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Bridging across cognitive training and brain plasticity: a neurally inspired computational model of interactive skill learning
Author(s) -
Fu WaiTat,
Lee Hyunkyu,
Boot Walter R.,
Kramer Arthur F.
Publication year - 2012
Publication title -
wiley interdisciplinary reviews: cognitive science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.526
H-Index - 49
eISSN - 1939-5086
pISSN - 1939-5078
DOI - 10.1002/wcs.1214
Subject(s) - cognition , cognitive psychology , context (archaeology) , psychology , cognitive training , task (project management) , transfer of learning , dreyfus model of skill acquisition , neuroplasticity , computer science , developmental psychology , neuroscience , paleontology , management , economics , biology , economic growth
This article reviews recent empirical and brain imaging data on effects of cognitive training methods on complex interactive skill learning, and presents a neurally inspired computational model that characterizes the effects of these training methods. In particular, the article focuses on research that shows that variable priority training (VPT), which requires learners to shift their priorities to different task components during training, often leads to better acquisition and retention of skills than fixed priority training (FPT). However, there is only weak evidence that shows that VPT can enhance transfer of complex interactive skills to untrained situations. Brain imaging studies show that VPT leads to significantly lower activations and a higher reduction of activities in attentional control areas after training than FPT. Research also shows that the volume of the striatum predicts the learning effects, but only in VPT. The computational model, developed based on learning mechanisms at the neural level, bridges across the empirical and the braining imaging results by explaining the effects of VPT and FPT at both the behavioral and neural levels. The results were discussed in the context of previous findings on cognitive training. WIREs Cogn Sci 2013, 4:225–236. doi: 10.1002/wcs.1214 This article is categorized under: Psychology > Learning