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    政大機構典藏 > 理學院 > 心理學系 > 期刊論文 >  Item 140.119/79375
    Please use this identifier to cite or link to this item: http://nccur.lib.nccu.edu.tw/handle/140.119/79375


    Title: Development of common neural representation for distinct numerical problems
    Authors: 張葶葶
    Chang, Ting-Ting
    Rosenberg-Lee, M.
    Metcalfe, A.W.S.
    Chen, T.
    Menon, V.
    Contributors: 心理系
    Keywords: Intraparietal sulcus;Dorsal lateral prefrontal cortex;Fusiform gyrus;Representational similarity analysis;Multivoxel representational similarity;Arithmetic;Problem solving
    Date: 2015-08
    Issue Date: 2015-11-10 16:08:09 (UTC+8)
    Abstract: How the brain develops representations for abstract cognitive problems is a major unaddressed question in neuroscience. Here we tackle this fundamental question using arithmetic problem solving, a cognitive domain important for the development of mathematical reasoning. We first examined whether adults demonstrate common neural representations for addition and subtraction problems, two complementary arithmetic operations that manipulate the same quantities. We then examined how the common neural representations for the two problem types change with development. Whole-brain multivoxel representational similarity (MRS) analysis was conducted to examine common coding of addition and subtraction problems in children and adults. We found that adults exhibited significant levels of MRS between the two problem types, not only in the intraparietal sulcus (IPS) region of the posterior parietal cortex (PPC), but also in ventral temporal-occipital, anterior temporal and dorsolateral prefrontal cortices. Relative to adults, children showed significantly reduced levels of MRS in these same regions. In contrast, no brain areas showed significantly greater MRS between problem types in children. Our findings provide novel evidence that the emergence of arithmetic problem solving skills from childhood to adulthood is characterized by maturation of common neural representations between distinct numerical operations, and involve distributed brain regions important for representing and manipulating numerical quantity. More broadly, our findings demonstrate that representational analysis provides a powerful approach for uncovering fundamental mechanisms by which children develop proficiencies that are a hallmark of human cognition.
    Relation: Neuropsychologia,75, 481-495
    Data Type: article
    DOI 連結: http://dx.doi.org/10.1016/j.neuropsychologia.2015.07.005
    DOI: 10.1016/j.neuropsychologia.2015.07.005
    Appears in Collections:[心理學系] 期刊論文

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