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  Magnetic resonance-based eye tracking using deep neural networks

Frey, M., Nau, M., & Doeller, C. F. (2021). Magnetic resonance-based eye tracking using deep neural networks. Nature Neuroscience, 24(12), 1772-1779. doi:10.1038/s41593-021-00947-w.

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Item Permalink: https://hdl.handle.net/21.11116/0000-0009-79CA-C Version Permalink: https://hdl.handle.net/21.11116/0000-000D-0735-0
Genre: Journal Article

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 Creators:
Frey, Markus1, 2, Author
Nau, Matthias1, 2, Author
Doeller, Christian F.1, 2, 3, Author           
Affiliations:
1Egil and Pauline Braathen and Fred Kavli Centre for Cortical Microcircuits, Kavli Institute, Norwegian University of Science and Technology, Trondheim, Norway, ou_persistent22              
2Department Psychology (Doeller), MPI for Human Cognitive and Brain Sciences, Max Planck Society, Leipzig, DE, ou_2591710              
3Institute of Psychology, University of Leipzig, Germany, ou_persistent22              

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Free keywords: Cognitive neuroscience; Computational neuroscience; Oculomotor system; Visual system
 Abstract: Viewing behavior provides a window into many central aspects of human cognition and health, and it is an important variable of interest or confound in many functional magnetic resonance imaging (fMRI) studies. To make eye tracking freely and widely available for MRI research, we developed DeepMReye, a convolutional neural network (CNN) that decodes gaze position from the magnetic resonance signal of the eyeballs. It performs cameraless eye tracking at subimaging temporal resolution in held-out participants with little training data and across a broad range of scanning protocols. Critically, it works even in existing datasets and when the eyes are closed. Decoded eye movements explain network-wide brain activity also in regions not associated with oculomotor function. This work emphasizes the importance of eye tracking for the interpretation of fMRI results and provides an open source software solution that is widely applicable in research and clinical settings.

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Language(s): eng - English
 Dates: 2020-10-222021-09-172021-11-082021-12
 Publication Status: Issued
 Pages: -
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 Table of Contents: -
 Rev. Type: -
 Identifiers: DOI: 10.1038/s41593-021-00947-w
Other: epub 2021
PMID: 34750593
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Project name : -
Grant ID : ERC-CoG GEOCOG 724836
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Funding organization : European Research Council (ERC)
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Funding program : -
Funding organization : Max Planck Society
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Funding organization : Kavli Foundation
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Funding organization : Centre of Excellence scheme of the Research Council of Norway
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Grant ID : 223262/F50
Funding program : -
Funding organization : Centre for Neural Computation
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Funding organization : The Egil and Pauline Braathen and Fred Kavli Centre for Cortical Microcircuits
Project name : -
Grant ID : 197467/F50
Funding program : -
Funding organization : National Infrastructure scheme of the Research Council of Norway, NORBRAIN

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Title: Nature Neuroscience
  Other : Nat. Neurosci.
Source Genre: Journal
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Pages: - Volume / Issue: 24 (12) Sequence Number: - Start / End Page: 1772 - 1779 Identifier: ISSN: 1097-6256
CoNE: https://pure.mpg.de/cone/journals/resource/954925610931