NYU Retinotopy Dataset

uploaded by Jan W. Kurzawski on 2021-08-31 - about 2 months ago
last modified on 2021-09-27 - 28 days ago
authored by Marc Himmelberg, Jan Kurzawski, Noah Benson, Denis Pelli, Marisa Carrasco, Jon Winawer
15
We found 1 Warning in your dataset. You are not required to fix warnings, but doing so will make your dataset more BIDS compliant.

/sub-wlsubj004/ses-anat/anat/sub-wlsubj004_ses-anat_acq-highres_run-01_T2w.nii.gz

The most common set of dimensions is: 240,256,256 (voxels), This file has the dimensions: 224,300,320 (voxels). The most common resolution is: 0.90mm x 0.90mm x 0.90mm, This file has the resolution: 0.80mm x 0.80mm x 0.80mm.

/sub-wlsubj014/ses-anat/anat/sub-wlsubj014_ses-anat_acq-highres_run-01_T1w.nii.gz

The most common set of dimensions is: 192,300,320 (voxels), This file has the dimensions: 256,256,256 (voxels). The most common resolution is: 0.80mm x 0.80mm x 0.80mm, This file has the resolution: 1.00mm x 1.00mm x 1.00mm.

/sub-wlsubj023/ses-anat/anat/sub-wlsubj023_ses-anat_acq-highres_run-01_T1w.nii.gz

The most common set of dimensions is: 192,300,320 (voxels), This file has the dimensions: 256,256,256 (voxels). The most common resolution is: 0.80mm x 0.80mm x 0.80mm, This file has the resolution: 1.00mm x 1.00mm x 1.00mm.

/sub-wlsubj043/ses-anat/anat/sub-wlsubj043_ses-anat_acq-highres_run-01_T1w.nii.gz

The most common set of dimensions is: 192,300,320 (voxels), This file has the dimensions: 256,256,256 (voxels). The most common resolution is: 0.80mm x 0.80mm x 0.80mm, This file has the resolution: 1.00mm x 1.00mm x 1.00mm.


OpenNeuro Accession Number: ds003787
Files: 2002, Size: 69.63GB, Subjects: 44, Sessions: 2
Available Tasks: prf
Available Modalities: MRI

README

The New York University (NYU) Retinotopy Dataset is a part of 'Cross-dataset reproducability of human retinotopic maps' by Marc Himmelberg, Jan Kurzawski, Noah Benson, Denis Pelli, Marisa Carrasco, and Jonathan Winawer.

The full dataset consists of 44 subjects, 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.

Dataset organisation:

NYU_Retinotopy_Dataset:

This folder contains subject folders holding the raw, unprocessed data for each subject (nifti files).

NYU_Retinotopy_Dataset/derivatives/bayesian_inference_maps:

This folder contains subject folders holding bayesian inferred angle, eccentricity, and pRF size maps, and inferred visual areas (see https://elifesciences.org/articles/40224) (.mgz files)

NYU_Retinotopy_Dataset/derivatives/fmriprep:

This folder contains subject folders and fmriprep output logs. Within each subjects session folder you can find functional data on the fsnative and fsaverage surface (.mgz files)

NYU_Retinotopy_Dataset/derivatives/freesurfer:

This folder contains subject folders with standard freesurfer output (freesurfer v6)

NYU_Retinotopy_Dataset/derivatives/freesurfer:

This folder contains MRIQC output logs for each subject

NYU_Retinotopy_Dataset/derivatives/prfanalyze-vista:

Here you can find subject folders that house the vistasoft pRF model output on the fsnative surface for each subject (.mgz)

eccen.mgz

- eccentricity maps sigma.mgz - pRF size maps angle.mgz - polar angle maps angle_adj.mgz - polar angle maps adjusted so that left hemifield is 0 - negative 180, right hemisfield 0 - positive 180. vexpl.mgz - variance explained x.mgz - x coordinates maps y.mgz - y coordinates maps

sub-wlsubj000

contains the pRF solutions from the group-average time-series (n=44). sub-wlsubj_average_parameter contains the median pRF solutions across all individual subjects on the fsaverage surface (n=44).

NYU_Retinotopy_Dataset/derivatives/ROIs:

These folders contain V1, V2, V3, and hV4 ROIS drawn on the fsnative surface using Neuropythy. Labels of 1, 2, 3, and 4, correspond to V1, V2, V3, and hV4, respectively.

NYU_Retinotopy_Dataset/derivatives/stimulus_apertures:

This folder contains the pRF bar stimulus aperture for each scan for those who wish to reprocess any data - note that all the apertures are the same for each subject (standard pRF bar runs)

Authors

  • Marc Himmelberg
  • Jan Kurzawski
  • Noah Benson
  • Denis Pelli
  • Marisa Carrasco
  • Jon Winawer

Dataset DOI

10.18112/openneuro.ds003787.v1.0.0

License

CC0

Acknowledgements

Cite 'Cross-dataset reproducibility of human retinotopic maps' by Himmelberg, Kurzawski, Benson, Pelli, Carrasco, & Winawer

How to Acknowledge

Funding

  • US National Eye Institute R01-EY027401 to MC and JW
  • US National Eye Institute R01-EY027964 to DGP and JW

References and Links

  • TODO
  • List of papers or websites

Ethics Approvals

How To Cite

Copy
Marc Himmelberg and Jan Kurzawski and Noah Benson and Denis Pelli and Marisa Carrasco and Jon Winawer (2021). NYU Retinotopy Dataset . OpenNeuro. [Dataset] doi: 10.18112/openneuro.ds003787.v1.0.0
More citation info

NYU Retinotopy Dataset

uploaded by Jan W. Kurzawski on 2021-08-31 - about 2 months ago
last modified on 2021-09-27 - 28 days ago
authored by Marc Himmelberg, Jan Kurzawski, Noah Benson, Denis Pelli, Marisa Carrasco, Jon Winawer
15

OpenNeuro Accession Number: ds003787
Files: 2002, Size: 69.63GB, Subjects: 44, Sessions: 2
Available Tasks: prf
Available Modalities: MRI

README

The New York University (NYU) Retinotopy Dataset is a part of 'Cross-dataset reproducability of human retinotopic maps' by Marc Himmelberg, Jan Kurzawski, Noah Benson, Denis Pelli, Marisa Carrasco, and Jonathan Winawer.

The full dataset consists of 44 subjects, 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.

Dataset organisation:

NYU_Retinotopy_Dataset:

This folder contains subject folders holding the raw, unprocessed data for each subject (nifti files).

NYU_Retinotopy_Dataset/derivatives/bayesian_inference_maps:

This folder contains subject folders holding bayesian inferred angle, eccentricity, and pRF size maps, and inferred visual areas (see https://elifesciences.org/articles/40224) (.mgz files)

NYU_Retinotopy_Dataset/derivatives/fmriprep:

This folder contains subject folders and fmriprep output logs. Within each subjects session folder you can find functional data on the fsnative and fsaverage surface (.mgz files)

NYU_Retinotopy_Dataset/derivatives/freesurfer:

This folder contains subject folders with standard freesurfer output (freesurfer v6)

NYU_Retinotopy_Dataset/derivatives/freesurfer:

This folder contains MRIQC output logs for each subject

NYU_Retinotopy_Dataset/derivatives/prfanalyze-vista:

Here you can find subject folders that house the vistasoft pRF model output on the fsnative surface for each subject (.mgz)

eccen.mgz

- eccentricity maps sigma.mgz - pRF size maps angle.mgz - polar angle maps angle_adj.mgz - polar angle maps adjusted so that left hemifield is 0 - negative 180, right hemisfield 0 - positive 180. vexpl.mgz - variance explained x.mgz - x coordinates maps y.mgz - y coordinates maps

sub-wlsubj000

contains the pRF solutions from the group-average time-series (n=44). sub-wlsubj_average_parameter contains the median pRF solutions across all individual subjects on the fsaverage surface (n=44).

NYU_Retinotopy_Dataset/derivatives/ROIs:

These folders contain V1, V2, V3, and hV4 ROIS drawn on the fsnative surface using Neuropythy. Labels of 1, 2, 3, and 4, correspond to V1, V2, V3, and hV4, respectively.

NYU_Retinotopy_Dataset/derivatives/stimulus_apertures:

This folder contains the pRF bar stimulus aperture for each scan for those who wish to reprocess any data - note that all the apertures are the same for each subject (standard pRF bar runs)

Authors

  • Marc Himmelberg
  • Jan Kurzawski
  • Noah Benson
  • Denis Pelli
  • Marisa Carrasco
  • Jon Winawer

Dataset DOI

10.18112/openneuro.ds003787.v1.0.0

License

CC0

Acknowledgements

Cite 'Cross-dataset reproducibility of human retinotopic maps' by Himmelberg, Kurzawski, Benson, Pelli, Carrasco, & Winawer

How to Acknowledge

Funding

  • US National Eye Institute R01-EY027401 to MC and JW
  • US National Eye Institute R01-EY027964 to DGP and JW

References and Links

  • TODO
  • List of papers or websites

Ethics Approvals

How To Cite

Copy
Marc Himmelberg and Jan Kurzawski and Noah Benson and Denis Pelli and Marisa Carrasco and Jon Winawer (2021). NYU Retinotopy Dataset . OpenNeuro. [Dataset] doi: 10.18112/openneuro.ds003787.v1.0.0
More citation info

Dataset File Tree

Git Hash: d3b7e1b 

BIDS Validation

We found 1 Warning in your dataset. You are not required to fix warnings, but doing so will make your dataset more BIDS compliant.

/sub-wlsubj004/ses-anat/anat/sub-wlsubj004_ses-anat_acq-highres_run-01_T2w.nii.gz

The most common set of dimensions is: 240,256,256 (voxels), This file has the dimensions: 224,300,320 (voxels). The most common resolution is: 0.90mm x 0.90mm x 0.90mm, This file has the resolution: 0.80mm x 0.80mm x 0.80mm.

/sub-wlsubj014/ses-anat/anat/sub-wlsubj014_ses-anat_acq-highres_run-01_T1w.nii.gz

The most common set of dimensions is: 192,300,320 (voxels), This file has the dimensions: 256,256,256 (voxels). The most common resolution is: 0.80mm x 0.80mm x 0.80mm, This file has the resolution: 1.00mm x 1.00mm x 1.00mm.

/sub-wlsubj023/ses-anat/anat/sub-wlsubj023_ses-anat_acq-highres_run-01_T1w.nii.gz

The most common set of dimensions is: 192,300,320 (voxels), This file has the dimensions: 256,256,256 (voxels). The most common resolution is: 0.80mm x 0.80mm x 0.80mm, This file has the resolution: 1.00mm x 1.00mm x 1.00mm.

/sub-wlsubj043/ses-anat/anat/sub-wlsubj043_ses-anat_acq-highres_run-01_T1w.nii.gz

The most common set of dimensions is: 192,300,320 (voxels), This file has the dimensions: 256,256,256 (voxels). The most common resolution is: 0.80mm x 0.80mm x 0.80mm, This file has the resolution: 1.00mm x 1.00mm x 1.00mm.

Dataset File Tree

Git Hash: d3b7e1b 

Comments

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By marchimmelberg@gmail.com - about 1 month ago
Publicly available
By marchimmelberg@gmail.com - about 1 month ago
public release
By jan.kurzawski@gmail.com - 27 days ago
public