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首页> 外文期刊>Cognitive, affective & behavioral neuroscience >Visuospatial referents facilitate the learning and transfer of mathematical operations: Extending the role of the angular gyrus
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Visuospatial referents facilitate the learning and transfer of mathematical operations: Extending the role of the angular gyrus

机译:Visuospatial referents facilitate the learning and transfer of mathematical operations: Extending the role of the angular gyrus

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摘要

Different external representations for learning and solving mathematical operations may affect learning and transfer. To explore the effects of learning representations, learners were each introduced to two new operations (ba dagger n and ba dagger"n) via either formulas or graphical representations. Both groups became adept at solving regular (trained) problems. During transfer, no external formulas or graphs were present; however, graph learners' knowledge could allow them to mentally associate problem expressions with visuospatial referents. The angular gyrus (AG) has recently been hypothesized to map problems to mental referents (e.g., symbolic answers; Grabner, Ansari, Koschutnig, Reishofer, Ebner Human Brain Mapping, 34, 1013-1024, 2013), and we sought to test this hypothesis for visuospatial referents. To determine whether the AG and other math (horizontal intraparietal sulcus) and visuospatial (fusiform and posterior superior parietal lobule PSPL) regions were implicated in processing visuospatial mental referents, we included two types of transfer problems, computational and relational, which differed in referential load (one graph vs. two). During solving, the activations in AG, PSPL, and fusiform reflected the referential load manipulation among graph but not formula learners. Furthermore, the AG was more active among graph learners overall, which is consistent with its hypothesized referential role. Behavioral performance was comparable across the groups on computational transfer problems, which could be solved in a way that incorporated learners' respective procedures for regular problems. However, graph learners were more successful on relational transfer problems, which assessed their understanding of the relations between pairs of similar problems within and across operations. On such problems, their behavioral performance correlated with activation in the AG, fusiform, and a relational processing region (BA 10).

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