IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v15y2024i1d10.1038_s41467-024-47365-7.html
   My bibliography  Save this article

Perirhinal cortex learns a predictive map of the task environment

Author

Listed:
  • David G. Lee

    (Boston University
    Boston University)

  • Caroline A. McLachlan

    (Boston University
    Boston University)

  • Ramon Nogueira

    (Columbia University
    Columbia University)

  • Osung Kwon

    (Boston University
    Boston University)

  • Alanna E. Carey

    (Boston University
    Boston University)

  • Garrett House

    (Boston University)

  • Gavin D. Lagani

    (Boston University)

  • Danielle LaMay

    (Boston University)

  • Stefano Fusi

    (Columbia University
    Columbia University)

  • Jerry L. Chen

    (Boston University
    Boston University
    Boston University
    Boston University)

Abstract

Goal-directed tasks involve acquiring an internal model, known as a predictive map, of relevant stimuli and associated outcomes to guide behavior. Here, we identified neural signatures of a predictive map of task behavior in perirhinal cortex (Prh). Mice learned to perform a tactile working memory task by classifying sequential whisker stimuli over multiple training stages. Chronic two-photon calcium imaging, population analysis, and computational modeling revealed that Prh encodes stimulus features as sensory prediction errors. Prh forms stable stimulus-outcome associations that can progressively be decoded earlier in the trial as training advances and that generalize as animals learn new contingencies. Stimulus-outcome associations are linked to prospective network activity encoding possible expected outcomes. This link is mediated by cholinergic signaling to guide task performance, demonstrated by acetylcholine imaging and systemic pharmacological perturbation. We propose that Prh combines error-driven and map-like properties to acquire a predictive map of learned task behavior.

Suggested Citation

  • David G. Lee & Caroline A. McLachlan & Ramon Nogueira & Osung Kwon & Alanna E. Carey & Garrett House & Gavin D. Lagani & Danielle LaMay & Stefano Fusi & Jerry L. Chen, 2024. "Perirhinal cortex learns a predictive map of the task environment," Nature Communications, Nature, vol. 15(1), pages 1-16, December.
  • Handle: RePEc:nat:natcom:v:15:y:2024:i:1:d:10.1038_s41467-024-47365-7
    DOI: 10.1038/s41467-024-47365-7
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41467-024-47365-7
    File Function: Abstract
    Download Restriction: no

    File URL: https://libkey.io/10.1038/s41467-024-47365-7?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. Johannes Friedrich & Pengcheng Zhou & Liam Paninski, 2017. "Fast online deconvolution of calcium imaging data," PLOS Computational Biology, Public Library of Science, vol. 13(3), pages 1-26, March.
    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. Luis M. Franco & Michael J. Goard, 2024. "Differential stability of task variable representations in retrosplenial cortex," Nature Communications, Nature, vol. 15(1), pages 1-17, December.
    2. Mitchell Clough & Ichun Anderson Chen & Seong-Wook Park & Allison M. Ahrens & Jeffrey N. Stirman & Spencer L. Smith & Jerry L. Chen, 2021. "Flexible simultaneous mesoscale two-photon imaging of neural activity at high speeds," Nature Communications, Nature, vol. 12(1), pages 1-7, December.
    3. Kyerl Park & Yoonsoo Yeo & Kisung Shin & Jeehyun Kwag, 2024. "Egocentric neural representation of geometric vertex in the retrosplenial cortex," Nature Communications, Nature, vol. 15(1), pages 1-14, December.
    4. Celia M. Gagliardi & Marc E. Normandin & Alexandra T. Keinath & Joshua B. Julian & Matthew R. Lopez & Manuel-Miguel Ramos-Alvarez & Russell A. Epstein & Isabel A. Muzzio, 2024. "Distinct neural mechanisms for heading retrieval and context recognition in the hippocampus during spatial reorientation," Nature Communications, Nature, vol. 15(1), pages 1-22, December.
    5. Daniel U Campos-Delgado & Omar Gutierrez-Navarro & Ricardo Salinas-Martinez & Elvis Duran & Aldo R Mejia-Rodriguez & Miguel J Velazquez-Duran & Javier A Jo, 2021. "Blind deconvolution estimation by multi-exponential models and alternated least squares approximations: Free-form and sparse approach," PLOS ONE, Public Library of Science, vol. 16(3), pages 1-29, March.
    6. Sean Jewell & Paul Fearnhead & Daniela Witten, 2022. "Testing for a change in mean after changepoint detection," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 84(4), pages 1082-1104, September.
    7. Alexandra T. Keinath & Coralie-Anne Mosser & Mark P. Brandon, 2022. "The representation of context in mouse hippocampus is preserved despite neural drift," Nature Communications, Nature, vol. 13(1), pages 1-11, December.
    8. Philipp Berens & Jeremy Freeman & Thomas Deneux & Nikolay Chenkov & Thomas McColgan & Artur Speiser & Jakob H Macke & Srinivas C Turaga & Patrick Mineault & Peter Rupprecht & Stephan Gerhard & Rainer , 2018. "Community-based benchmarking improves spike rate inference from two-photon calcium imaging data," PLOS Computational Biology, Public Library of Science, vol. 14(5), pages 1-13, May.
    9. Daniel M. Virga & Stevie Hamilton & Bertha Osei & Abigail Morgan & Parker Kneis & Emiliano Zamponi & Natalie J. Park & Victoria L. Hewitt & David Zhang & Kevin C. Gonzalez & Fiona M. Russell & D. Grah, 2024. "Activity-dependent compartmentalization of dendritic mitochondria morphology through local regulation of fusion-fission balance in neurons in vivo," Nature Communications, Nature, vol. 15(1), pages 1-21, December.
    10. Ignacio Alonso & Irina Scheer & Mélanie Palacio-Manzano & Noémie Frézel-Jacob & Antoine Philippides & Mario Prsa, 2023. "Peripersonal encoding of forelimb proprioception in the mouse somatosensory cortex," Nature Communications, Nature, vol. 14(1), pages 1-16, December.
    11. Sasa Teng & Fenghua Zhen & Li Wang & Jose Canovas Schalchli & Jane Simko & Xinyue Chen & Hao Jin & Christopher D. Makinson & Yueqing Peng, 2022. "Control of non-REM sleep by ventrolateral medulla glutamatergic neurons projecting to the preoptic area," Nature Communications, Nature, vol. 13(1), pages 1-15, December.
    12. Yanjun Sun & Lisa M. Giocomo, 2022. "Neural circuit dynamics of drug-context associative learning in the mouse hippocampus," Nature Communications, Nature, vol. 13(1), pages 1-19, December.
    13. Sudiksha Sridhar & Eric Lowet & Howard J. Gritton & Jennifer Freire & Chengqian Zhou & Florence Liang & Xue Han, 2024. "Beta-frequency sensory stimulation enhances gait rhythmicity through strengthened coupling between striatal networks and stepping movement," Nature Communications, Nature, vol. 15(1), pages 1-17, December.
    14. Shinichiro Kira & Houman Safaai & Ari S. Morcos & Stefano Panzeri & Christopher D. Harvey, 2023. "A distributed and efficient population code of mixed selectivity neurons for flexible navigation decisions," Nature Communications, Nature, vol. 14(1), pages 1-28, December.
    15. Lloyd E. Russell & Mehmet Fişek & Zidan Yang & Lynn Pei Tan & Adam M. Packer & Henry W. P. Dalgleish & Selmaan N. Chettih & Christopher D. Harvey & Michael Häusser, 2024. "The influence of cortical activity on perception depends on behavioral state and sensory context," Nature Communications, Nature, vol. 15(1), pages 1-17, December.
    16. Johannes Friedrich & Weijian Yang & Daniel Soudry & Yu Mu & Misha B Ahrens & Rafael Yuste & Darcy S Peterka & Liam Paninski, 2017. "Multi-scale approaches for high-speed imaging and analysis of large neural populations," PLOS Computational Biology, Public Library of Science, vol. 13(8), pages 1-24, August.
    17. M. Angeles Rabadan & Estanislao Daniel De La Cruz & Sneha B. Rao & Yannan Chen & Cheng Gong & Gregg Crabtree & Bin Xu & Sander Markx & Joseph A. Gogos & Rafael Yuste & Raju Tomer, 2022. "An in vitro model of neuronal ensembles," Nature Communications, Nature, vol. 13(1), pages 1-17, December.
    18. Laura D'Angelo & Antonio Canale & Zhaoxia Yu & Michele Guindani, 2023. "Bayesian nonparametric analysis for the detection of spikes in noisy calcium imaging data," Biometrics, The International Biometric Society, vol. 79(2), pages 1370-1382, June.
    19. Kevin K. Sit & Michael J. Goard, 2023. "Coregistration of heading to visual cues in retrosplenial cortex," Nature Communications, Nature, vol. 14(1), pages 1-15, December.

    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:nat:natcom:v:15:y:2024:i:1:d:10.1038_s41467-024-47365-7. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.nature.com .

    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.