spatial_frequency_preferences

uploaded by William F. Broderick on 2021-09-20 - about 1 month ago
last modified on 2021-08-25 - 2 months ago
authored by William F. Broderick, Jonathan Winawer, Eero P. Simoncelli
31945
We found 2 Warnings in your dataset. You are not required to fix warnings, but doing so will make your dataset more BIDS compliant.

There are files in the /stimuli directory that are not utilized in any _events.tsv file.

There are files in the /stimuli directory that are not utilized in any _events.tsv file.

There are files in the /stimuli directory that are not utilized in any _events.tsv file.

There are files in the /stimuli directory that are not utilized in any _events.tsv file.

There are files in the /stimuli directory that are not utilized in any _events.tsv file.

There are files in the /stimuli directory that are not utilized in any _events.tsv file.

/participants.tsv

Tabular file contains custom columns not described in a data dictionary

Columns: age, sex not defined, please define in: /participants.json


OpenNeuro Accession Number: ds003812
Files: 768, Size: 40.54GB, Subjects: 12, Session: 1
Available Tasks: sfprescaled
Available Modalities: MRI

README

README

This spatial_frequency_preferences dataset contains the data from the paper "Mapping Spatial Frequency Preferences Across Human Primary Visual Cortex", by William F. Broderick, Eero P. Simoncelli, and Jonathan Winawer. ADD LINK

In this experiment, we 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. We 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.

This dataset is presented with the intention of enabling re-running our analyses to reproduce our results with our accompanying Github repo. This dataset should contain sufficient information for re-analysis with a novel method, but there are no guarantees.

If you use this dataset in a publication, please cite the corresponding paper.

  • Contact person: William F. Broderick, ORCID 0000-0002-8999-9003, wfb229@nyu.edu

This dataset is hosted on OpenNeuro, and can be downloaded from there. Additionally, we present two additional variants of this data, both hosted on this project's OSF page: - Fully-processed data: contains the final output of our analyses, the data required to reproduce the figures as they appear in the paper. - Partially-processed data: contains the outputs of GLMdenoise and all data required to start fitting the spatial frequency response functions.

Both data sets build on top of this one and so require the data contained here as well.

All three of these variants may be downloaded using code found in the Github repo, see the README there for more details.

Overview

  • Spatial frequency preferences

  • Year(s) that the project ran: started gathering pilot data in 2017, this dataset was gathered in the springs of 2019 and 2020. Paper written in 2020 and 2021, submitted fall 2021.

  • Brief overview of the tasks in the experiment: subjects viewed the stimuli, fixating on the center of the images. A sequence of digits, alternating black and white, was presented at fixation; subjects pressed a button whenever a digit repeated. The behavioral data was not presented in the paper and so is not present here. See paper for more details.

  • Description of the contents of the dataset:

    • Summary:
      • 767 Files
      • 12 subjects
      • 1 session each
    • Available tasks:
      • sfprescaled
    • Available modalities:
      • MRI

  • Quality assessment of the data: the MRIQC reports for each included scan can be found on this project's OSF page

Methods

Subjects

Subjects were recruited from graduate students and postdocs at NYU, all experienced MRI participants.

Apparatus

Data was gathered on NYU's Center for Brain Imaging's Siemens Prisma 3T MRI scanner in a shielded room. Data was gathered with subjects lying down, with the stimuli projected onto a screen above their head.

Initial setup

When subjects arrived, subjects were briefed on the task, given the experimental consent form to read and sign, and talked through the screener form.

Task organization

This experiment has only a single task.

Task details

Subjects passively viewed the stimuli while performing the distractor task described above: viewing a stream of alternating black and white digits and pressing a button whenever a digit repeated. Their button presses were recorded.

Additional data acquired

No additional data gathered.

Experimental location

All data gathered at NYU's Center for Brain Imaging in New York, NY.

Missing data

One subject (sub-wlsubj045) only has 7 of the 12 runs, due to technical issues that came up during the run. The quality of their GLMdenoise fits and their final model fits do not appear to vary much from that of the other subjects.

Authors

  • William F. Broderick
  • Jonathan Winawer
  • Eero P. Simoncelli

Dataset DOI

10.18112/openneuro.ds003812.v1.0.0

License

CC0

Acknowledgements

The authors would like to thank Noah C. Benson for his assistance with the retinotopy analysis.

How to Acknowledge

If you use this dataset, please cite both the data set (using the DatasetDOI in this file) and the corresponding paper (as given in ReferencesandLinks).

Funding

  • GRANT NIH R01EY027401 (JW)
  • GRANT NIH R01EY027964 (JW)
  • NSF GRFP (WFB)
  • HHMI (EPS)

References and Links

Ethics Approvals

How To Cite

Copy
William F. Broderick and Jonathan Winawer and Eero P. Simoncelli (2021). spatial_frequency_preferences. OpenNeuro. [Dataset] doi: 10.18112/openneuro.ds003812.v1.0.0
More citation info

spatial_frequency_preferences

uploaded by William F. Broderick on 2021-09-20 - about 1 month ago
last modified on 2021-08-25 - 2 months ago
authored by William F. Broderick, Jonathan Winawer, Eero P. Simoncelli
31945

OpenNeuro Accession Number: ds003812
Files: 768, Size: 40.54GB, Subjects: 12, Session: 1
Available Tasks: sfprescaled
Available Modalities: MRI

README

README

This spatial_frequency_preferences dataset contains the data from the paper "Mapping Spatial Frequency Preferences Across Human Primary Visual Cortex", by William F. Broderick, Eero P. Simoncelli, and Jonathan Winawer. ADD LINK

In this experiment, we 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. We 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.

This dataset is presented with the intention of enabling re-running our analyses to reproduce our results with our accompanying Github repo. This dataset should contain sufficient information for re-analysis with a novel method, but there are no guarantees.

If you use this dataset in a publication, please cite the corresponding paper.

  • Contact person: William F. Broderick, ORCID 0000-0002-8999-9003, wfb229@nyu.edu

This dataset is hosted on OpenNeuro, and can be downloaded from there. Additionally, we present two additional variants of this data, both hosted on this project's OSF page: - Fully-processed data: contains the final output of our analyses, the data required to reproduce the figures as they appear in the paper. - Partially-processed data: contains the outputs of GLMdenoise and all data required to start fitting the spatial frequency response functions.

Both data sets build on top of this one and so require the data contained here as well.

All three of these variants may be downloaded using code found in the Github repo, see the README there for more details.

Overview

  • Spatial frequency preferences

  • Year(s) that the project ran: started gathering pilot data in 2017, this dataset was gathered in the springs of 2019 and 2020. Paper written in 2020 and 2021, submitted fall 2021.

  • Brief overview of the tasks in the experiment: subjects viewed the stimuli, fixating on the center of the images. A sequence of digits, alternating black and white, was presented at fixation; subjects pressed a button whenever a digit repeated. The behavioral data was not presented in the paper and so is not present here. See paper for more details.

  • Description of the contents of the dataset:

    • Summary:
      • 767 Files
      • 12 subjects
      • 1 session each
    • Available tasks:
      • sfprescaled
    • Available modalities:
      • MRI

  • Quality assessment of the data: the MRIQC reports for each included scan can be found on this project's OSF page

Methods

Subjects

Subjects were recruited from graduate students and postdocs at NYU, all experienced MRI participants.

Apparatus

Data was gathered on NYU's Center for Brain Imaging's Siemens Prisma 3T MRI scanner in a shielded room. Data was gathered with subjects lying down, with the stimuli projected onto a screen above their head.

Initial setup

When subjects arrived, subjects were briefed on the task, given the experimental consent form to read and sign, and talked through the screener form.

Task organization

This experiment has only a single task.

Task details

Subjects passively viewed the stimuli while performing the distractor task described above: viewing a stream of alternating black and white digits and pressing a button whenever a digit repeated. Their button presses were recorded.

Additional data acquired

No additional data gathered.

Experimental location

All data gathered at NYU's Center for Brain Imaging in New York, NY.

Missing data

One subject (sub-wlsubj045) only has 7 of the 12 runs, due to technical issues that came up during the run. The quality of their GLMdenoise fits and their final model fits do not appear to vary much from that of the other subjects.

Authors

  • William F. Broderick
  • Jonathan Winawer
  • Eero P. Simoncelli

Dataset DOI

10.18112/openneuro.ds003812.v1.0.0

License

CC0

Acknowledgements

The authors would like to thank Noah C. Benson for his assistance with the retinotopy analysis.

How to Acknowledge

If you use this dataset, please cite both the data set (using the DatasetDOI in this file) and the corresponding paper (as given in ReferencesandLinks).

Funding

  • GRANT NIH R01EY027401 (JW)
  • GRANT NIH R01EY027964 (JW)
  • NSF GRFP (WFB)
  • HHMI (EPS)

References and Links

Ethics Approvals

How To Cite

Copy
William F. Broderick and Jonathan Winawer and Eero P. Simoncelli (2021). spatial_frequency_preferences. OpenNeuro. [Dataset] doi: 10.18112/openneuro.ds003812.v1.0.0
More citation info

Dataset File Tree

Git Hash: 7cd6ca8 

BIDS Validation

We found 2 Warnings in your dataset. You are not required to fix warnings, but doing so will make your dataset more BIDS compliant.

There are files in the /stimuli directory that are not utilized in any _events.tsv file.

There are files in the /stimuli directory that are not utilized in any _events.tsv file.

There are files in the /stimuli directory that are not utilized in any _events.tsv file.

There are files in the /stimuli directory that are not utilized in any _events.tsv file.

There are files in the /stimuli directory that are not utilized in any _events.tsv file.

There are files in the /stimuli directory that are not utilized in any _events.tsv file.

/participants.tsv

Tabular file contains custom columns not described in a data dictionary

Columns: age, sex not defined, please define in: /participants.json

Dataset File Tree

Git Hash: 7cd6ca8 

Comments

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