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Data describing the accuracy of non-numerical visual features in predicting fMRI responses to numerosity.

ABSTRACT: 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).

SUBMITTER: Harvey BM

PROVIDER: S-EPMC5702870 | biostudies-other | 2018 Feb

REPOSITORIES: biostudies-other

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Data describing the accuracy of non-numerical visual features in predicting fMRI responses to numerosity.

Harvey Ben M BM Dumoulin Serge O SO

Data in brief 20171109

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 re ...[more]

PMID: 29201986

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