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Cognitive resource allocation for neural activity underlying mathematical cognition: a multi-method study

机译:基于数学认知的神经活动的认知资源分配:多方法研究

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摘要

Mathematical cognition requires the allocation of computation resources, where math-specific computations are assumed to take place in the parietal cortex and math-supportive computations in the frontal cortex. Because the pupil dilation has a higher temporal resolution than functional MRI (fMRI), the study investigated to which extent the pupil dilation can help to identify cognitive resource allocation for neural activity underlying math-specific and math-supportive cognition. Combining pupillometry and event-related fMRI, we administered a multiplication verification paradigm to 15 healthy participants asking them to solve easy, moderate, and difficult multiplication tasks. The results revealed that (1) behavioral and pupil dilation data increased parametrically with task difficulty; (2) mental multiplication with increasing difficulty recruited a fronto-parietal circuit comprising left pre-supplementary motor area, left precentral gyrus, right dorsolateral prefrontal cortex, and bilateral intraparietal sulcus (IPS); and (3) pupil dilation was sensitive to cognitive resource allocation for neural activity underlying math-specific cognition in the bilateral IPS, implicating a strong reliance on numerical quantity processing during multiplication. In conclusion, the pupil dilation could be used in mathematics education as an easily acquired peripheral physiological indicator (without relying on fMRI) that might lead to a better understanding of dynamical changes in learning arithmetic abilities as a function of training, experience, and development. On a broader level, its application allows to obtain useful insights into learning disabilities such as dyscalculia, and further improve rehabilitation programs with appropriate intervention structures.
机译:数学认知需要分配计算资源,其中假定特定数学计算在顶叶皮层中进行,而数学支持计算在额叶皮层中进行。由于瞳孔扩张的时间分辨率高于功能性MRI(fMRI),因此该研究调查了瞳孔扩张在多大程度上可以帮助识别针对特定于数学和数学支持的认知的神经活动的认知资源分配。结合瞳孔测量和事件相关的功能磁共振成像,我们对15名健康参与者进行了乘法验证范例,要求他们解决简单,中等和困难的乘法任务。结果表明:(1)行为和瞳孔扩张数据随着任务难度而参数增加; (2)难度不断增加的智力增生募集了额叶顶上回路,包括额叶前辅助运动区,左前中枢回,右前外侧前额叶皮层和双侧顶内沟(IPS); (3)瞳孔扩大对双侧IPS中基于数学特定认知的神经活动的认知资源分配敏感,暗示在乘法过程中强烈依赖数值处理。总之,瞳孔扩张可以在数学教育中用作容易获得的外围生理指标(不依赖fMRI),从而可以更好地理解学习算术能力随训练,经验和发展而变化的动态变化。在更广泛的层面上,它的应用可以使人们获得对学习障碍(例如运动障碍)的有用见解,并通过适当的干预结构进一步改善康复计划。

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