Experiment in which we use pink noise different filtered to display specific
range of spatial frequency and contrast levels to determine the neural Contrast
Sensitivity Function (nCSF) of visual cortical areas. Participants are instructed
to fixate and report an orientation of the noise pattern presented on every TR.
Marco BEDINI, Sina KLING, Uriel LASCOMBES, Guillaume MASSON & Martin SZINTE
- Run heudiconv on Xnat, export BIDS data and import them on meso (see : https://invibe.nohost.me/bookstack/books/7t-crmbm/page/export-data-from-xnat)
- Rename subject and session rename_subject_and_session.py
- Copy events.tsv and matlab files from experients repo copy_events_and_matfiles.py
- Bids corections bids_conversion.py
- Validate bids format [https://bids-standard.github.io/bids-validator/] / alternately, use a docker [https://pypi.org/project/bids-validator/]
Analyses are run on individual participant (sub-0X) surface (fsnative) or their projection on the HCP cifti format
- Download BIDSonym singularity (singularity build /scratch/mszinte/data/nCSF/code/singularity/bidsonym-v0.0.4.simg docker://peerherholz/bidsonym:v0.0.4)
- Deface participants t1w image bidsonym_sbatch.py
- Download fMRIprep singulatity (singularity build /scratch/mszinte/data/nCSF/code/singularity/fmriprep-25.2.3.simg docker://nipreps/fmriprep:25.2.3)
- Download template flow using datalad and pute it in /code/singularity/fmriprep_tf
datalad install -r ///templateflow
cd templateflow
datalad get *- fMRIprep with anat-only option fmriprep_sbatch.py
- Create sagittal view video before manual edit sagital_view.py
- Manual edit of brain segmentation pial_edits.sh
- FreeSurfer with new brainmask manually edited freesurfer_pial.py
- Flattening of the cortex using flatten_sbatch.py (with or without manual cut cortex_cuts.sh)
Analyses are run on individual participant (sub-0X) surface (fsnative) or their projection on the HCP cifti format
- fMRIprep fmriprep_sbatch.py
- Load freesurfer and import subject in pycortex db freesurfer_import_pycortex.py
- High-pass, z-score, anat preproc_end.py or ro run on server preproc_end_sbatch.py
- Averaging across runs averaging_sbatch.py using averaging.py
Analyses are run on individual participant (sub-0X) surface (fsnative) or their projection on the HCP cifti format
- Compute inter-run correlation compute_run_corr_sbatch
- Make maps with pycortex pycortex_maps_run_corr.py or pycortex_maps_run_corr.sh
Analysis are run on the template of the HCP cifti format (170k) in which individual results are averaged.
- Compute inter-run correlation for template_avg compute_run_corr.py
- Make maps with pycortex for hcp1.6mm pycortex_maps_run_corr.py
Analyses are run on individual participant (sub-0X) surface (fsnative) or their projection on the HCP cifti format
- Create 170k MMP rois masks create_rois-mmp_npz.py
- Project MMP atlas on fsnative surface using freesurfer freesurfer_project_mmp_fsnative.py
- Make fsnative roi mmp npz and overlays fsnative_mmp_rois.py
- Make ROIS files make_rois_img.py
- Create flatmaps of ROIs pycortex_maps_rois.py or pycortex_maps_rois.sh
- Create the visual matrix design vdm_builder_prf.py
- CSS fit prf_submit_css_jobs.py
- Compute CSS statistics css_stats_sbatch.py
- Compute CSS fit derivatives compute_css_derivatives.py
- Compute CSS population cortical magnification (CM) css_pcm_sbatch.py
- Make maps with pycortex pycortex_maps_css.py or pycortex_maps_css.sh
- Make general TSV with CSS pRF fit derivatives, statistics and CM make_tsv_css.py
- Make ROIs figure specific TSV with CSS pRF fit derivatives, statistics and CM make_rois_fig_tsv.py or make_rois_fig_tsv.sh
- Make ROIs figure of CSS pRF fit derivatives, statistics and CM make_rois_fig.py or make_rois_fig.sh
- Merge all figures merge_fig_prf.py
Analyses are run on individual participant (sub-0X) surface (fsnative) or their projection on the HCP cifti format
- nCSF fit submit_nCSF_jobs.py
- Compute nCSF statistics ncsf_stats_sbatch.py
- Compute nCSF fit derivatives compute_ncsf_derivatives.py
- Make maps with pycortex pycortex_maps_ncsf.py or pycortex_maps_ncsf.sh
- Make general TSV with nCSF fit derivatives and statistics make_ncsf_tsv.py
- Make ROIs figure specific TSV with nCSF fit derivatives and statistics make_ncsf_rois_fig_tsv.py or make_ncsf_rois_fig_tsv.sh
- Make ROIs figure of nCSF fit derivatives and statistics make_ncsf_rois_fig.py or make_rois_fig.sh
- Merge all figures merge_fig_ncsf.py