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

Extracting neural signals from semi-immobilized animals with deformable non-negative matrix factorization

View ORCID ProfileAmin Nejatbakhsh, View ORCID ProfileErdem Varol, View ORCID ProfileEviatar Yemini, View ORCID ProfileVivek Venkatachalam, View ORCID ProfileAlbert Lin, View ORCID ProfileAravinthan D.T. Samuel, Liam Paninski
doi: https://doi.org/10.1101/2020.07.07.192120
Amin Nejatbakhsh
1Department of Neuroscience, Columbia University, New York, NY 10025
2Department of Statistics, Columbia University, New York, NY 10025
3Grossman Center for the Statistics of Mind, Columbia University, New York, NY 10025
4Zuckerman Institute, Center for Theoretical Neuroscience, Columbia University, New York, NY 10025
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Amin Nejatbakhsh
  • For correspondence: mn2822@columbia.edu
Erdem Varol
1Department of Neuroscience, Columbia University, New York, NY 10025
2Department of Statistics, Columbia University, New York, NY 10025
3Grossman Center for the Statistics of Mind, Columbia University, New York, NY 10025
4Zuckerman Institute, Center for Theoretical Neuroscience, Columbia University, New York, NY 10025
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Erdem Varol
Eviatar Yemini
5Department of Biological Sciences, Columbia University, New York, NY 10025
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Eviatar Yemini
Vivek Venkatachalam
6Department of Physics, Northeastern University, Boston, MA 02115
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Vivek Venkatachalam
Albert Lin
7Department of Physics, Harvard University, Cambridge, MA 02138
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Albert Lin
Aravinthan D.T. Samuel
7Department of Physics, Harvard University, Cambridge, MA 02138
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Aravinthan D.T. Samuel
Liam Paninski
1Department of Neuroscience, Columbia University, New York, NY 10025
2Department of Statistics, Columbia University, New York, NY 10025
3Grossman Center for the Statistics of Mind, Columbia University, New York, NY 10025
4Zuckerman Institute, Center for Theoretical Neuroscience, Columbia University, New York, NY 10025
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • Abstract
  • Full Text
  • Info/History
  • Metrics
  • Supplementary material
  • Data/Code
  • Preview PDF
Loading

Abstract

Extracting calcium traces from populations of neurons is a critical step in the study of the large-scale neural dynamics that govern behavior. Accurate activity extraction requires the correction of motion and movement-induced deformations as well as demixing of signals that may overlap spatially due to limitations in optical resolution. Traditionally, non-negative matrix factorization (NMF) methods have been successful in demixing and denoising cellular calcium activity in relatively motionless or pre-registered videos. However, standard NMF methods fail in animals undergoing significant non-rigid motion; similarly, standard image registration methods based on template matching can fail when large changes in activity lead to mismatches with the image template. To address these issues simultaneously, we introduce a deformable non-negative matrix factorization (dNMF) framework that jointly optimizes registration with signal demixing. On simulated data and real semi-immobilized C. elegans microscopy videos, dNMF outperforms traditional demixing methods that account for motion and demixing separately. Finally, following the extraction of neural traces from multiple imaging experiments, we develop a quantile regression time-series normalization technique to account for varying neural signal intensity baselines across different animals or different imaging setups. Open source code implementing this pipeline is available at https://github.com/amin-nejat/dNMF.

Competing Interest Statement

The authors have declared no competing interest.

Footnotes

  • https://github.com/amin-nejat/dNMF

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. All rights reserved. No reuse allowed without permission.
Back to top
PreviousNext
Posted July 08, 2020.
Download PDF

Supplementary Material

Data/Code
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.
Extracting neural signals from semi-immobilized animals with deformable non-negative matrix factorization
(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
Extracting neural signals from semi-immobilized animals with deformable non-negative matrix factorization
Amin Nejatbakhsh, Erdem Varol, Eviatar Yemini, Vivek Venkatachalam, Albert Lin, Aravinthan D.T. Samuel, Liam Paninski
bioRxiv 2020.07.07.192120; doi: https://doi.org/10.1101/2020.07.07.192120
Reddit logo Twitter logo Facebook logo LinkedIn logo Mendeley logo
Citation Tools
Extracting neural signals from semi-immobilized animals with deformable non-negative matrix factorization
Amin Nejatbakhsh, Erdem Varol, Eviatar Yemini, Vivek Venkatachalam, Albert Lin, Aravinthan D.T. Samuel, Liam Paninski
bioRxiv 2020.07.07.192120; doi: https://doi.org/10.1101/2020.07.07.192120

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 (4685)
  • Biochemistry (10362)
  • Bioengineering (7682)
  • Bioinformatics (26343)
  • Biophysics (13534)
  • Cancer Biology (10694)
  • Cell Biology (15446)
  • Clinical Trials (138)
  • Developmental Biology (8501)
  • Ecology (12824)
  • Epidemiology (2067)
  • Evolutionary Biology (16867)
  • Genetics (11401)
  • Genomics (15484)
  • Immunology (10620)
  • Microbiology (25225)
  • Molecular Biology (10225)
  • Neuroscience (54481)
  • Paleontology (402)
  • Pathology (1669)
  • Pharmacology and Toxicology (2897)
  • Physiology (4345)
  • Plant Biology (9252)
  • Scientific Communication and Education (1587)
  • Synthetic Biology (2558)
  • Systems Biology (6781)
  • Zoology (1466)