[CITATION]
This repository contains code that was used to analyze and create the figures of the manuscript cited above. The code is organised as follows:
.
├── data: .zip archives downloaded from the Human Connectome Project
├── results: storage of the analysis results
└── src: source code for the analysis
The data used in the study are the raw functional and structural fMRI data from the 1080 HCP subjects who have completed the Motor Task ({subject}_3T_Structural_unproc.zip and {subject}_3T_tfMRI_MOTOR_unproc.zip). Archives were downloaded from https://db.humanconnectome.org/ into the data
folder.
Octave 5.1 and SPM12 for Octave were used.
The folder path for SPM12 was specified in the file .src/bash_scripts/spmpath.txt
. Additionally, the paths to the folder containing the functions was stored in ./src/bash_scripts/srcpath.txt
.
Run ./src/bash_scripts/preprocessing_<PARAM_PREPROC>_list_IGRIDA.sh "<SUB1> <SUB2> <SUB3>"
in a terminal where <SUB1>
, <SUB2>
, <SUB3>
, etc. are the HCP subject identifiers as found in src/src/list_subjects_ordered_full.txt
(this can be used to run preprocessing for part of the subjects to account for reduced storage space) and <PARAM_PREPROC>
is taken from the table below.
PARAM_PREPROC | Pipeline parameters |
---|---|
5 | smoothing 5mm |
8 | smoothing 8mm |
-
To perform first-level analysis and obtain the left foot contrast, run
./src/bash_scripts/fla_<PARAM_FLA>_list_IGRIDA.sh "<SUB1> <SUB2> <SUB3>"
in a terminal where<SUB1>
,<SUB2>
,<SUB3>
, etc. are the HCP subject identifiers as found insrc/src/list_subjects_ordered_full.txt
(this can be used to run preprocessing for part of the subjects to account for reduced storage space) and<PARAM_FLA>
is taken from the table below. -
Similarly to 1., run
./src/bash_scripts/fla_<PARAM_FLA>_list_hand_IGRIDA.sh "<SUB1> <SUB2> <SUB3>"
in a terminal to obtain the right hand contrast.
PARAM_FLA | Pipeline parameters |
---|---|
5_0_0 | smoothing 5mm, no motion regressors, canonical HRF |
5_0_1 | smoothing 5mm, no motion regressors, canonical HRF with temporal derivatives |
5_6_0 | smoothing 5mm, 6 motion regressors, canonical HRF |
5_6_1 | smoothing 5mm, 6 motion regressors, canonical HRF with temporal derivatives |
5_24_0 | smoothing 5mm, 24 motion regressors, canonical HRF |
5_24_1 | smoothing 5mm, 24 motion regressors, canonical HRF with temporal derivatives |
8_0_0 | smoothing 8mm, no motion regressors, canonical HRF |
8_0_1 | smoothing 8mm, no motion regressors, canonical HRF with temporal derivatives |
8_6_0 | smoothing 8mm, 6 motion regressors, canonical HRF |
8_6_1 | smoothing 8mm, 6 motion regressors, canonical HRF with temporal derivatives |
8_24_0 | smoothing 8mm, 24 motion regressors, canonical HRF |
8_24_1 | smoothing 8mm, 24 motion regressors, canonical HRF with temporal derivatives |
Similarly to the previous SPM scripts, we use scripts ./src/bash_scripts/preprocessing_{parameter values}_list_fsl_IGRIDA.sh
and ./src/bash_scripts/fla_{parameter values}_list_hand_fsl_IGRIDA.sh
to perform preprocessing and first-level analysis on subject data with FSL.
-
Run
./src/bash_scripts/second_level_analysis_full_hand_spm_IGRIDA.sh
to perform the 1000 group analyses for every pair of pipelines. -
Run
./src/bash_scripts/false_positive_rate_full_hand_spm_IGRIDA.sh
to obtain the empirical false positive rate for every pair of pipelines.
The resulting estimation of the false positive rate for each pair of pipeline is stored in the following file : results/smooth_<SMOOTH1>_reg_<REG1>_der_<DER1>/smooth_<SMOOTH2>_reg_<REG2>_der_<DER2>/mean_hand_50_FWE.mat
, with <SMOOTH1>
, <REG1>
, <DER1>
the parameter values for the first pipeline and <SMOOTH2>
, <REG2>
, <DER2>
for the second pipeline, taken from the tables below.
SMOOTH1, SMOOTH2 | Pipeline parameters |
---|---|
5 | smoothing 5mm |
8 | smoothing 8mm |
REG1, REG2 | Pipeline parameters |
---|---|
0 | no motion regressors |
6 | 6 motion regressors |
24 | 24 motion regressors |
DER1, DER2 | Pipeline parameters |
---|---|
0 | canonical HRF |
1 | canonical HRF with temporal derivatives |