Search for: All records

IntroductionGait automaticity refers to the ability to walk with minimal recruitment of attentional networks typically mediated through the prefrontal cortex (PFC). Reduced gait automaticity (i.e., greater use of attentional resources during walking) is common with aging, contributing to an increased risk of falls and reduced quality of life. A common assessment of gait automaticity involves examining PFC activation using near-infrared spectroscopy (fNIRS) during dual-task (DT) paradigms, such as walking while performing a cognitive task. However, neither PFC activity nor task performance in isolation measures automaticity accurately. For example, greater PFC activation could be interpreted as worse gait automaticity when accompanied by poorer DT performance, but when accompanied by better DT performance, it could be seen as successful compensation. Thus, there is a need to incorporate behavioral performance and PFC measurements for a more comprehensive evaluation of gait automaticity. To address this need, we propose a novel attentional gait index as an analytical approach that combines changes in PFC activity with changes in DT performance to quantify automaticity, where a reduction in automaticity will be reflected as an increased need for attentional gait control (i.e., larger index). MethodsThe index was validated in 173 participants (≥65 y/o) who completed DTs with two levels of difficulty while PFC activation was recorded with fNIRS. The two DTs consisted of reciting every other letter of the alphabet while walking over either an even or uneven surface. ResultsAs DT difficulty increases, more participants showed the anticipated increase in the attentional control of gait (i.e., less automaticity) as measured by the novel index compared to PFC activation. Furthermore, when comparing across individuals, lower cognitive function was related to higher attentional gait index, but not PFC activation or DT performance. ConclusionThe proposed index better quantified the differences in attentional control of gait between tasks and individuals by providing a unified measure that includes both brain activation and performance. This new approach opens exciting possibilities to assess participant-specific deficits and compare rehabilitation outcomes from gait automaticity interventions. 

Abstract Background Asymmetric gait post-stroke is associated with decreased mobility, yet individuals with chronic stroke often self-select an asymmetric gait despite being capable of walking more symmetrically. The purpose of this study was to test whether self-selected asymmetry could be explained by energy cost minimization. We hypothesized that short-term deviations from self-selected asymmetry would result in increased metabolic energy consumption, despite being associated with long-term rehabilitation benefits. Other studies have found no difference in metabolic rate across different levels of enforced asymmetry among individuals with chronic stroke, but used methods that left some uncertainty to be resolved. Methods In this study, ten individuals with chronic stroke walked on a treadmill at participant-specific speeds while voluntarily altering step length asymmetry. We included only participants with clinically relevant self-selected asymmetry who were able to significantly alter asymmetry using visual biofeedback. Conditions included targeting zero asymmetry, self-selected asymmetry, and double the self-selected asymmetry. Participants were trained with the biofeedback system in one session, and data were collected in three subsequent sessions with repeated measures. Self-selected asymmetry was consistent across sessions. A similar protocol was conducted among unimpaired participants. Results Participants with chronic stroke substantially altered step length asymmetry using biofeedback, but this did not affect metabolic rate (ANOVA, p  = 0.68). In unimpaired participants, self-selected step length asymmetry was close to zero and corresponded to the lowest metabolic energy cost (ANOVA, p  = 6e-4). While the symmetry of unimpaired gait may be the result of energy cost minimization, self-selected step length asymmetry in individuals with chronic stroke cannot be explained by a similar least-effort drive. Conclusions Interventions that encourage changes in step length asymmetry by manipulating metabolic energy consumption may be effective because these therapies would not have to overcome a metabolic penalty for altering asymmetry. 

Abstract Successful motor control requires accurate estimation of our body in space for planning, executing, and evaluating the outcome of our actions. It has been shown that the estimation of limb position is susceptible to motor adaptation. However, a similar effect has not been found in locomotion, possibly due to how it was tested. We hypothesized that split-belt walking with the legs moving at different speeds changes the estimation of the legs’ position when taking a step. Thus, we assessed young subjects’ perception of step length (i.e., inter-feet distance at foot landing) when they moved their legs (active perception) or when the legs were moved by the experimenter (passive perception). We found that the active perception of step length was substantially altered following split-belt walking, whereas passive perception exhibited minor changes. This suggests that split-belt walking induced the adaptation of efferent signals, without altering sensory signals. We also found that active perceptual shifts were sensitive to how they were tested: they were most salient in the trailing leg and at short step lengths. Our results suggest that split-belt walking could modulate the deficient perception of step length post-stroke, which may contribute to gait asymmetries impairing patients’ mobility.