ArticleBrain and behavior2025
Time/Movement Estimation and Mental Rotation Tasks as Early Cognitive Markers in Alzheimer's Disease.
Article in Brain and behavior, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Parkinson's and Alzheimer's disease impairs temporal precision.Research square · 2026Article
- Time/Movement Estimation and Mental Rotation Tasks as Early Cognitive Markers in Alzheimer's Disease.Brain and behavior · 2025Article
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5 authors.
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Abstract
introductionCognitive impairments, including memory decline and executive dysfunction, are well-documented in Alzheimer's disease (AD); however, distortions in temporal judgment, motion perception and mental rotation in the early stages remain underexplored. Existing research has predominantly relied on verbal time-estimation tasks, with a limited investigation into alternative paradigms, such as time reproduction or bisection tasks. This study investigated the diagnostic utility of time-movement estimation and mental rotation tasks from the psychology experiment building language (PEBL) test battery for identifying early cognitive impairment. Moreover, it assessed correlations among task performance, cognitive test scores, and demographic variables.
methodsThis cross-sectional study included 28 patients with mild dementia (MD), 27 with amnestic mild cognitive impairment (MCI), and 26 with normal cognitive function as the control cohort (CC). Participants completed the mini-mental state examination, clinical dementia rating assessments, Alzheimer's disease assessment scale-cognitive subscale 13 (ADAS-Cog 13), and PEBL-based Time-Wall and mental rotation tasks.
resultsTime-Wall task inaccuracy scores exhibited strong diagnostic accuracy in distinguishing between the CC and early AD (MCI and MD), with an AUC of 0.9, and effectively differentiated CC from MCI, with an AUC of 0.86. Conversely, the mental rotation task exhibited weaker diagnostic properties, with AUC values of 0.75 for distinguishing CC from early AD and 0.71 for distinguishing CC from MCI. The multinomial logistic regression model accurately categorized 75.3% of participants (CC = 92.3%, MCI = 59.3%, and MD = 75%), utilizing demographic data and ADAS-Cog 13 and Time-Wall inaccuracy scores as predictors. Both ADAS-Cog 13 and Time-Wall task inaccuracy scores were statistically significant predictors (X
conclusionsThe Time-Wall task showed strong diagnostic utility in identifying early AD, independent of age. The mental rotation task exhibited low sensitivity and requires further investigation regarding its potential to reflect compensatory brain network functions.
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