Harvey Ben M, Dumoulin Serge O
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, The Netherlands.
Data Brief. 2017 Nov 9;16:193-205. doi: 10.1016/j.dib.2017.11.022. eCollection 2018 Feb.
Here we took several stimulus configurations that have the same numerosity progression but vary considerably in their non-numerical visual features. We collected responses to these stimuli using ultra-high-field (7T) fMRI in a posterior parietal area that responds to changes in these stimuli. We first quantify the relationships between numerosity and several non-numerical visual features in each stimulus configuration. We then use population receptive field (pRF) modeling to quantify how well responses to each of these visual features predicts the observed responses to each stimulus configuration, and observed responses to all stimulus configurations together. We compare the predictive accuracy of responses to numerosity and to non-numerical visual features in explaining the observed responses. This provides the details of the analysis outcomes summarized in an accompanying article (10.1016/j.neuroimage.2017.02.012, NIMG-16-1350).
在这里，我们采用了几种具有相同数量级进展但非数字视觉特征差异很大的刺激配置。我们使用超高场（7T）功能磁共振成像（fMRI）在顶叶后部区域收集对这些刺激的反应，该区域对这些刺激的变化有反应。我们首先量化每种刺激配置中数量与几种非数字视觉特征之间的关系。然后，我们使用群体感受野（pRF）建模来量化对每种视觉特征的反应在多大程度上能够预测对每种刺激配置的观察反应，以及对所有刺激配置的共同观察反应。我们比较了数量反应和非数字视觉特征反应在解释观察反应方面的预测准确性。这提供了一篇配套文章（10.1016/j.neuroimage.2017.02.012，NIMG - 16 - 1350）中总结的分析结果的详细信息。
