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Gait 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).

The 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.

As 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.

The 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.

Black older adults have a higher vascular burden compared to non‐Hispanic White (NHW) older adults, which may put them at risk for a form of depression known as vascular depression (VaDep). The literature examining VaDep in Black older adults is sparse. The current study addressed this important gap by examining whether vascular burden was associated with depressive symptoms in Black older adults.

Participants included 113 Black older adults from the Healthy Brain Project, a substudy of the Health, Aging, and Body Composition Study. In multiple regression analyses, clinical vascular burden (sum of vascular conditions) and white matter hyperintensity (WMH) volume predicted depressive symptoms as measured by the Center for Epidemiologic Studies Depression Scale, controlling for demographic variables. Follow‐up analyses compared the associations in the Black subsample and in 179 NHW older adults.

Higher total WMH volume, but not clinically‐defined vascular burden, predicted higher concurrent depressive symptoms and higher average depressive symptoms over 4 years. Similar associations were found between uncinate fasciculus (UF) WMHs and concurrent depressive symptoms and between superior longitudinal fasciculus WMHs and average depressive symptoms. The association between depressive symptoms and UF WMH was stronger in Black compared to NHW individuals.

This research is consistent with the VaDep hypothesis and extends it to Black older adults, a group that has historically been underrepresented in the literature. Results highlight WMH in the UF as particularly relevant to depressive symptoms in Black older adults and suggest this group may be particularly vulnerable to the negative effects of WMH.