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

FARCI: Fast and Robust Connectome Inference

Saber Meamardoost, Mahasweta Bhattacharya, EunJung Hwang, Takaki Komiyama, Claudia Mewes, Linbing Wang, Ying Zhang, View ORCID ProfileRudiyanto Gunawan
doi: https://doi.org/10.1101/2020.10.07.330175
Saber Meamardoost
1Department of Chemical and Biological Engineering, University at Buffalo, Buffalo, NY 14260, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Mahasweta Bhattacharya
2Department of Biomedical Engineering, University at Buffalo, Buffalo, NY 14260, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
EunJung Hwang
3Neurobiology Section, Center for Neural Circuits and Behavior, and Department of Neurosciences, University of California San Diego, La Jolla, CA 92093, USA
4Cell Biology and Anatomy Discipline, Center for Brain Function and Repair, Chicago Medical School, Rosalind Franklin University of Medicine and Science, North Chicago, IL 60064, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Takaki Komiyama
3Neurobiology Section, Center for Neural Circuits and Behavior, and Department of Neurosciences, University of California San Diego, La Jolla, CA 92093, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Claudia Mewes
5Department of Physics and Astronomy, University of Alabama, Tuscaloosa, Alabama 35487, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Linbing Wang
6Department of Civil and Environmental Engineering, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Ying Zhang
7Department of Cell and Molecular Biology, University of Rhode Island, Kingston, RI 02881, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Rudiyanto Gunawan
1Department of Chemical and Biological Engineering, University at Buffalo, Buffalo, NY 14260, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Rudiyanto Gunawan
  • For correspondence: rgunawan@buffalo.edu
  • Abstract
  • Full Text
  • Info/History
  • Metrics
  • Data/Code
  • Preview PDF
Loading

Abstract

The inference of neuronal connectome from large-scale neuronal activity recordings, such as two-photon Calcium imaging, represents an active area of research in computational neuroscience. In this work, we developed FARCI (Fast and Robust Connectome Inference), a MATLAB package for neuronal connectome inference from high-dimensional two-photon Calcium fluorescence data. We employed partial correlations as a measure of the functional association strength between pairs of neurons to reconstruct a neuronal connectome. We demonstrated using gold standard datasets from the Neural Connectomics Challenge (NCC) that FARCI provides an accurate connectome and its performance is robust to network sizes, missing neurons, and noise levels. Moreover, FARCI is computationally efficient and highly scalable to large networks. In comparison to the best performing algorithm in the NCC, FARCI produces more accurate networks over different network sizes and subsampling, while providing over two orders of magnitude faster computational speed.

Competing Interest Statement

The authors have declared no competing interest.

Footnotes

  • https://github.com/CABSEL/FARCI

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-NC-ND 4.0 International license.
Back to top
PreviousNext
Posted October 08, 2020.
Download PDF
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.
FARCI: Fast and Robust Connectome Inference
(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
FARCI: Fast and Robust Connectome Inference
Saber Meamardoost, Mahasweta Bhattacharya, EunJung Hwang, Takaki Komiyama, Claudia Mewes, Linbing Wang, Ying Zhang, Rudiyanto Gunawan
bioRxiv 2020.10.07.330175; doi: https://doi.org/10.1101/2020.10.07.330175
Digg logo Reddit logo Twitter logo CiteULike logo Facebook logo Google logo Mendeley logo
Citation Tools
FARCI: Fast and Robust Connectome Inference
Saber Meamardoost, Mahasweta Bhattacharya, EunJung Hwang, Takaki Komiyama, Claudia Mewes, Linbing Wang, Ying Zhang, Rudiyanto Gunawan
bioRxiv 2020.10.07.330175; doi: https://doi.org/10.1101/2020.10.07.330175

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 (2533)
  • Biochemistry (4975)
  • Bioengineering (3486)
  • Bioinformatics (15229)
  • Biophysics (6908)
  • Cancer Biology (5395)
  • Cell Biology (7751)
  • Clinical Trials (138)
  • Developmental Biology (4539)
  • Ecology (7157)
  • Epidemiology (2059)
  • Evolutionary Biology (10233)
  • Genetics (7516)
  • Genomics (9790)
  • Immunology (4860)
  • Microbiology (13231)
  • Molecular Biology (5142)
  • Neuroscience (29464)
  • Paleontology (203)
  • Pathology (838)
  • Pharmacology and Toxicology (1465)
  • Physiology (2142)
  • Plant Biology (4754)
  • Scientific Communication and Education (1013)
  • Synthetic Biology (1338)
  • Systems Biology (4014)
  • Zoology (768)