Skip to main content
bioRxiv
  • Home
  • About
  • Submit
  • ALERTS / RSS
Advanced Search
New Results

Stimulus domain transfer in recurrent models for large scale cortical population prediction on video

View ORCID ProfileFabian H. Sinz, View ORCID ProfileAlexander S. Ecker, View ORCID ProfilePaul G. Fahey, View ORCID ProfileEdgar Y. Walker, Erick Cobos, Emmanouil Froudarakis, Dimitri Yatsenko, View ORCID ProfileXaq Pitkow, Jacob Reimer, View ORCID ProfileAndreas S. Tolias
doi: https://doi.org/10.1101/452672
Fabian H. Sinz
1Department of Neuroscience, Baylor College of Medicine, Houston, TX, USA
2Center for Neuroscience and Artificial Intelligence, Baylor College of Medicine, Houston, TX, USA
5Bernstein Center for Computational Neuroscience, University of Tübingen, Germany
7Institute for Computer Science, University of Tübingen, Germany
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Fabian H. Sinz
  • For correspondence: sinz@bcm.edu
Alexander S. Ecker
2Center for Neuroscience and Artificial Intelligence, Baylor College of Medicine, Houston, TX, USA
4Centre for Integrative Neuroscience, University of Tübingen, Germany
5Bernstein Center for Computational Neuroscience, University of Tübingen, Germany
6Institute for Theoretical Physics, University of Tübingen, Germany
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Alexander S. Ecker
Paul G. Fahey
1Department of Neuroscience, Baylor College of Medicine, Houston, TX, USA
2Center for Neuroscience and Artificial Intelligence, Baylor College of Medicine, Houston, TX, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Paul G. Fahey
Edgar Y. Walker
1Department of Neuroscience, Baylor College of Medicine, Houston, TX, USA
2Center for Neuroscience and Artificial Intelligence, Baylor College of Medicine, Houston, TX, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Edgar Y. Walker
Erick Cobos
1Department of Neuroscience, Baylor College of Medicine, Houston, TX, USA
2Center for Neuroscience and Artificial Intelligence, Baylor College of Medicine, Houston, TX, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Emmanouil Froudarakis
1Department of Neuroscience, Baylor College of Medicine, Houston, TX, USA
2Center for Neuroscience and Artificial Intelligence, Baylor College of Medicine, Houston, TX, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Dimitri Yatsenko
1Department of Neuroscience, Baylor College of Medicine, Houston, TX, USA
2Center for Neuroscience and Artificial Intelligence, Baylor College of Medicine, Houston, TX, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Xaq Pitkow
1Department of Neuroscience, Baylor College of Medicine, Houston, TX, USA
2Center for Neuroscience and Artificial Intelligence, Baylor College of Medicine, Houston, TX, USA
3Department of Electrical and Computer Engineering, Rice University, Houston, TX, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Xaq Pitkow
Jacob Reimer
1Department of Neuroscience, Baylor College of Medicine, Houston, TX, USA
2Center for Neuroscience and Artificial Intelligence, Baylor College of Medicine, Houston, TX, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Andreas S. Tolias
1Department of Neuroscience, Baylor College of Medicine, Houston, TX, USA
2Center for Neuroscience and Artificial Intelligence, Baylor College of Medicine, Houston, TX, USA
3Department of Electrical and Computer Engineering, Rice University, Houston, TX, USA
5Bernstein Center for Computational Neuroscience, University of Tübingen, Germany
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Andreas S. Tolias
  • Abstract
  • Full Text
  • Info/History
  • Metrics
  • Supplementary material
  • Preview PDF
Loading

Abstract

To better understand the representations in visual cortex, we need to generate better predictions of neural activity in awake animals presented with their ecological input: natural video. Despite recent advances in models for static images, models for predicting responses to natural video are scarce and standard linear-nonlinear models perform poorly. We developed a new deep recurrent network architecture that predicts inferred spiking activity of thousands of mouse V1 neurons simultaneously recorded with two-photon microscopy, while accounting for confounding factors such as the animal‘s gaze position and brain state changes related to running state and pupil dilation. Powerful system identification models provide an opportunity to gain insight into cortical functions through in silico experiments that can subsequently be tested in the brain. However, in many cases this approach requires that the model is able to generalize to stimulus statistics that it was not trained on, such as band-limited noise and other parameterized stimuli. We investigated these domain transfer properties in our model and find that our model trained on natural images is able to correctly predict the orientation tuning of neurons in responses to artificial noise stimuli. Finally, we show that we can fully generalize from movies to noise and maintain high predictive performance on both stimulus domains by fine-tuning only the final layer’s weights on a network otherwise trained on natural movies. The converse, however, is not true.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-ND 4.0 International license.
Back to top
PreviousNext
Posted October 25, 2018.
Download PDF

Supplementary Material

Email

Thank you for your interest in spreading the word about bioRxiv.

NOTE: Your email address is requested solely to identify you as the sender of this article.

Enter multiple addresses on separate lines or separate them with commas.
Stimulus domain transfer in recurrent models for large scale cortical population prediction on video
(Your Name) has forwarded a page to you from bioRxiv
(Your Name) thought you would like to see this page from the bioRxiv website.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Share
Stimulus domain transfer in recurrent models for large scale cortical population prediction on video
Fabian H. Sinz, Alexander S. Ecker, Paul G. Fahey, Edgar Y. Walker, Erick Cobos, Emmanouil Froudarakis, Dimitri Yatsenko, Xaq Pitkow, Jacob Reimer, Andreas S. Tolias
bioRxiv 452672; doi: https://doi.org/10.1101/452672
Digg logo Reddit logo Twitter logo Facebook logo Google logo LinkedIn logo Mendeley logo
Citation Tools
Stimulus domain transfer in recurrent models for large scale cortical population prediction on video
Fabian H. Sinz, Alexander S. Ecker, Paul G. Fahey, Edgar Y. Walker, Erick Cobos, Emmanouil Froudarakis, Dimitri Yatsenko, Xaq Pitkow, Jacob Reimer, Andreas S. Tolias
bioRxiv 452672; doi: https://doi.org/10.1101/452672

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
  • Tweet Widget
  • Facebook Like
  • Google Plus One

Subject Area

  • Neuroscience
Subject Areas
All Articles
  • Animal Behavior and Cognition (3607)
  • Biochemistry (7581)
  • Bioengineering (5529)
  • Bioinformatics (20809)
  • Biophysics (10338)
  • Cancer Biology (7988)
  • Cell Biology (11647)
  • Clinical Trials (138)
  • Developmental Biology (6611)
  • Ecology (10217)
  • Epidemiology (2065)
  • Evolutionary Biology (13630)
  • Genetics (9550)
  • Genomics (12854)
  • Immunology (7925)
  • Microbiology (19555)
  • Molecular Biology (7668)
  • Neuroscience (42147)
  • Paleontology (308)
  • Pathology (1258)
  • Pharmacology and Toxicology (2203)
  • Physiology (3269)
  • Plant Biology (7051)
  • Scientific Communication and Education (1294)
  • Synthetic Biology (1952)
  • Systems Biology (5429)
  • Zoology (1119)