K Zwingmann1, L Hübner1, W B Verwey2,3, J S Barnhoorn2,4, B Godde5, C Voelcker-Rehage6,7. 1. Institute of Human Movement Science and Health, Chemnitz University of Technology, Chemnitz, Germany. 2. Cognitive Psychology and Ergonomics, University of Twente, Twente, The Netherlands. 3. Department of Health and Kinesiology, Texas A&M University, College Station, USA. 4. Human Behaviour & Organisational Innovation, The Netherlands Organization for Applied Scientific Research TNO, The Hague, The Netherlands. 5. Department of Psychology and Methods, Jacobs University Bremen, Bremen, Germany. 6. Institute of Human Movement Science and Health, Chemnitz University of Technology, Chemnitz, Germany. claudia.voelcker-rehage@uni-muenster.de. 7. Institute of Sport and Exercise Sciences, University of Muenster, Muenster, Germany. claudia.voelcker-rehage@uni-muenster.de.
Abstract
INTRODUCTION: Older adults show higher interindividual performance variability during the learning of new motor sequences than younger adults. It is largely unknown what factors contribute to this variability. This study aimed to, first, characterize age differences in motor sequence learning and, second, examine influencing factors for interindividual performance differences. METHOD: 30 young adults (age M = 21.89, SD = 2.08, 20 female) and 29 older adults (age M = 69.55, SD = 3.03, 18 female) participated in the study. Motor sequence learning was assessed with a discrete sequence production (DSP) task, requiring key presses to a sequence of visual stimuli. Three DSP practice phases (á 8 blocks × 16 sequences, two six-element sequences) and two transfer blocks (new untrained sequences) were performed. Older participants conducted the Mini-Mental Status Examination and a visuospatial working-memory task. All participants finished a questionnaire on everyday leisure activities and a cardiovascular fitness test. RESULTS: Performance speed increased with practice in both groups, but young improved more than older adults (significant Group × Time effect for response time, F(1,5) = 4.353, p = 0.004, [Formula: see text] = 0.071). Accuracy did not change in any age group (non-significant Group × Time effect for error rates, F(1,5) = 2.130, p = 0.091, [Formula: see text] = 0.036). Older adults revealed lower transfer costs for performance speed (significant Time × Group effect, e.g., simple sequence, F(1,2) = 10.511, p = 0.002, [Formula: see text] = 0.156). High participation in leisure time activities (β = - 0.58, p = 0.010, R2 = 0.45) and high cardiovascular fitness (β = - 0.49, p = 0.011, R2 = 0.45) predicted successful motor sequence learning in older adults. DISCUSSION: Results confirmed impaired motor learning in older adults. Younger adults seem to show a better implicit knowledge of the practiced sequences compared to older adults. Regular participation in leisure time activities and cardiovascular fitness seem to prevent age-related decline and to facilitate motor sequence performance and motor sequence learning in older adults.
INTRODUCTION: Older adults show higher interindividual performance variability during the learning of new motor sequences than younger adults. It is largely unknown what factors contribute to this variability. This study aimed to, first, characterize age differences in motor sequence learning and, second, examine influencing factors for interindividual performance differences. METHOD: 30 young adults (age M = 21.89, SD = 2.08, 20 female) and 29 older adults (age M = 69.55, SD = 3.03, 18 female) participated in the study. Motor sequence learning was assessed with a discrete sequence production (DSP) task, requiring key presses to a sequence of visual stimuli. Three DSP practice phases (á 8 blocks × 16 sequences, two six-element sequences) and two transfer blocks (new untrained sequences) were performed. Older participants conducted the Mini-Mental Status Examination and a visuospatial working-memory task. All participants finished a questionnaire on everyday leisure activities and a cardiovascular fitness test. RESULTS: Performance speed increased with practice in both groups, but young improved more than older adults (significant Group × Time effect for response time, F(1,5) = 4.353, p = 0.004, [Formula: see text] = 0.071). Accuracy did not change in any age group (non-significant Group × Time effect for error rates, F(1,5) = 2.130, p = 0.091, [Formula: see text] = 0.036). Older adults revealed lower transfer costs for performance speed (significant Time × Group effect, e.g., simple sequence, F(1,2) = 10.511, p = 0.002, [Formula: see text] = 0.156). High participation in leisure time activities (β = - 0.58, p = 0.010, R2 = 0.45) and high cardiovascular fitness (β = - 0.49, p = 0.011, R2 = 0.45) predicted successful motor sequence learning in older adults. DISCUSSION: Results confirmed impaired motor learning in older adults. Younger adults seem to show a better implicit knowledge of the practiced sequences compared to older adults. Regular participation in leisure time activities and cardiovascular fitness seem to prevent age-related decline and to facilitate motor sequence performance and motor sequence learning in older adults.
Authors: Sander M Daselaar; Serge A R B Rombouts; Dick J Veltman; Jeroen G W Raaijmakers; Cees Jonker Journal: Neurobiol Aging Date: 2003-11 Impact factor: 4.673
Authors: Nils Henrik Pixa; Lena Hübner; Dieter F Kutz; Claudia Voelcker-Rehage Journal: Int J Environ Res Public Health Date: 2021-11-27 Impact factor: 3.390