1. Neuroscience
Download icon

Stable and dynamic representations of value in the prefrontal cortex

  1. Pierre Enel  Is a corresponding author
  2. Joni D Wallis
  3. Erin L Rich
  1. Icahn School of Medicine at Mount Sinai, United States
  2. University of California, Berkeley, United States
Research Article
  • Cited 8
  • Views 2,717
  • Annotations
Cite this article as: eLife 2020;9:e54313 doi: 10.7554/eLife.54313

Abstract

Optimal decision-making requires that stimulus-value associations are kept up to date by constantly comparing the expected value of a stimulus with its experienced outcome. To do this, value information must be held in mind when a stimulus and outcome are separated in time. However, little is known about the neural mechanisms of working memory (WM) for value. Contradicting theories have suggested WM requires either persistent or transient neuronal activity, with stable or dynamic representations respectively. To test these hypotheses, we recorded neuronal activity in the orbitofrontal and anterior cingulate cortex of two monkeys performing a valuation task. We found that features of all hypotheses were simultaneously present in prefrontal activity, and no single hypothesis was exclusively supported. Instead, mixed dynamics supported robust, time invariant value representations while also encoding the information in a temporally specific manner. We suggest that this hybrid coding is a critical mechanism supporting flexible cognitive abilities.

Data availability

The neural recording data analyzed in this paper is available online at https://doi.org/10.5061/dryad.4j0zpc88b

The following data sets were generated

Article and author information

Author details

  1. Pierre Enel

    Department of Neurosience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, United States
    For correspondence
    pierre.enel@mssm.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-8983-6223
  2. Joni D Wallis

    Helen Wills Neuroscience Institute, Department of Psychology, University of California, Berkeley, Berkeley, United States
    Competing interests
    The authors declare that no competing interests exist.
  3. Erin L Rich

    Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, United States
    Competing interests
    The authors declare that no competing interests exist.

Funding

National Institute of Mental Health (R01-MH121448)

  • Joni D Wallis

National Institute of Mental Health (R01-MH097990)

  • Joni D Wallis

Hilda and Preston Davis Foundation (Postdoctoral fellowship)

  • Erin L Rich

National Institute on Drug Abuse (K08-DA039051)

  • Erin L Rich

National Institute of Mental Health (R01-MH117763)

  • Joni D Wallis

Whitehall Foundation Research Grant (Postdoctoral fellowship)

  • Erin L Rich

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Ethics

Animal experimentation: This study was performed in strict accordance with the recommendations in the Guide for the Care and Use of Laboratory Animals of the National Institutes of Health (Assurance Number A3084-01). All of the animals were handled according to approved institutional animal care and use committee (IACUC) protocols (Protocol Number R283) of the University of California at Berkeley. All surgery was performed under isoflurane anesthesia, and every effort was made to minimize suffering.

Reviewing Editor

  1. Geoffrey Schoenbaum, National Institute on Drug Abuse, National Institutes of Health, United States

Publication history

  1. Received: December 10, 2019
  2. Accepted: July 6, 2020
  3. Accepted Manuscript published: July 6, 2020 (version 1)
  4. Accepted Manuscript updated: July 8, 2020 (version 2)
  5. Version of Record published: July 29, 2020 (version 3)

Copyright

© 2020, Enel et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

Metrics

  • 2,717
    Page views
  • 409
    Downloads
  • 8
    Citations

Article citation count generated by polling the highest count across the following sources: Crossref, PubMed Central, Scopus.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Download citations (links to download the citations from this article in formats compatible with various reference manager tools)

Open citations (links to open the citations from this article in various online reference manager services)

Further reading

    1. Neuroscience
    Casey Paquola et al.
    Tools and Resources Updated

    Neuroimaging stands to benefit from emerging ultrahigh-resolution 3D histological atlases of the human brain; the first of which is ‘BigBrain’. Here, we review recent methodological advances for the integration of BigBrain with multi-modal neuroimaging and introduce a toolbox, ’BigBrainWarp’, that combines these developments. The aim of BigBrainWarp is to simplify workflows and support the adoption of best practices. This is accomplished with a simple wrapper function that allows users to easily map data between BigBrain and standard MRI spaces. The function automatically pulls specialised transformation procedures, based on ongoing research from a wide collaborative network of researchers. Additionally, the toolbox improves accessibility of histological information through dissemination of ready-to-use cytoarchitectural features. Finally, we demonstrate the utility of BigBrainWarp with three tutorials and discuss the potential of the toolbox to support multi-scale investigations of brain organisation.

    1. Neuroscience
    Gabriella R Sterne et al.
    Tools and Resources Updated

    Neural circuits carry out complex computations that allow animals to evaluate food, select mates, move toward attractive stimuli, and move away from threats. In insects, the subesophageal zone (SEZ) is a brain region that receives gustatory, pheromonal, and mechanosensory inputs and contributes to the control of diverse behaviors, including feeding, grooming, and locomotion. Despite its importance in sensorimotor transformations, the study of SEZ circuits has been hindered by limited knowledge of the underlying diversity of SEZ neurons. Here, we generate a collection of split-GAL4 lines that provides precise genetic targeting of 138 different SEZ cell types in adult Drosophila melanogaster, comprising approximately one third of all SEZ neurons. We characterize the single-cell anatomy of these neurons and find that they cluster by morphology into six supergroups that organize the SEZ into discrete anatomical domains. We find that the majority of local SEZ interneurons are not classically polarized, suggesting rich local processing, whereas SEZ projection neurons tend to be classically polarized, conveying information to a limited number of higher brain regions. This study provides insight into the anatomical organization of the SEZ and generates resources that will facilitate further study of SEZ neurons and their contributions to sensory processing and behavior.