Quinn Andrew J, Pitt Jemma, Kohl Oliver, Gohil Chetan, van Es Mats WJ, Nobre Anna C, Woolrich Mark W (2025) Robust and replicable effects of ageing on resting state brain electrophysiology measured with MEG eLife 14:RP108829 https://doi.org/10.7554/eLife.108829.2
Quinn, A. J., Pitt, J., Kohl, O., Gohil, C., van Es, M. W. J., Nobre, A. C., & Woolrich, M. W. (2025). Robust and replicable effects of ageing on resting state brain electrophysiology measured with MEG. Cold Spring Harbor Laboratory. https://doi.org/10.1101/2025.08.01.668093
Dependencies are contained within pyproject.toml and recommend using uv for installation. The following code creates a virtual environment with exact specifications in current directory (likely code root)
uv venv
source .venv/bin/activate
uv pip sync pyproject.toml
Run above once to install, then activate in future sessions with
source .venv/bin/activate
UoB specific:
module load bear-apps/2023a
module load uv/0.6.5
module load ImageMagick/7.1.1-15-GCCcore-12.3.0
Update paths in pyproject_paths.toml to point to data directories and output locations.
Preprocessing and (optional) SLURM cluster submission scripts.
bigmeg-0-preproc_oxford_preproc-slurm.sh
bigmeg-0-preproc_oxford_preproc-slurm.py
bigmeg-0-preproc_nottingham_preproc-slurm.sh
bigmeg-0-preproc_nottingham_preproc-slurm.py
bigmeg-0-preproc_camcan_preproc-stats.py
bigmeg-0-preproc_camcan_preproc-slurm.sh
bigmeg-0-preproc_camcan_preproc-slurm.py
bigmeg-0-preproc_cambridge_preproc-slurm.sh
bigmeg-0-preproc_cambridge_preproc-slurm.py
Data analysis
bigmeg-1a_group-glm-perms_age-only.py
bigmeg-1b_group-glm-perms_age-with-covariates.py
bigmeg-1c_group-glm-perms_age-only-variant-preproc.py
bigmeg-1d_group-glm-perms_age-only-variant-headpos.py
Figures
bigmeg-3a_figures123_camcan-age-only.py
bigmeg-3b_figures45_alldata-age-only.py
bigmeg-3c_figures6_camcan-age-only-absolute.py
bigmeg-3d_figures78_camcan-age-covariates.py