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Updated readme #66

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Expand Up @@ -5,24 +5,19 @@
[![License](https://img.shields.io/badge/license-GPL3-blue.svg)](./LICENSE)
![https://github.com/psf/black](https://img.shields.io/badge/code%20style-black-000000.svg)
[![All Contributors](https://img.shields.io/badge/all_contributors-2-orange.svg)](#contributors)
[![Paper_link](https://img.shields.io/badge/DOI-10.1038%2Fs41593--021--00947--w-blue)](https://doi.org/10.1038/s41593-021-00947-w)

# bidsMReye

BIDS app using [deepMReye](https://github.com/DeepMReye/DeepMReye) to decode eye
motion for fMRI time series data.
BIDS app for decoding gaze position from the eyeball MR-signal using [deepMReye](https://github.com/DeepMReye/DeepMReye) ([1](https://doi.org/10.1038/s41593-021-00947-w)).

To be used on preprocessed BIDS derivatives (like those from fMRIprep), to
predict eye movements from the bold data when no eye movement data are
available.
To be used on preprocessed BIDS derivatives (e.g. [fMRIprep](https://github.com/nipreps/fmriprep) outputs). No eye-tracking data required.

By default it uses the [deepMReye](https://github.com/DeepMReye/DeepMReye)
[pre-trained "fixation" model](https://osf.io/cqf74).
By default, bidsMReye uses a [pre-trained version](https://osf.io/23t5v) of [deepMReye](https://github.com/DeepMReye/DeepMReye) trained on 5 datasets incl. guided fixations ([2](https://doi.org/10.1038/sdata.2017.181)), smooth pursuit ([3](https://doi.org/10.1016/j.neuroimage.2018.04.012),[4](https://doi.org/10.1101/2021.08.03.454928),[5](https://doi.org/10.1038/s41593-017-0050-8)) and free viewing ([6](https://doi.org/10.1038/s41593-017-0049-1)). Other pretrained versions are optional. Dedicated model training is recommended.

The first part of the pipeline can however be used to extract data, irrespective
of the presence of eye movement labels and could thus be usefull to share
anonimysed subject data to the
[deepMReye](https://github.com/DeepMReye/DeepMReye) dev team to allow them to
improve their pre-trained models.
The pipeline automatically extracts the eyeball voxels and saves them as a python pickle file. This can be used also for other multivariate pattern analyses in the absence of eye-tracking data. Decoded gaze positions allow computing eye movements.

For more information, see the [User Recommendations](https://deepmreye.slite.com/p/channel/MUgmvViEbaATSrqt3susLZ/notes/kKdOXmLqe). If you have other questions, please reach out to the developer team.

## Install

Expand Down Expand Up @@ -91,3 +86,5 @@ Thanks goes to these wonderful people
This project follows the
[all-contributors](https://github.com/all-contributors/all-contributors)
specification. Contributions of any kind welcome!

If you train [deepMReye](https://github.com/DeepMReye/DeepMReye), or if you have eye-tracking training labels and the extracted eyeball voxels, consider sharing it to contribute to the [pretrained model pool](https://osf.io/mrhk9/).