Influence of divergent and convergent thinking on visuomotor adaptation in young and older adults.
Visuomotor adaptation declines in older age. This has been attributed to cognitive impairments. One relevant cognitive function could be creativity, since creativity is implicated as mediator of early learning. The present study therefore evaluates whether two aspects of creativity, divergent and convergent thinking, are differentially involved in the age-dependent decline of visuomotor adaptation. In 25 young and 24 older volunteers, divergent thinking was assessed by the alternative-uses-task (AUT), convergent thinking by the Intelligenz-Struktur-Test-2000 (IST), and sensorimotor-adaptation by a pointing task with 60° rotated visual feedback. Young participants outperformed older participants in all three tasks. AUT scores were positively associated with young but not older participants' adaptive performance, whereas IST scores were negatively associated with older but not young participants' adaptive performance. This pattern of findings could be attributed to a consistent relationship between AUT, IST and adaptation; taking this into account, adaptation deficits of older participants were no longer significant. We conclude that divergent thinking supports workaround-strategies during adaptation, but doesn't influence visuomotor recalibration. Furthermore, the decay of divergent thinking in older adults may explain most of age-related decline of adaptive strategies. When the age-related decay of divergent thinking coincides with well-preserved convergent thinking, adaptation suffers most.
['Simon|Anja|A|', 'Bock|Otmar|O|']
D000223:Adaptation, Psychological D000328:Adult D000368:Aged D000375:Aging D003405:Creativity D005260:Female D006801:Humans D007361:Intelligence Tests D008297:Male D008875:Middle Aged D009483:Neuropsychological Tests D011340:Problem Solving D011597:Psychomotor Performance D013239:Stereotyped Behavior D013850:Thinking D055815:Young Adult
Convergent thinking Age-dependence Divergent thinking Motor learning