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Dataset . 2022
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Dataset . 2022
License: CC BY
Data sources: Sygma
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Dataset . 2022
Data sources: Datacite
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ZENODO
Dataset . 2022
Data sources: ZENODO
ZENODO
Dataset . 2022
License: CC BY
Data sources: Datacite
ZENODO
Dataset . 2022
License: CC BY
Data sources: Datacite
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Data and Code: Cortical representations of symbolic and non-symbolic quantity expand but become estranged with learning and development

Authors: Tomoya Nakai; Jérôme Prado;

Data and Code: Cortical representations of symbolic and non-symbolic quantity expand but become estranged with learning and development

Abstract

Note Here we provide preprocessed data and analysis code used in "Cortical representations of symbolic and non-symbolic quantity expand but become estranged with learning and development". 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 preprocessed volumes, normalized into the MNI template, and averaged across five TRs for each block (see paper for details about the preprocessing pipeline). The analysis code requires Python version 3.8.8, Nilearn version 0.8.1, and Scikit-learn version 0.24.1. If you have any questions, please send an email to nakai.tomoya [at] neuro.mimoza.jp. Usage import PredysDecoding5ans_SearchLight_LOOCV as pdsl5 import PredysDecoding8ans_SearchLight_LOOCV as pdsl8 import PredysDecoding5to8_SearchLight as pdsl58 import PredysDecoding8to5_SearchLight as pdsl85 Within-format decoding for 5-year-olds (Figures 2A, B): pdsl5.IntraModalDec(TaskName='Dots') pdsl5.SaveNifti_PermTest(TaskName='Dots') pdsl5.IntraModalDec(TaskName='Digits') pdsl5.SaveNifti_PermTest(TaskName='Digits') Within-format decoding for 8-year-olds (Figure 2C, D): pdsl8.IntraModalDec(TaskName='Dots') pdsl8.SaveNifti_PermTest(TaskName='Dots') pdsl8.IntraModalDec(TaskName='Digits') pdsl8.SaveNifti_PermTest(TaskName='Digits') Within-format decoding, paired tests between 5- and 8-year-olds (Figures 3A, B): pdsl5.SaveNifti_Paired_PermTest(TaskName='Dots') pdsl5.SaveNifti_Paired_PermTest(TaskName='Digits') pdsl8.SaveNifti_Paired_PermTest(TaskName='Dots') pdsl8.SaveNifti_Paired_PermTest(TaskName='Digits') Within-format decoding across 5- and 8-year-olds (Figures 3C, D): pdsl85.IntraModalDec(TaskName='Dots') pdsl85.SaveNifti_PermTest(TaskName='Dots') pdsl85.IntraModalDec(TaskName='Digits') pdsl85.SaveNifti_PermTest(TaskName='Digits') pdsl58.IntraModalDec(TaskName='Dots') pdsl58.SaveNifti_PermTest(TaskName='Dots') pdsl58.IntraModalDec(TaskName='Digits') pdsl58.SaveNifti_PermTest(TaskName='Digits') pdsl58.SaveNifti_PermTest_Conj(TaskName='Dots') pdsl58.SaveNifti_PermTest_Conj(TaskName='Digits') Between-format decoding for 5-year-olds (Figures 4A, 5B): pdsl5.CrossModalDec(TaskName1='Dots', TaskName2='Digits') pdsl5.SaveNifti_PermTest(TaskName='Dots2Digits') pdsl5.CrossModalDec(TaskName1='Digits', TaskName2='Dots') pdsl5.SaveNifti_PermTest(TaskName='Digits2Dots') pdsl5.SaveNifti_PermTest_Conj(TaskName1='Dots2Digits', TaskName2='Digits2Dots') pdsl5.CrossModalDec(TaskName1='Dots', TaskName2='Letters') pdsl5.SaveNifti_PermTest(TaskName='Dots2Letters') pdsl5.CrossModalDec(TaskName1='Letters', TaskName2='Dots') pdsl5.SaveNifti_PermTest(TaskName='Letters2Dots') pdsl5.SaveNifti_PermTest_Conj(TaskName1='Dots2Letters', TaskName2='Letters2Dots') Between-format decoding for 8-year-olds (Figure 4A): pdsl8.CrossModalDec(TaskName1='Dots', TaskName2='Digits') pdsl8.SaveNifti_PermTest(TaskName='Dots2Digits') pdsl8.CrossModalDec(TaskName1='Digits', TaskName2='Dots') pdsl8.SaveNifti_PermTest(TaskName='Digits2Dots') pdsl8.SaveNifti_PermTest_Conj(TaskName1='Dots2Digits', TaskName2='Digits2Dots') Between-format decoding, paired tests between 5- and 8-year-olds (Figure 4B) pdsl5.SaveNifti_Paired_PermTest_Conj(TaskName1='Dots2Digits', TaskName2='Digits2Dots') pdsl8.SaveNifti_Paired_PermTest_Conj(TaskName1='Dots2Digits', TaskName2='Digits2Dots')

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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