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

Clustering and compositionality of task representations in a neural network trained to perform many cognitive tasks

Guangyu Robert Yang, H. Francis Song, William T. Newsome, Xiao-Jing Wang
doi: https://doi.org/10.1101/183632
Guangyu Robert Yang
1Center for Neural Science, New York University, 4 Washington Place, New York, NY 10003
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
H. Francis Song
1Center for Neural Science, New York University, 4 Washington Place, New York, NY 10003
5Current address: DeepMind, London EC4A 3TW, United Kingdom.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
William T. Newsome
3Department of Neurobiology, Stanford University, Stanford, CA 94305, USA
4Howard Hughes Medical Institute, Stanford University, Stanford, CA 94305, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Xiao-Jing Wang
1Center for Neural Science, New York University, 4 Washington Place, New York, NY 10003
2NYU-ECNU Institute of Brain and Cognitive Science, NYU Shanghai, Shanghai, China
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • Abstract
  • Full Text
  • Info/History
  • Metrics
  • Preview PDF
Loading

ABSTRACT

A neural system has the ability to flexibly perform many tasks, but the underlying mechanism cannot be elucidated in traditional experimental and modeling studies designed for one task at a time. Here, we trained a single network model to perform 20 cognitive tasks that may involve working memory, decision-making, categorization and inhibitory control. We found that after training, recurrent units developed into clusters that are functionally specialized for various cognitive processes. We introduce a measure to quantify relationships between single-unit neural representations of tasks, and report five distinct types of such relationships that can be tested experimentally. Surprisingly, our network developed compositionality of task representations, a critical feature for cognitive flexibility, whereby one task can be performed by recombining instructions for other tasks. Finally, we demonstrate how the network could learn multiple tasks sequentially. This work provides a computational platform to investigate neural representations of many cognitive tasks.

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 September 01, 2017.
Download PDF
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.
Clustering and compositionality of task representations in a neural network trained to perform many cognitive tasks
(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
Clustering and compositionality of task representations in a neural network trained to perform many cognitive tasks
Guangyu Robert Yang, H. Francis Song, William T. Newsome, Xiao-Jing Wang
bioRxiv 183632; doi: https://doi.org/10.1101/183632
Reddit logo Twitter logo Facebook logo LinkedIn logo Mendeley logo
Citation Tools
Clustering and compositionality of task representations in a neural network trained to perform many cognitive tasks
Guangyu Robert Yang, H. Francis Song, William T. Newsome, Xiao-Jing Wang
bioRxiv 183632; doi: https://doi.org/10.1101/183632

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 (4223)
  • Biochemistry (9101)
  • Bioengineering (6748)
  • Bioinformatics (23930)
  • Biophysics (12081)
  • Cancer Biology (9488)
  • Cell Biology (13726)
  • Clinical Trials (138)
  • Developmental Biology (7614)
  • Ecology (11654)
  • Epidemiology (2066)
  • Evolutionary Biology (15473)
  • Genetics (10613)
  • Genomics (14291)
  • Immunology (9454)
  • Microbiology (22773)
  • Molecular Biology (9066)
  • Neuroscience (48831)
  • Paleontology (354)
  • Pathology (1479)
  • Pharmacology and Toxicology (2560)
  • Physiology (3820)
  • Plant Biology (8307)
  • Scientific Communication and Education (1467)
  • Synthetic Biology (2288)
  • Systems Biology (6168)
  • Zoology (1297)