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Neural ensemble dynamics underlying a long-term associative memory

Author

Listed:
  • Benjamin F. Grewe

    (James H. Clark Center for Biomedical Engineering & Sciences, Stanford University
    Howard Hughes Medical Institute, Stanford University
    CNC Program, Stanford University)

  • Jan Gründemann

    (Friedrich Miescher Institute for Biomedical Research)

  • Lacey J. Kitch

    (James H. Clark Center for Biomedical Engineering & Sciences, Stanford University
    Howard Hughes Medical Institute, Stanford University
    CNC Program, Stanford University)

  • Jerome A. Lecoq

    (James H. Clark Center for Biomedical Engineering & Sciences, Stanford University
    Howard Hughes Medical Institute, Stanford University
    CNC Program, Stanford University)

  • Jones G. Parker

    (CNC Program, Stanford University
    Pfizer Neuroscience Research)

  • Jesse D. Marshall

    (James H. Clark Center for Biomedical Engineering & Sciences, Stanford University
    Howard Hughes Medical Institute, Stanford University
    CNC Program, Stanford University)

  • Margaret C. Larkin

    (James H. Clark Center for Biomedical Engineering & Sciences, Stanford University
    CNC Program, Stanford University)

  • Pablo E. Jercog

    (James H. Clark Center for Biomedical Engineering & Sciences, Stanford University
    Howard Hughes Medical Institute, Stanford University
    CNC Program, Stanford University)

  • Francois Grenier

    (Friedrich Miescher Institute for Biomedical Research
    † Present address: International Institute for Integrative Sleep Medicine (WPI-IIIS), University of Tsukuba, 1-1-1 Tennodai, Tsukuba 305-8575, Japan.)

  • Jin Zhong Li

    (James H. Clark Center for Biomedical Engineering & Sciences, Stanford University
    CNC Program, Stanford University)

  • Andreas Lüthi

    (Friedrich Miescher Institute for Biomedical Research
    University of Basel)

  • Mark J. Schnitzer

    (James H. Clark Center for Biomedical Engineering & Sciences, Stanford University
    Howard Hughes Medical Institute, Stanford University
    CNC Program, Stanford University)

Abstract

The brain’s ability to associate different stimuli is vital for long-term memory, but how neural ensembles encode associative memories is unknown. Here we studied how cell ensembles in the basal and lateral amygdala encode associations between conditioned and unconditioned stimuli (CS and US, respectively). Using a miniature fluorescence microscope, we tracked the Ca2+ dynamics of ensembles of amygdalar neurons during fear learning and extinction over 6 days in behaving mice. Fear conditioning induced both up- and down-regulation of individual cells’ CS-evoked responses. This bi-directional plasticity mainly occurred after conditioning, and reshaped the neural ensemble representation of the CS to become more similar to the US representation. During extinction training with repetitive CS presentations, the CS representation became more distinctive without reverting to its original form. Throughout the experiments, the strength of the ensemble-encoded CS–US association predicted the level of behavioural conditioning in each mouse. These findings support a supervised learning model in which activation of the US representation guides the transformation of the CS representation.

Suggested Citation

  • Benjamin F. Grewe & Jan Gründemann & Lacey J. Kitch & Jerome A. Lecoq & Jones G. Parker & Jesse D. Marshall & Margaret C. Larkin & Pablo E. Jercog & Francois Grenier & Jin Zhong Li & Andreas Lüthi & M, 2017. "Neural ensemble dynamics underlying a long-term associative memory," Nature, Nature, vol. 543(7647), pages 670-675, March.
  • Handle: RePEc:nat:nature:v:543:y:2017:i:7647:d:10.1038_nature21682
    DOI: 10.1038/nature21682
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    Cited by:

    1. Masakazu Agetsuma & Issei Sato & Yasuhiro R. Tanaka & Luis Carrillo-Reid & Atsushi Kasai & Atsushi Noritake & Yoshiyuki Arai & Miki Yoshitomo & Takashi Inagaki & Hiroshi Yukawa & Hitoshi Hashimoto & J, 2023. "Activity-dependent organization of prefrontal hub-networks for associative learning and signal transformation," Nature Communications, Nature, vol. 14(1), pages 1-22, December.
    2. Luca Sità & Marco Brondi & Pedro Lagomarsino de Leon Roig & Sebastiano Curreli & Mariangela Panniello & Dania Vecchia & Tommaso Fellin, 2022. "A deep-learning approach for online cell identification and trace extraction in functional two-photon calcium imaging," Nature Communications, Nature, vol. 13(1), pages 1-22, December.
    3. Anna J. Bowen & Y. Waterlily Huang & Jane Y. Chen & Jordan L. Pauli & Carlos A. Campos & Richard D. Palmiter, 2023. "Topographic representation of current and future threats in the mouse nociceptive amygdala," Nature Communications, Nature, vol. 14(1), pages 1-16, December.
    4. Masanori Nomoto & Emi Murayama & Shuntaro Ohno & Reiko Okubo-Suzuki & Shin-ichi Muramatsu & Kaoru Inokuchi, 2022. "Hippocampus as a sorter and reverberatory integrator of sensory inputs," Nature Communications, Nature, vol. 13(1), pages 1-15, December.
    5. Maria Wilhelm & Yaroslav Sych & Aleksejs Fomins & José Luis Alatorre Warren & Christopher Lewis & Laia Serratosa Capdevila & Roman Boehringer & Elizabeth A. Amadei & Benjamin Grewe & Eoin C. O’Connor , 2023. "Striatum-projecting prefrontal cortex neurons support working memory maintenance," Nature Communications, Nature, vol. 14(1), pages 1-16, December.

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