Supporting code to perform the analyses and create the figures of the manuscript with the same title available at https://doi.org/10.1101/285585.
To cite this repository, please cite the corresponding manuscript:
"Exploring the Impact of Analysis Software on fMRI Results" Alexander Bowring, Camille Maumet*, Thomas Nichols*. bioRxiv 285585; doi: 10.1101/285585
To reproduce the figures, you will need to install the dependencies listed in requirements.txt
, this can be done using pip with:
pip install -r requirements.txt
You will also need to have Jupyter notebook installed, we recommend using Anaconda to perform the install.
-
From a Terminal, run:
jupyter notebook ./figures/ds001_notebook.ipynb
-
In the notebook, run all the cells up to the cell starting with
from lib import plot_excursion_sets
. In this cell, make sure thatx_coords=[4, 32]
. Running this cell will then reproduce the first column of figure 1.
Same as Fig. 1, but using ./figures/ds109_notebook.ipynb
; again, make sure that x_coords=[0, 32]
.
Same as Fig. 1, but using ./figures/ds120_notebook.ipynb
again, make sure that x_coords=[0, 32]
.
-
From a Terminal, run:
jupyter notebook ./figures/ds001_notebook.ipynb
-
In the notebook, run all the cells up to the cell starting with
from lib import plot_stat_images
. In this cell, make sure that the coordinates being inputted to theplot_stat_images
function are[-17, 1, 15]
. Running this cell will then repoduce the first column of figure 2.
Same as Fig. 2, but using ./figures/ds109_notebook.ipynb
.
Same as Fig. 2, but using ./figures/ds120_notebook.ipynb
.
-
From a Terminal, run:
jupyter notebook ./figures/ds001_notebook.ipynb
-
In the notebook, run all the cells up to the cell starting with
from lib import bland_altman
which will reproduce the first column of figure 3a.
Same as Fig. 3a left but using ./figures/ds109_notebook.ipynb
.
Same as 3a but using ./figures/ds120_notebook.ipynb
.
-
From a Terminal, run:
jupyter notebook ./figures/ds001_notebook.ipynb
-
In the notebook, run all the cells up to the cell starting with
from lib import dice
.
Same as Fig. 4 left but using ./figures/ds109_notebook.ipynb
.
Same as Fig. 4 left but using ./figures/ds120_notebook.ipynb
.
-
From a Terminal, run:
jupyter notebook ./figures/ds001_notebook.ipynb
-
In the notebook, run all the cells up to the cell starting with
from lib import euler_characteristics
.
Same as Fig. 5 left but using ./figures/ds109_notebook.ipynb
.
-
From a Terminal, run:
jupyter notebook ./figures/ds001_notebook.ipynb
-
In the notebook, run all the cells up to the cell starting with
from lib import plot_excursion_sets
.
-
From a Terminal, run:
jupyter notebook ./figures/ds001_notebook.ipynb
-
In the notebook, run all the cells up to the cell starting with
bland_altman.bland_altman('Bland-Altman Plots: Permutation Tests')
.
Same as Fig. 7 left but using ./figures/ds109_notebook.ipynb
.
-
From a Terminal, run:
jupyter notebook ./figures/ds001_notebook.ipynb
-
In the notebook, run all the cells up to the cell starting with
reload(bland_altman) bland_altman.bland_altman_intra('Bland-Altman Plots: Parametric vs Permutation')
.
Same as Fig. 8 left but using ./figures/ds109_notebook.ipynb
.
To run the experiments included in the manuscript, raw data must be downloaded from OpenfMRI.org and copied on your local computer:
- ds000001 revision 2.0.4: https://openfmri.org/dataset/ds000001/
- ds000109 revision 2.0.2: https://openfmri.org/dataset/ds000109/
- ds000120 revision 1.0.0: https://openfmri.org/dataset/ds000120/
Given:
<PATH_TO_RAW_DATA>
: the path to the raw data fords000001
and<PATH_TO_OUTPUT>
: the path to the output folder where the results should be stored (must end with ads001
sub-folder).
-
In
scripts/process_ds001_SPM.m
replace the values ofstudy_dir
andresults_dir
by<PATH_TO_RAW_DATA>
and<PATH_TO_OUTPUT>
respectively. -
In
scripts/process_ds001_FSL.py
andscripts/process_ds001_AFNI.py
replace the values ofraw_dir
andresults_dir
by<PATH_TO_RAW_DATA>
and<PATH_TO_OUTPUT>
respectively. -
For the SPM analysis, inside Matlab run:
addpath('scripts') addpath(fullfile('scripts', 'lib')) process_ds001_SPM
This will create onsets, preprocess the data, and run first and group level analyses.
-
For the FSL analysis, from a terminal run:
python scripts/process_ds001_FSL.py
-
For the AFNI analysis, from a terminal run:
python scripts/process_ds001_AFNI.py
The derived data available on NeuroVault at https://neurovault.org/collections/2209/ can be reproduced as follows:
-
NIDM-Results packs for SPM and FSL are available in
<PATH_TO_OUTPUT>/SPM/LEVEL2
and<PATH_TO_OUTPUT>/FSL/LEVEL2
respectively. -
For the resliced images, inside Matlab run
addpath('scripts') addpath(fullfile('scripts', 'lib')) ds001_reslice_images
The csv files containing the Euler characteristics can be recomputed in Matlab, using:
addpath('scripts') addpath(fullfile('scripts', 'lib')) ds001_euler_chars
Same as for ds000001, replacing all occurences of 001
by 109
and https://neurovault.org/collections/2209/ by https://neurovault.org/collections/2238/.
Same as for ds000001, replacing all occurences of 001
by 120
and https://neurovault.org/collections/2209/ by https://neurovault.org/collections/2982/.
ds001: Part of ds001 output data (excluding images)
ds109: Part of ds109 output data (excluding images)
ds120: Part of ds120 output data (excluding images)
figures: Scripts and notebooks to reproduce the figures
scripts: Scripts to rerun the analysis
.gitignore: git configuration file
README.md: current file