By : Martin Szinte & Gilles de Hollander
With : Marco Aqil, Serge Dumoulin & Tomas Knapen
Experiment in which we first used a full screen 4 direction (left/right/up/down)
bar pass stimuli in a attention to fixation or attention to the bar experiment.
Next, we use the same tasks but this time using a bar pass restricted to an aperture and
displayed at 3 different position surrounding the fixation target put at the screen center
or displaced to the left or to the right.
- 8 participants tested using experiment_code/main/expLauncher.m
- Compute and plot performance results: behav_results.ipynb
- Compute and plot eccentricity results using ecc_results.ipynb
- Convert data in bids.
- Run fmriprpep with anat-only option: fmriprep_sbatch.py
- Manual edition of the pial surface using freeview launched: pial_edits.py and following these rules
- Re-run freesurfer with change of the pial surface: freesurfer_pial.py
- Cut brains and flatten hemispheres: flatten_sbatch.py
- Run fmriprpep for functionnal runs: fmriprep_sbatch.py
- Deface T1w/T2w data: deface_sbatch.py
- Run pybest to z-scores, high pass filter the data: pybest_sbatch.py
- Arrange data in pp_data folder: preproc_end.py
- Import in pycortex surfaces and flatmaps: pycortex_import.py
- Average runs together: average_runs.py
- Compute pRF across conditions
- Compute pRF out-of_set fit
- Compute pRF refit
- Create pRF threshold mask: prf_th_masks.ipynb
- Generate Fullscreen retinotopy maps: pycortex.ipynb
- Draw ROIS using Inkscape and Fullscreen maps
- Define ROI masks nifti files: roi_masks.ipynb
- Generate "all" pycortex flatmaps and webgl: pycortex.ipynb
- Push subjects webgl online: webgl.ipynb
- Create TSV files of stats comparisons: make_tsv.ipynb
- Compute pickle files with all timeseries/predictions of out of set analysis: make_tsv.ipynb
- Draw Fullscreen attention R2 comparison: attcmp_plots.ipynb
- Draw timeseries and pRF model: timeseries_plot.ipynb
- Compute out of set r2 change: fs_fit_cmp_plots.ipynb
- Draw refit pRFx parameter: refit_pRFx_plots.ipynb
- Draw refit reference frame index: refit_indexcmp_plots.ipynb
- Compute decoding outcomes pickle files: make_tsv.ipynb
- Draw decoding time series using decode_timeseries_plot.ipynb
- Draw decoding time series across bar pass: decode_time_cor_plot.ipynb
- Draw decoding correlations to ground truth: decode_correlation_plot.ipynb
- Draw decoding reference frame index: decode_ref_index_plot.ipynb
- Compute decoding statistics Central_stats_decoding.ipynb.ipynb
- Statistics for manuscript manuscript_stats.ipynb
- DeepMReye analysis deepmreye_gpu_sbatch.py
- Statistics for DeepMReye eye_analysis.ipynb
Optional:
- Compute GLM in link with gainfield results get_gainfield_betas.py
- Draw pycortex flatmap of gainfield results pycortex.ipynb
- Draw GLM with gainfiled results comparison glmcmp_plots.ipynb
- Figure 1C: behav_results.ipynb
- Figure 1D: timeseries_plot.ipynb
- Figure 1G-H: pycortex.ipynb
- Figure 1I: attcmp_plots.ipynb
- Figure 2B-C: timeseries_plot.ipynb
- Figure 2D-E: fs_fit_cmp_plots.ipynb
- Figure 3C-D: refit_pRFx_plots.ipynb
- Figure 3E: refit_indexcmp_plots.ipynb
- Figure 3F-G: pycortex.ipynb
- Figure 4A-B: timeseries_plot.ipynb
- Figure 4C: decode_timeseries_plot.ipynb
- Figure 4D-E: decode_time_cor_plot.ipynb
- Figure 4F: decode_correlation_plot.ipynb
- Figure 4G: decode_ref_index_plot.ipynb