Faculty of Psychology and Education Sciences, University of Coimbra, Rua do Colégio Novo, 3001-802 Coimbra, Portugal; Experimental Psychology, Helmholtz Institute, Utrecht University, Heidelberglaan 1, Utrecht 3584 CS, Netherlands.
Experimental Psychology, Helmholtz Institute, Utrecht University, Heidelberglaan 1, Utrecht 3584 CS, Netherlands; Spinoza Centre for Neuroimaging, Amsterdam, Netherlands.
Neuroimage. 2017 Apr 1;149:200-209. doi: 10.1016/j.neuroimage.2017.02.012. Epub 2017 Feb 7.
Humans and many animals can distinguish between stimuli that differ in numerosity, the number of objects in a set. Human and macaque parietal lobes contain neurons that respond to changes in stimulus numerosity. However, basic non-numerical visual features can affect neural responses to and perception of numerosity, and visual features often co-vary with numerosity. Therefore, it is debated whether numerosity or co-varying low-level visual features underlie neural and behavioral responses to numerosity. To test the hypothesis that non-numerical visual features underlie neural numerosity responses in a human parietal numerosity map, we analyze responses to a group of numerosity stimulus configurations that have the same numerosity progression but vary considerably in their non-numerical visual features. Using ultra-high-field (7T) fMRI, we measure responses to these stimulus configurations in an area of posterior parietal cortex whose responses are believed to reflect numerosity-selective activity. We describe an fMRI analysis method to distinguish between alternative models of neural response functions, following a population receptive field (pRF) modeling approach. For each stimulus configuration, we first quantify the relationships between numerosity and several non-numerical visual features that have been proposed to underlie performance in numerosity discrimination tasks. We then determine how well responses to these non-numerical visual features predict the observed fMRI responses, and compare this to the predictions of responses to numerosity. We demonstrate that a numerosity response model predicts observed responses more accurately than models of responses to simple non-numerical visual features. As such, neural responses in cognitive processing need not reflect simpler properties of early sensory inputs.
人类和许多动物能够区分刺激的数量，即集合中的物体数量。人类和猕猴的顶叶包含对刺激数量变化做出反应的神经元。然而，基本的非数值视觉特征会影响对数量的神经反应和感知，并且视觉特征通常与数量相关。因此，人们争论的是数量还是数量相关的低水平视觉特征是对数量的神经和行为反应的基础。为了测试非数值视觉特征是人类顶叶数量图中神经数量反应的基础这一假设，我们分析了一组具有相同数量进展但在非数值视觉特征上差异很大的数量刺激配置的反应。使用超高场 (7T) fMRI，我们测量了后顶叶皮层中一个区域对这些刺激配置的反应，据信该区域的反应反映了数量选择性活动。我们描述了一种 fMRI 分析方法，用于在遵循群体感受野 (pRF) 建模方法的情况下，区分神经反应函数的替代模型。对于每个刺激配置，我们首先量化了数量和几个被提出的非数量视觉特征之间的关系，这些特征被认为是数量辨别任务表现的基础。然后，我们确定对这些非数值视觉特征的反应在多大程度上可以预测观察到的 fMRI 反应，并将其与对数量的反应的预测进行比较。我们证明，数量反应模型比对简单非数值视觉特征的反应模型更准确地预测观察到的反应。因此，认知处理中的神经反应不一定反映早期感觉输入的更简单属性。
