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通过 fMRI 适应技术解析顶枕叶皮层中与非符号数字加工相关的阶段。

Stages of nonsymbolic number processing in occipitoparietal cortex disentangled by fMRI adaptation.

机构信息

Institutionen för Neurovetenskap, Karolinska Institute, 17177 Stockholm, Sweden.

出版信息

J Neurosci. 2011 May 11;31(19):7168-73. doi: 10.1523/JNEUROSCI.4503-10.2011.

Abstract

The neurobiological mechanisms of nonsymbolic number processing in humans are still unclear. Computational modeling proposed three successive stages: first, the spatial location of objects is stored in an object location map; second, this information is transformed into a numerical summation code; third, this summation code is transformed to a number-selective code. Here, we used fMRI-adaptation to identify these three stages and their relative anatomical location. By presenting the same number of dots on the same locations in the visual field, we adapted neurons of human volunteers. Occasionally, deviants with the same number of dots at different locations or different numbers of dots at the same location were shown. By orthogonal number and location factors in the deviants, we were able to calculate three independent contrasts, each sensitive to one of the stages. We found an occipitoparietal gradient for nonsymbolic number processing: the activation of the object location map was found in the inferior occipital gyrus. The summation coding map exhibited a nonlinear pattern of activation, with first increasing and then decreasing activation, and most activity in the middle occipital gyrus. Finally, the number-selective code became more pronounced in the superior parietal lobe. In summary, we disentangled the three stages of nonsymbolic number processing predicted by computational modeling and demonstrated that they constitute a pathway along the occipitoparietal processing stream.

摘要

人类非符号数字加工的神经生物学机制尚不清楚。计算模型提出了三个连续的阶段:首先,物体的空间位置存储在物体位置图中;其次,将此信息转换为数值求和代码;第三,将此求和代码转换为数字选择代码。在这里,我们使用 fMRI 适应来识别这三个阶段及其相对的解剖位置。通过在视野中相同的位置呈现相同数量的点,我们适应了人类志愿者的神经元。偶尔会显示具有相同数量的点在不同位置或不同数量的点在相同位置的偏差。通过在偏差中使用正交的数字和位置因子,我们能够计算出三个独立的对比,每个对比都对一个阶段敏感。我们发现了一个非符号数字处理的枕顶梯度:物体位置图的激活位于下枕叶。求和编码图显示出激活的非线性模式,首先增加然后减少,并且在中枕叶中有最多的活动。最后,数字选择代码在上顶叶变得更加明显。总之,我们解开了计算模型预测的非符号数字处理的三个阶段,并证明它们构成了沿着枕顶处理流的途径。

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