Science Score: 36.0%
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○Scientific vocabulary similarity
Low similarity (9.6%) to scientific vocabulary
Repository
Shared paper codes for SDMA2024 project
Basic Info
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Metadata Files
README.md
Statistical Inference for Same Data Meta-Analysis for Neuroimaging Multiverse Analyzes
Jeremy Lefort-Besnard, Thomas E. Nichols°, Camille Maumet°
°These authors contributed equally to this work
Table of contents
How to cite?
See CITATION.
Contents overview
This repository includes the codes necessary to reproduce the analyses described in the paper "Statistical Inference for Same Data Meta-Analysis for Neuroimaging Multiverse Analyses". The repository is structured as follows:
- CITATION/: How to cite our work.
- data/: Raw data used in the analyses.
- figures/: Summary and derived data used to create figures.
- results/: Summary and derived data used to create tables.
- src/: Source code for simulations and analyses.
Reproducing figures and tables
Please note that the "NARPS" and "HCP Young Adult" multiverse outputs must be downloaded and stored in "SDMA/data/NARPS" and "SDMA/data/HCP". "NARPS" multiverse outputs can be downloaded from NeuroVault (Gorgolewski & al, 2015)NARPS. "HCP Young Adult" multiverse output can be downloaded from Germani et al. 2023
Additionally, the following scripts must be run beforehand:
- "SDMA/src/extractHCPdata.py" for preprocessing and computation of the intersectional mask.
- "SDMA/src/extractNARPSdata.py" for preprocessing and removal of non-included participants.
- "SDMA/src/intersectional_mask.py" to compute the intersectional mask between all NARPS team outputs.
Fig. 1
This figure is saved at "SDMA/figures/SIMULATIONS/simulationsvisualisation.pdf", generated by the script "SDMA/scr/SDMAingenerateddata.py"
Fig. 2
This figure is saved at "SDMA/figures/SIMULATIONS/J20000K20Corr0.8.pdf", generated by the script "SDMA/scr/SDMAingenerated_data.py"
Fig. 3
This figure combines "SDMA/figures/NARPS/hyp1/SDMA/thresholdedmaphyp1.png" generated by the script "SDMA/scr/SDMAinNARPS.py" and "SDMA/figures/HCP/thresholdedmaphyp" generated by the script "SDMA/scr/SDMAinHCP.py".
Additionally, the result maps of the SDMA estimators in NARPS and HCP shown in Figure 3 are publicly available on NeuroVault at https://neurovault.org/collections/18197/.
Fig. 4
This figure combines "SDMA/figures/NARPS/hyp1/clusteranalysis/3clusters/Fig4.png" and "SDMA/figures/NARPS/hyp1/clusteranalysis/3clusters/perclusterweights3.png" generated by the script "SDMA/scr/clusteranalysisinNARPS.py".
Tables
The results for all tables can be found in the files "SDMA/results/NARPS/hyp1/spatialhomogeneity/FrobeniusscoreNARPS.xlsx" (with "hyp1" to be adapted depending on the hypothesis number) and "SDMA/results/HCP/spatialhomogeneity/FrobeniusscoreHCP.xlsx." These files were generated by the scripts "SDMA/scr/spatialhomogeneityinNARPS.py" and "SDMA/scr/spatialhomogeneityinHCP.py," respectively.
Results from Table 1 (Difference Frobenius score) in the manuscript are located in the aforementioned files within the columns labeled 'GM+WM as Qref' and 'Norm. F.'
Results from Table 2 (Impact of regional vs. whole-brain Q for HCP results. Dice) in the manuscript are located in the aforementioned files within the column labeled 'DICE with GM&WM'
Results from Table 3 (Impact of regional vs. whole-brain Q for NARPS hypothesis 1 results. Dice) in the manuscript are located in the aforementioned files within the column labeled 'DICE with GM&WM'
Owner
- Name: Inria Empenn research team
- Login: Inria-Empenn
- Kind: organization
- Location: Rennes, France
- Website: https://team.inria.fr/empenn
- Repositories: 11
- Profile: https://github.com/Inria-Empenn
Citation (CITATION/.gitkeep)
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