Are single-peaked tuning curves tuned for speed rather than accuracy?

  1. Movitz Lenninger  Is a corresponding author
  2. Mikael Skoglund
  3. Pawel Andrzej Herman
  4. Arvind Kumar  Is a corresponding author
  1. KTH Royal Institute of Technology, Sweden

Abstract

According to the efficient coding hypothesis, sensory neurons are adapted to provide maximal information about the environment, given some biophysical constraints. In early visual areas, stimulus-induced modulations of neural activity (or tunings) are predominantly single-peaked. However, periodic tuning, as exhibited by grid cells, has been linked to a significant increase in decoding performance. Does this imply that the tuning curves in early visual areas are sub-optimal? We argue that the time scale at which neurons encode information is imperative to understanding the advantages of single-peaked and periodic tuning curves. Here, we show that the possibility of catastrophic (large) errors creates a trade-off between decoding time and decoding ability. We investigate how decoding time and stimulus dimensionality affect the optimal shape of tuning curves for removing catastrophic errors. In particular, we focus on the spatial periods of the tuning curves for a class of circular tuning curves. We show an overall trend for minimal decoding time to increase with increasing Fisher information, implying a trade-off between accuracy and speed. This trade-off is reinforced whenever the stimulus dimensionality is high, or there is ongoing activity. Thus, given constraints on processing speed, we present normative arguments for the existence of the single-peaked tuning organization observed in early visual areas.

Data availability

Code has been made publicly available on Github (https://github.com/movitzle/Short_Decoding_Time)

Article and author information

Author details

  1. Movitz Lenninger

    Division of Information Science and Engineering, KTH Royal Institute of Technology, Stockholm, Sweden
    For correspondence
    movitzle@kth.se
    Competing interests
    The authors declare that no competing interests exist.
  2. Mikael Skoglund

    Division of Information Science and Engineering, KTH Royal Institute of Technology, Stockholm, Sweden
    Competing interests
    The authors declare that no competing interests exist.
  3. Pawel Andrzej Herman

    Division of Computational Science and Technology, KTH Royal Institute of Technology, Stockholm, Sweden
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-6553-823X
  4. Arvind Kumar

    Division of Computational Science and Technology, KTH Royal Institute of Technology, Stockholm, Sweden
    For correspondence
    arvkumar@kth.se
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-8044-9195

Funding

Digital Futures

  • Movitz Lenninger
  • Mikael Skoglund
  • Pawel Andrzej Herman
  • Arvind Kumar

Vetenskapsrådet

  • Arvind Kumar

Institute of Advanced Studies Fellowship, University of Strasbourg, France

  • Arvind Kumar

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

Reviewing Editor

  1. Peter Latham, University College London, United Kingdom

Version history

  1. Preprint posted: September 10, 2022 (view preprint)
  2. Received: October 28, 2022
  3. Accepted: May 11, 2023
  4. Accepted Manuscript published: May 16, 2023 (version 1)
  5. Version of Record published: June 9, 2023 (version 2)

Copyright

© 2023, Lenninger 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.

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  1. Movitz Lenninger
  2. Mikael Skoglund
  3. Pawel Andrzej Herman
  4. Arvind Kumar
(2023)
Are single-peaked tuning curves tuned for speed rather than accuracy?
eLife 12:e84531.
https://doi.org/10.7554/eLife.84531

Share this article

https://doi.org/10.7554/eLife.84531

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