ArticleSensors (Basel, Switzerland)2023
Exploring Biomarkers of Mental Flexibility in Healthy Aging: A Computational Psychometric Study.
Article in Sensors (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 13 citations in OpenAlex.
- Machine Learning Approaches for Optimizing Drug Combinations in Neurodegenerative Diseases: A Brief Review.ACS omega · 2025Review
- A stochastic model for affect dynamics: methodological insights from heart rate variability in an illustrative case of Anorexia Nervosa.Frontiers in psychiatry · 2025Article
- Article
- Mind and body connection in expert meditators: a computational study based on central and peripheral nervous system.BMC complementary medicine and therapies · 2024Article
- Cognitive inflexibility, obsessive-compulsive symptoms and traits and poor post-pandemic adjustment.Neuroscience applied · 2024Review
- Mental flexibility assessment: A research protocol for patients with Parkinson's Disease and Anorexia Nervosa.PloS one · 2023Article
- Outlining a novel psychometric model of mental flexibility and affect dynamics.Frontiers in psychology · 2023Review
Corrections and comments
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Authors and funding
7 authors at 5 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Mental flexibility (MF) has long been defined as cognitive flexibility. Specifically, it has been mainly studied within the executive functions domain. However, there has recently been increased attention towards its affective and physiological aspects. As a result, MF has been described as an ecological and cross-subject skill consisting of responding variably and flexibly to environmental cognitive-affective demands. Cross-sectional studies have mainly focused on samples composed of healthy individual and of patients with chronic conditions such as Mild Cognitive Impairment and Parkinson's, emphasizing their behavioral rigidity. Our study is the first to consider a sample of healthy older subjects and to outline physiological and psychological markers typical of mental flexibility, to identify functional biomarkers associated with successful aging. Our results reveal that biomarkers (respiratory and heart rate variability assessments) distinguished between individuals high vs. low in mental flexibility more reliably than traditional neuropsychological tests. This unveiled the multifaceted nature of mental flexibility composed of both cognitive and affective aspects, which emerged only if non-linear multi-variate analytic approaches, such as Supervised Machine Learning, were used.
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Registered trials
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