Data and Code: Neural representations of non-symbolic magnitudes show familial specificity in the right intraparietal sulcus

Here we provide anonymized behavioral data, individual beta maps and anatomical maps as well as analyses code used in "Neural representations of non-symbolic magnitudes show familial specificity in the right intraparietal sulcus". Because of anonymization concerns within the framework of EU privacy regulations (GDPR), we cannot provide raw MRI data. Therefore, the fMRI data consists of individual beta maps from the first-level analysis, which correspond to the difference between brain activity associated with no adaptation and adaptation to dot arrays. Maps are normalized into the MNI template, and unsmoothed. See paper for details about the preprocessing and first-level analysis. The sMRI data consists of voxelwise maps of surface area and cortical thickness in the MNI template. The dataset consists of mother-child dyads. Mothers are assigned codes of 200 or higher. Children are assigned codes below 200. Each child's code is exactly 200 less than their mother's code. The analyses codes require Python version 3.8.8 and Nilearn version 0.8.1. If you have any questions, please send an email to [e-mail].