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

Ben M. Harvey, Serge O Dumoulin

    Research output: Contribution to journal/periodicalArticleScientificpeer-review

    6 Citations (Scopus)
    124 Downloads (Pure)

    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).

    Original languageEnglish
    Pages (from-to)193-205
    Number of pages13
    JournalData in Brief
    Volume16
    DOIs
    Publication statusPublished - 2018

    Keywords

    • Journal Article

    Fingerprint

    Dive into the research topics of 'Data describing the accuracy of non-numerical visual features in predicting fMRI responses to numerosity'. Together they form a unique fingerprint.

    Cite this