fMRI_MotionCorrection

The quality of fMRI data is affected by the subject’s motion in the scanner. This can cause signal alterations across fMRI volumes generating spurious results. Hence, motion correction is always an important preprocessing step in fMRI data analysis. This code will perform brain extraction and motion correction to fMRI acquired data. The dataset that I used is accessible through openneuroi: Flanker test https://openneuro.org/datasets/ds000102/versions/00001.

How to Run

To start the notebook, run the following line on a terminal :

'fsleyes --notebookFile main.ipynb'

Dependencies

• os
• nibabel
• pandas
• numpy
• tqdm
• urllib
• matplotlib
• FSLPy
• Nilearn
• Dipy
• MNE-NIRS
• jupyterlab
• openneuro-py
• fsleyes

Data

The data can be found here : https://openneuro.org/datasets/ds000102/versions/00001
It comprises data collected from 26 healthy adults while they performed a slow event-related Eriksen Flanker task. For this study, only the first three subjects are used (sub-01, sub-02, sub-03).

References

Kelly, A.M., Uddin, L.Q., Biswal, B.B., Castellanos, F.X., Milham, M.P. (2008). Competition between functional brain networks mediates behavioral variability. Neuroimage, 39(1):527-37

Mennes, M., Kelly, C., Zuo, X.N., Di Martino, A., Biswal, B.B., Castellanos, F.X., Milham, M.P. (2010). Inter-individual differences in resting-state functional connectivity predict task-induced BOLD activity. Neuroimage, 50(4):1690-701. doi: 10.1016/j.neuroimage.2010.01.002. Epub 2010 Jan 15. Erratum in: Neuroimage. 2011 Mar 1;55(1):434

Mennes, M., Zuo, X.N., Kelly, C., Di Martino, A., Zang, Y.F., Biswal, B., Castellanos, F.X., Milham, M.P. (2011). Linking inter-individual differences in neural activation and behavior to intrinsic brain dynamics. Neuroimage, 54(4):2950-9. doi: 10.1016/j.neuroimage.2010.10.046