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

Encoding of reinforcement along the hippocampal long axis and the transition from exploration to exploitation

View ORCID ProfileAlexandre Y. Dombrovski, View ORCID ProfileBeatriz Luna, View ORCID ProfileMichael N. Hallquist
doi: https://doi.org/10.1101/2020.01.02.893255
Alexandre Y. Dombrovski
Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, 15213, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Alexandre Y. Dombrovski
Beatriz Luna
Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, 15213, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Beatriz Luna
Michael N. Hallquist
Department of Psychology, Penn State University, University Park, PA 16801, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Michael N. Hallquist
  • For correspondence: michael.hallquist@gmail.com
  • Abstract
  • Full Text
  • Info/History
  • Metrics
  • Supplementary material
  • Preview PDF
Loading

SUMMARY

Hippocampal maps incorporate reward information, yet the functional contributions of the anterior and posterior hippocampal divisions (AH and PH) to reinforcement learning remain unclear. Here, we examined exploration and exploitation of a continuous unidimensional task with a basis function reinforcement learning model. In model-based fMRI analyses, we found doubly dissociated representations along the hippocampal long axis: state-wise reward prediction error signals in the PH (tail) and global value maximum signals in the AH (anterior body). PH prediction error signals predicted exploration whereas AH global value maximum signals predicted exploitation. AH-mediated exploitation depended on value representations compressed across episodes and options. PH responses to reinforcement were early and phasic while AH responses were delayed and evolved throughout learning. During choice, AH (head) displayed goal cell-like responses to the global value maximum. In summary, granular reinforcement representations in PH facilitate exploration and compressed representations of the value maximum in AH facilitate exploitation.

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 January 02, 2020.
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.
Encoding of reinforcement along the hippocampal long axis and the transition from exploration to exploitation
(Your Name) has forwarded a page to you from bioRxiv
(Your Name) thought you would like to see this page from the bioRxiv website.
Share
Encoding of reinforcement along the hippocampal long axis and the transition from exploration to exploitation
Alexandre Y. Dombrovski, Beatriz Luna, Michael N. Hallquist
bioRxiv 2020.01.02.893255; doi: https://doi.org/10.1101/2020.01.02.893255
Digg logo Reddit logo Twitter logo CiteULike logo Facebook logo Google logo Mendeley logo
Citation Tools
Encoding of reinforcement along the hippocampal long axis and the transition from exploration to exploitation
Alexandre Y. Dombrovski, Beatriz Luna, Michael N. Hallquist
bioRxiv 2020.01.02.893255; doi: https://doi.org/10.1101/2020.01.02.893255

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 (1647)
  • Biochemistry (2739)
  • Bioengineering (1907)
  • Bioinformatics (10243)
  • Biophysics (4183)
  • Cancer Biology (3218)
  • Cell Biology (4538)
  • Clinical Trials (135)
  • Developmental Biology (2840)
  • Ecology (4460)
  • Epidemiology (2041)
  • Evolutionary Biology (7231)
  • Genetics (5476)
  • Genomics (6813)
  • Immunology (2388)
  • Microbiology (7483)
  • Molecular Biology (2992)
  • Neuroscience (18584)
  • Paleontology (136)
  • Pathology (472)
  • Pharmacology and Toxicology (780)
  • Physiology (1149)
  • Plant Biology (2706)
  • Scientific Communication and Education (680)
  • Synthetic Biology (888)
  • Systems Biology (2846)
  • Zoology (468)