Enhancing Cognitive Functioning and Brain Plasticity, Volume by Wojtek J Chodzko-Zajko; Arthur F Kramer; Leonard W Poon

By Wojtek J Chodzko-Zajko; Arthur F Kramer; Leonard W Poon

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Extra resources for Enhancing Cognitive Functioning and Brain Plasticity, Volume 3

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The study revealed that each intervention improved the targeted cognitive ability compared to the baseline and control group values both on the immediate posttraining evaluation and, to a lesser extent, on the second evaluation at 24 months. Unlike Spector and colleagues (2003), Ball’s group did not find that the positive effects of cognitive training significantly generalized to improvement in everyday functioning. An earlier experimental training study by Willis and Schaie (1986), however, does provide proof that training older adults can yield generalization across cognitive skills demonstrated by SEM to belong to different latent factors.

For the younger group it was about the same size as the reciprocal effect of Substantive Complexity on Intellectual Flexibility; for the older group, it was about half the size. , Occupational Self-Direction) and full-information SEM (Schooler, Mulatu, & Oates, 2004). Leisure Complexity and Intellectual Functioning In contrast to our original analyses involving substantive complexity of paid work and intellectual flexibility (Schooler, Mulatu, & Oates, 1999), we used a full-information modeling approach in our analysis of the relationship between leisure-time activities and intellectual flexibility.

Virtually all of the training literature relies on repetition of effortful, topdown cognitive processes that have declined with age, on the assumption that repeated performance of the process will make the operation easier or more efficient to perform on a range of tasks. Another approach to improving cognitive function relies on exploiting cognitive processes that are age invariant and do not decline with age (Park, 2000). Such automatic processes (Hasher & Zacks, 1979) utilize few cognitive resources and tend to be bottom-up, data-driven processes that are activated in response to environmental cues or suggestions.

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