Plasticity following visual spatial working memory training: Evidence from an untrained visual spatial working memory task
Working-memory (WM), the ability to maintain and manipulate information, is a core cognitive function important for everyday life. Recent research suggests that WM is malleable and can be improved through cognitive training. Training-induced improvements have at times been shown to transfer to untra...
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Veröffentlicht in: | Cognitive Neuroscience Society ... Annual Meeting abstract program 2013-01, p.43d-43d |
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Zusammenfassung: | Working-memory (WM), the ability to maintain and manipulate information, is a core cognitive function important for everyday life. Recent research suggests that WM is malleable and can be improved through cognitive training. Training-induced improvements have at times been shown to transfer to untrained cognitive tasks, and have long lasting benefits. Neuronal changes following WM training have been found on training specific tasks, localized to regions activated by in-task performance. Previously, we showed that visual spatial WM (vsWM) training, relative to active-control (AC) training, led to decreased activation in the cognitive control network and increased activation in the default mode network, during the training task. These patterns of activation suggest that the brain is more efficient at performing the trained task following training. In the present study, we examined the neural response on an untrained vsWM task (delayed-match-to-sample task) before and after 10 hours of either vsWM training or AC training (composed of math and sentence reading tasks). Post-minus-Pre training for the high load arrays (5,6,7dots) minus control arrays, revealed greater activation for the AC>vsWM in right frontal and cingulate regions, and the left inferior-parietal, whereas vsWM>AC resulted in greater activation in bilateral striatal regions and left inferior-frontal. These results are consistent with our previous findings, but further illustrate that training related changes in neural efficiency generalize to non-trained tasks. The results support the view that WM training can improve cognitive processing on tasks that engage the same neural networks that are targeted by the training tasks. |
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ISSN: | 1096-8857 |