pRFs / Benson14-Retinotopy

This app will This app will automatically map population receptive field (pRF) data to the cortical surface of a participant using just the Freesurfer datatype as input. This method is based on methodologies published in Benson et al (2014) and runs code from the neuropythy docker container.

Authors

• Brad Caron (bacaron@utexas.edu)
• David Hunt (dhunt@iu.edu)

Contributors

• Soichi Hayashi (shayashi@iu.edu)

Funding Acknowledgement

brainlife.io is publicly funded and for the sustainability of the project it is helpful to Acknowledge the use of the platform. We kindly ask that you acknowledge the funding below in your publications and code reusing this code.

Citations

We kindly ask that you cite the following articles when publishing papers and code using this code.

1. Avesani, P., McPherson, B., Hayashi, S. et al. The open diffusion data derivatives, brain data upcycling via integrated publishing of derivatives and reproducible open cloud services. Sci Data 6, 69 (2019). https://doi.org/10.1038/s41597-019-0073-y

2. Benson NC, Butt OH, Datta R, Radoeva PD, Brainard DH, Aguirre GK. The retinotopic organization of striate cortex is well predicted by surface topology.

3. Benson NC, Butt OH, Brainard DH, Aguirre GK. Correction of distortion in flattened representations of the cortical surface allows prediction of V1-V3 functional organization from anatomy. PLoS Computational Biology. 2014;10:e1003538. doi: 10.1371/journal.pcbi.1003538.

4. Benson NC, Winawer J. Bayesian analysis of retinotopic maps. Elife. 2018;7:e40224. Published 2018 Dec 6. doi:10.7554/eLife.40224

MIT Copyright (c) 2020 brainlife.io The University of Texas at Austin and Indiana University

Running the App

On Brainlife.io

You can submit this App online at https://doi.org/https://doi.org/10.25663/brainlife.app.559 via the 'Execute' tab.

Running Locally (on your machine)

1. git clone this repo

2. Inside the cloned directory, create config.json with something like the following content with paths to your input files.

{
	"freesurfer": "/input/freesurfer/output",
	"template": "Benson14"
}

Sample Datasets

You can download sample datasets from Brainlife using Brainlife CLI.

npm install -g brainlife
bl login
mkdir input
bl dataset download

3. Launch the App by executing 'main'

./main

Output

The main output of this App is a prf datatype, a parcellation/volume datatype containing the visual areas in volume space, a surface/data datatype containing the surface data files, a surface/vertices datatype containing the pial and white surfaces, and a parcellation/surface-deprecated datatype combining the surface/data and surface/vertices into the same datatype.

Product.json

The secondary output of this app is product.json. This file allows web interfaces, DB and API calls on the results of the processing.

Dependencies

This App only requires singularity to run. If you don't have singularity, you will need to install following dependencies.

• neuropythy: https://github.com/noahbenson/neuropythy

MIT Copyright (c) 2020 brainlife.io The University of Texas at Austin and Indiana University