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Below you can find a list of public datasets that have been collected partly or entirely in the CBI facilities.
The dataset is part of the paper 'Cross-dataset reproducibility of human retinotopic maps'. It consists of 44 participants, including freesurfer processed anatomical data, raw and preprocessed (via fMRIprep) functional data on the fsnative and fsaverage surface, vistasoft pRF model output, V1, V2, V3, and hV4 ROIs, and bayesian inferred retinotopic maps and ROIs. The dataset adhered to BIDS conventions.
The authors also provide a new release of vistasoft pRF model solutions for all 181 participants from the Human Connectome (HCP) 7T Retinotopy Project which are made available on the OSF page.
They provide two jupyter notebook scripts.
1. visualise_RetinotopyData.ipynb can be used to visualise the NYU Retinotopy data on cortical flatmaps and inflated mesh surfaces
2. draw_RetinotopyROIs.ipynb can be used to trace and create new visual area ROIs on the NYU data.
The NYU Retinotopy dataset is publicly available via OpenNeuro: https://openneuro.org/datasets/ds003787
OSF wiki page: https://osf.io/e6vqk/wiki/home/
Related article: https://doi.org/10.1016/j.neuroimage.2021.118609
This dataset contains the data from the paper 'Mapping Spatial Frequency Preferences Across Human Primary Visual Cortex'. In this experiment, the authors measured the BOLD responses of 12 human observers to a set of novel grating stimuli in order to measure the spatial frequency tuning in primary visual cortex across eccentricities, retinotopic angles, and stimulus orientations. They then fit a parametric model which fits all voxels for a given subject simultaneously, predicting each voxel's response as a function of the voxel's retinotopic location and the stimulus local spatial frequency and orientation.
This dataset contains the minimally pre-processed, BIDS-compliant data required to reproduce the analyses presented in the paper. In addition to the task imaging data and stimuli files, it contains three derivatives directories:
- freesurfer: freesurfer subject directories for each subject, with one
change: the contents of mri/ directories have been defaced.
- prf_solutions: solutions to the population receptive field models from a
separate retinotopy experiment for each subject, fit using
VistaSoft. Also contains the Benson retinotopic atlases for each subject (Benson et al., 2014) and the solutions for Bayesian retinotopic analyses (Benson and Winawer, 2018) -- the solutions to the Bayesian retinotopy are what we actually use in the paper.
- preprocessed: the preprocessed data (a custom script was used for preprocessing, found on the Winawer Lab Github, see Winawer Lab wiki for more details). See paper for description of steps taken. Results should not change substantially if fMRIPrep were to be used for preprocessing instead, as long as data is kept in individual subject space.
The Spatial Frequency Preferences dataset is publicly available via OpenNeuro: https://openneuro.org/datasets/ds003812
OSF project containing miscellaneous files: https://osf.io/afs85/
Github repository with all project code: https://github.com/billbrod/spatial-frequency-preferences
Related article: ADD LINK
OSF page: https://osf.io/knb5g/
Related article: https://elifesciences.org/articles/40224
OSF page: https://osf.io/v843t/
Related article: https://www.jneurosci.org/content/38/3/691
OSF page: https://osf.io/zm9bm/
Related article: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5491263/