IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0089762.html
   My bibliography  Save this article

Bayesian Integration of Information in Hippocampal Place Cells

Author

Listed:
  • Tamas Madl
  • Stan Franklin
  • Ke Chen
  • Daniela Montaldi
  • Robert Trappl

Abstract

Accurate spatial localization requires a mechanism that corrects for errors, which might arise from inaccurate sensory information or neuronal noise. In this paper, we propose that Hippocampal place cells might implement such an error correction mechanism by integrating different sources of information in an approximately Bayes-optimal fashion. We compare the predictions of our model with physiological data from rats. Our results suggest that useful predictions regarding the firing fields of place cells can be made based on a single underlying principle, Bayesian cue integration, and that such predictions are possible using a remarkably small number of model parameters.

Suggested Citation

  • Tamas Madl & Stan Franklin & Ke Chen & Daniela Montaldi & Robert Trappl, 2014. "Bayesian Integration of Information in Hippocampal Place Cells," PLOS ONE, Public Library of Science, vol. 9(3), pages 1-16, March.
    • Handle: RePEc:plo:pone00:0089762
    DOI: 10.1371/journal.pone.0089762
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0089762
    Download Restriction: no
    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0089762&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pone.0089762?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Marc O. Ernst & Martin S. Banks, 2002. "Humans integrate visual and haptic information in a statistically optimal fashion," Nature, Nature, vol. 415(6870), pages 429-433, January.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Simon Weiler & Vahid Rahmati & Marcel Isstas & Johann Wutke & Andreas Walter Stark & Christian Franke & Jürgen Graf & Christian Geis & Otto W. Witte & Mark Hübener & Jürgen Bolz & Troy W. Margrie & Kn, 2024. "A primary sensory cortical interareal feedforward inhibitory circuit for tacto-visual integration," Nature Communications, Nature, vol. 15(1), pages 1-24, December.
    2. Catarina Mendonça & Pietro Mandelli & Ville Pulkki, 2016. "Modeling the Perception of Audiovisual Distance: Bayesian Causal Inference and Other Models," PLOS ONE, Public Library of Science, vol. 11(12), pages 1-18, December.
    3. Jacques Pesnot Lerousseau & Cesare V. Parise & Marc O. Ernst & Virginie Wassenhove, 2022. "Multisensory correlation computations in the human brain identified by a time-resolved encoding model," Nature Communications, Nature, vol. 13(1), pages 1-12, December.
    4. Wen-Hao Zhang & Si Wu & Krešimir Josić & Brent Doiron, 2023. "Sampling-based Bayesian inference in recurrent circuits of stochastic spiking neurons," Nature Communications, Nature, vol. 14(1), pages 1-19, December.
    5. Marine Hainguerlot & Thibault Gajdos & Jean-Christophe Vergnaud & Vincent de Gardelle, 2023. "How Overconfidence Bias Influences Suboptimality in Perceptual Decision Making," PSE-Ecole d'économie de Paris (Postprint) hal-04197403, HAL.
    6. Adam N Sanborn & Ulrik R Beierholm, 2016. "Fast and Accurate Learning When Making Discrete Numerical Estimates," PLOS Computational Biology, Public Library of Science, vol. 12(4), pages 1-28, April.
    7. Patricia Besson & Christophe Bourdin & Lionel Bringoux, 2011. "A Comprehensive Model of Audiovisual Perception: Both Percept and Temporal Dynamics," PLOS ONE, Public Library of Science, vol. 6(8), pages 1-11, August.
    8. Anthony Renard & Evan R. Harrell & Brice Bathellier, 2022. "Olfactory modulation of barrel cortex activity during active whisking and passive whisker stimulation," Nature Communications, Nature, vol. 13(1), pages 1-13, December.
    9. Seth W. Egger & Stephen G. Lisberger, 2022. "Neural structure of a sensory decoder for motor control," Nature Communications, Nature, vol. 13(1), pages 1-13, December.
    10. Wendy J Adams, 2016. "The Development of Audio-Visual Integration for Temporal Judgements," PLOS Computational Biology, Public Library of Science, vol. 12(4), pages 1-17, April.
    11. Tim Genewein & Eduard Hez & Zeynab Razzaghpanah & Daniel A Braun, 2015. "Structure Learning in Bayesian Sensorimotor Integration," PLOS Computational Biology, Public Library of Science, vol. 11(8), pages 1-27, August.
    12. Xiaochen Zhang & Lingling Jin & Jie Zhao & Jiazhen Li & Ding-Bang Luh & Tiansheng Xia, 2022. "The Influences of Different Sensory Modalities and Cognitive Loads on Walking Navigation: A Preliminary Study," Sustainability, MDPI, vol. 14(24), pages 1-14, December.
    13. Johannes Burge & Priyank Jaini, 2017. "Accuracy Maximization Analysis for Sensory-Perceptual Tasks: Computational Improvements, Filter Robustness, and Coding Advantages for Scaled Additive Noise," PLOS Computational Biology, Public Library of Science, vol. 13(2), pages 1-32, February.
    14. Yingjie Lai & Chaemoon Yoo & Xiaomin Zhou & Younghwan Pan, 2023. "Elements of Food Service Design for Low-Carbon Tourism-Based on Dine-In Tourist Behavior and Attitudes in China," Sustainability, MDPI, vol. 15(9), pages 1-21, May.
    15. Florent Meyniel & Maxime Maheu & Stanislas Dehaene, 2016. "Human Inferences about Sequences: A Minimal Transition Probability Model," PLOS Computational Biology, Public Library of Science, vol. 12(12), pages 1-26, December.
    16. Brocas, Isabelle & Carrillo, Juan D., 2012. "From perception to action: An economic model of brain processes," Games and Economic Behavior, Elsevier, vol. 75(1), pages 81-103.
    17. Jean-François Patri & Pascal Perrier & Jean-Luc Schwartz & Julien Diard, 2018. "What drives the perceptual change resulting from speech motor adaptation? Evaluation of hypotheses in a Bayesian modeling framework," PLOS Computational Biology, Public Library of Science, vol. 14(1), pages 1-38, January.
    18. Florent Meyniel, 2020. "Brain dynamics for confidence-weighted learning," PLOS Computational Biology, Public Library of Science, vol. 16(6), pages 1-27, June.
    19. Anna Lambrechts & Vincent Walsh & Virginie van Wassenhove, 2013. "Evidence Accumulation in the Magnitude System," PLOS ONE, Public Library of Science, vol. 8(12), pages 1-10, December.
    20. Carrillo, Juan & Brocas, Isabelle, 2007. "Reason, Emotion and Information Processing in the Brain," CEPR Discussion Papers 6535, C.E.P.R. Discussion Papers.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pone00:0089762. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.