| Autor: |
Borghesi F; Department of Psychology, University of Turin, Via Verdi 10, 10124 Turin, Italy., Chirico A; Department of Psychology, Research Center in Communication Psychology, Universitá Cattolica del Sacro Cuore, 20123 Milan, Italy., Pedroli E; Faculty of Psychology, eCampus University, 22060 Novedrate, Italy.; Department of Geriatrics and Cardiovascular Medicine, IRCCS Istituto Auxologico Italiano, 20149 Milan, Italy., Cipriani GE; Department of Psychology, University of Turin, Via Verdi 10, 10124 Turin, Italy., Canessa N; ICoN Center, Scuola Universitaria Superiore IUSS, 27100 Pavia, Italy.; Istituti Clinici Scientifici Maugeri IRCCS, Cognitive Neuroscience Laboratory of Pavia Institute, 27100 Pavia, Italy., Amanzio M; Department of Psychology, University of Turin, Via Verdi 10, 10124 Turin, Italy., Cipresso P; Department of Psychology, University of Turin, Via Verdi 10, 10124 Turin, Italy.; Istituto Auxologico Italiano, IRCCS, 20145 Milan, Italy. |
| Abstrakt: |
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. |
