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Applying a network framework to the study of reading and dyslexia

Bailey, Aboud, Nguyen and Cutting

Journal of Neurodevelopmental Disabilities

This repository contains supplementary data and details for the analyses presented in this paper. Data is organized into folders based on the figures / analysis performed. Many of the analyses are based on publicly available datasets, the details of which can be found below.

Fig1_Yeo-to-NeuroSynth

Figure 1

  • NeuroSynth_reading_pXXX_z_FDR_0.01.nii.gz: Forward-inference (pAgF) and reverse-inference (pFgA) maps for the term "reading". Downloaded Oct. 2017 from NeuroSynth.
  • Yeo_7Networks_2mm_LiberalMask_reg2MNI.nii.gz: Cortical parcellation estimated in Yeo et al., 2011. The "Liberal Mask" volume (available here) was transformed from 1mm "fsaverage" space to FSL's 2mm MNI 152 standard space template using flirt.
  • Intersection_reading_pXXX_Yeo7.nii.gz: Yeo 7-network parcellation, masked by the corresponding inference map from NeuroSynth. File is in MNI 152 2mm space.

Fig2_Modularity-Predicts-Reading

Figure 2

  • Bailey2017_ROI-Details.csv: Node list including community assignments, hub measures and whether it was implicated in dyslexia. Node data (coordinates and network measures) is merged across the tables from Power et al., 2011 and Power et al., 2013, included elsewhere in this repository. Coordinates are in MNI space.
  • Power2011_ConsensusCommunities.xlsx: Original supplemental data listing consensus communities for each node, made available by Jonathan Power on his personal website.

Fig3_Dyslexia-vs-Hubness

Figure 3

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Supplementary figures, code and data for the 2018 Journal of Neurodevelopmental Disabilities paper

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