Excellent response inhibition is the basis for outstanding competitive athletic performance, and sleep may be an important factor affecting athletes’ response inhibition. This study investigates the effect of sleep deprivation on athletes’ response inhibition, and its differentiating effect on non-athlete controls’ performance, with the aim of helping athletes effectively improve their response inhibition ability through sleep pattern manipulation. Behavioral and event-related potential (ERP) data were collected from 36 participants (16 table tennis athletes and 20 general college students) after 36 h of sleep deprivation using ERP techniques and a stop-signal task. Sleep deprivation’s different effects on response inhibition in the two groups were explored through repeated-measures ANOVA. Behavioral data showed that in a baseline state, stop-signal response time was significantly faster in table tennis athletes than in non-athlete controls, and appeared significantly longer after sleep deprivation in both groups. ERP results showed that at baseline state, N2, ERN, and P3 amplitudes were lower in table tennis athletes than in non-athlete controls, and corresponding significant decreases were observed in non-athlete controls after 36 h of sleep deprivation. Table tennis athletes showed a decrease in P3 amplitude and no significant difference in N2 and ERN amplitudes, after 36 h of sleep deprivation compared to the baseline state. Compared to non-athlete controls, table tennis athletes had better response inhibition, and the adverse effects of sleep deprivation on response inhibition occurred mainly in the later top-down motor inhibition process rather than in earlier automated conflict detection and monitoring.

The decline in activities of daily living (ADL) significantly impacts independence and quality of life among older adults. This study used data from the China Health and Retirement Longitudinal Study (CHARLS) to conduct a cross-sectional analysis of 4,751 functionally impaired older Chinese adults aged ≥ 60 years with Modified Barthel Index (MBI) scores < 100. Participants were stratified into seven age groups (60–64, 65–69, 70–74, 75–79, 80–84, 85–89, and ≥ 90 years), and simple linear models were used to analyze age-related differences across 12 ADL domains. Results revealed three patterns of functional decline: (1) basic self-care activities (eating, getting up) remained relatively stable across age groups; (2) mobility functions (walking, stair climbing) showed progressive decline, with walking demonstrating continuous deterioration across multiple age transitions; and (3) personal care activities (bathing, grooming, toileting, dressing) showed significant decline primarily between ages 75–84. Gender-stratified analysis identified female advantages in self-care abilities and age-related changes in walking performance. The 75–84 years period emerged as a critical transition, with six functional domains showing significant deterioration. These findings suggest that interventions targeting mobility preservation and targeted interventions during the late 70s to early 80s may help delay functional decline and maintain independence in older adults.

Introduction: Visual prompts enhance motor performance in goal-directed tasks by modulating attentional resource allocation. Given that stroke patients often exhibit attentional deficits and impaired visual processing, cue-based interventions are increasingly used in neurorehabilitation. However, how different prompt types interact with attentional capacity to influence attention–motor performance remains unclear. This study aimed to examine the differential effects of static and dynamic prompts in stroke patients and healthy controls. Methods: Sustained attention was assessed using the Sustained Attention to Response Task (SART) in stroke patients and healthy controls. A virtual reality-based Target-Goal Task (TGT) was employed to compare the effects of static and dynamic prompts between groups. Results: Stroke patients showed significant impairments in attention–motor performance compared with controls. In healthy individuals, dynamic prompts were associated with faster response times, higher prefrontal oxygenated hemoglobin levels, and more efficient brain network topology (i.e., higher clustering coefficient [CC] and shorter characteristic path length [PL]), indicating enhanced attentional allocation and information integration. In contrast, stroke patients performed better under static cue conditions, possibly due to lower cognitive load demands. Discussion: The effects of visual prompts depend on sustained attention capacity. These findings highlight the importance of tailoring prompt strategies to individual cognitive profiles and provide evidence for personalized visual cue-based rehabilitation.