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Statsenko Y, Habuza T, Gorkom KNV, Zaki N, Almansoori TM, Al Zahmi F, Ljubisavljevic MR, Belghali M. Proportional Changes in Cognitive Subdomains During Normal Brain Aging. Front Aging Neurosci 2021; 13:673469. [PMID: 34867263 PMCID: PMC8634589 DOI: 10.3389/fnagi.2021.673469] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2021] [Accepted: 09/20/2021] [Indexed: 11/13/2022] Open
Abstract
Background: Neuroscience lacks a reliable method of screening the early stages of dementia. Objective: To improve the diagnostics of age-related cognitive functions by developing insight into the proportionality of age-related changes in cognitive subdomains. Materials and Methods: We composed a battery of psychophysiological tests and collected an open-access psychophysiological outcomes of brain atrophy (POBA) dataset by testing individuals without dementia. To extend the utility of machine learning (ML) classification in cognitive studies, we proposed estimates of the disproportional changes in cognitive functions: an index of simple reaction time to decision-making time (ISD), ISD with the accuracy performance (ISDA), and an index of performance in simple and complex visual-motor reaction with account for accuracy (ISCA). Studying the distribution of the values of the indices over age allowed us to verify whether diverse cognitive functions decline equally throughout life or there is a divergence in age-related cognitive changes. Results: Unsupervised ML clustering shows that the optimal number of homogeneous age groups is four. The sample is segregated into the following age-groups: Adolescents ∈ [0, 20), Young adults ∈ [20, 40), Midlife adults ∈ [40, 60) and Older adults ≥60 year of age. For ISD, ISDA, and ISCA values, only the median of the Adolescents group is different from that of the other three age-groups sharing a similar distribution pattern (p > 0.01). After neurodevelopment and maturation, the indices preserve almost constant values with a slight trend toward functional decline. The reaction to a moving object (RMO) test results (RMO_mean) follow another tendency. The Midlife adults group's median significantly differs from the remaining three age subsamples (p < 0.01). No general trend in age-related changes of this dependent variable is observed. For all the data (ISD, ISDA, ISCA, and RMO_mean), Levene's test reveals no significant changes of the variances in age-groups (p > 0.05). Homoscedasticity also supports our assumption about a linear dependency between the observed features and age. Conclusion: In healthy brain aging, there are proportional age-related changes in the time estimates of information processing speed and inhibitory control in task switching. Future studies should test patients with dementia to determine whether the changes of the aforementioned indicators follow different patterns.
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Affiliation(s)
- Yauhen Statsenko
- Department of Radiology, College of Medicine and Health Sciences, United Arab Emirates University, Al Ain, United Arab Emirates.,Big Data Analytics Center, United Arab Emirates University, Al Ain, United Arab Emirates
| | - Tetiana Habuza
- Big Data Analytics Center, United Arab Emirates University, Al Ain, United Arab Emirates.,Department of Computer Science and Software Engineering, College of Information Technology, United Arab Emirates University, Al Ain, United Arab Emirates
| | - Klaus Neidl-Van Gorkom
- Department of Radiology, College of Medicine and Health Sciences, United Arab Emirates University, Al Ain, United Arab Emirates
| | - Nazar Zaki
- Big Data Analytics Center, United Arab Emirates University, Al Ain, United Arab Emirates.,Department of Computer Science and Software Engineering, College of Information Technology, United Arab Emirates University, Al Ain, United Arab Emirates
| | - Taleb M Almansoori
- Department of Radiology, College of Medicine and Health Sciences, United Arab Emirates University, Al Ain, United Arab Emirates
| | - Fatmah Al Zahmi
- Department of Neurology, Mediclinic Middle East Parkview Hospital, Dubai, United Arab Emirates.,Department of Clinical Science, Mohammed Bin Rashid University of Medicine and Health Sciences, Dubai, United Arab Emirates
| | - Milos R Ljubisavljevic
- Department of Radiology, College of Medicine and Health Sciences, United Arab Emirates University, Al Ain, United Arab Emirates
| | - Maroua Belghali
- College of Education, United Arab Emirates University, Al Ain, United Arab Emirates
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