomotor adaptation, and (d) predictive visuomotor adaptation, and hypothesize that specific neural circuits are influenced differentially with age, which influence locomotor adaptation. The differences observed in the age-related changes in walking adaptation across different locomotor adaptation paradigms will be discussed in light of the age-related changes in the neural mechanisms underlying locomotion. [ABSTRACT FROM AUTHOR]

Fast treadmill walking combined with functional electrical stimulation to ankle muscles (FastFES) is a well-studied gait intervention that improves post-stroke walking function. Although individualized verbal feedback is commonly incorporated during clinical gait training, and a variable practice structure is posited to enhance learning, the influence of these two factors on motor learning during locomotor interventions such as FastFES is poorly understood. To determine if the addition of individualized verbal feedback or variable practice to a FastFES training session enhances motor learning of targeted gait patterns. Nine individuals with post-stroke hemiparesis completed a crossover study comprising exposure to 3 dose-matched types of gait training: (1) FastFES (FF), comprising five 6-minute bouts of training with intermittent FES, (2) FF with addition of individualized verbal instructions and faded feedback delivered by a physical therapist (FF+PT), (3) FF with variable gait speed and FES timing (FF+Var). Gait biomechanics data were collected before (Pre), immediately after (Post), and 24-h following (Retention) each training type. Within-session and retention change scores of 3 targeted gait variables were calculated to assess locomotor learning. FF+PT resulted in larger improvements within-session and at retention in trailing limb angle, and a trend for larger improvements in paretic pushoff compared to FF. FF+Var failed to show greater learning of biomechanical variables compared to FF. Addition of individualized verbal feedback (FF+PT) to a single session of gait training may enhance within- and across-session learning of targeted gait variables in people post-stroke, and merits more investigation. [ABSTRACT FROM AUTHOR]

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., Competing Interests: Disclosure of competing interests: None.

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  ∼  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.