Baillargeon, E. M. | Search bioRxiv

bioRxiv2026

Locomotor savings relies on attentional control of walking in older, but not younger adults

The ability to recall learned movements and rapidly adapt to environmental changes, known as locomotor savings, is crucial for mobility in community-dwelling older adults. However, the influence of aging on locomotor savings and the underlying mechanisms remains poorly understood. Attentional compensation is a particularly relevant mechanism because the control of automatic motor behaviors like walking tend to recruit more attentional/executive resources with aging. We hypothesize that locomotor savings is diminished with age and relies on attentional rather than automatic control of walking. To test this, we compared savings of a novel walking pattern learned on a split-belt treadmill, where each leg moves at a different speed, across multiple days in 21 older and 21 younger adults. Attentional control of walking was assessed by overground dual-task walking while prefrontal cortex (PFC) activity was recorded using functional near-infrared spectroscopy (fNIRS). We found that older adults exhibited less locomotor savings than younger adults after practice. Older adults also relied more on attentional resources during dual-task walking. Importantly, greater locomotor savings was associated with higher attentional control of walking in older adults, suggesting that the use of attentional resources during challenging walking facilitates the recall of previously learned movements. These results indicate that cognitive compensation strategies utilizing attentional resources are important neural mechanisms modulating locomotor savings. Understanding the role of cognitive compensation in locomotor savings may inform rehabilitation design to enhance mobility in older adults ensuring movement corrections practiced in clinical settings are saved for long-term benefit in daily life.

neuroscience↗

bioRxiv2023

Novel automaticity index characterizing dual task walking reveals a cognitive ability-related decline in gait automaticity.

Gait automaticity refers to the ability to walk with minimal recruitment of attentional networks typically mediated through the prefrontal cortex (PFC). Reduced gait automaticity 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 automaticity index as an analytical approach that combines changes in PFC activity with changes in DT performance to quantify gait automaticity. We validated the index 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. We found that as DT difficulty increases, more participants showed the anticipated decrease in automaticity as measured by the novel index compared to PFC activation. Furthermore, when comparing across individuals, lower cognitive function related to worse automaticity index, but not PFC activation or DT performance. In sum, the proposed index better quantified the differences in automaticity between tasks and individuals by providing a unified measure of gait automaticity 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.

neuroscience↗