IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v13y2022i1d10.1038_s41467-022-29180-0.html
   My bibliography  Save this article

A deep-learning approach for online cell identification and trace extraction in functional two-photon calcium imaging

Author

Listed:
  • Luca Sità

    (Optical Approaches to Brain Function Laboratory, Istituto Italiano di Tecnologia)

  • Marco Brondi

    (Optical Approaches to Brain Function Laboratory, Istituto Italiano di Tecnologia)

  • Pedro Lagomarsino de Leon Roig

    (Optical Approaches to Brain Function Laboratory, Istituto Italiano di Tecnologia
    University of Genova)

  • Sebastiano Curreli

    (Optical Approaches to Brain Function Laboratory, Istituto Italiano di Tecnologia)

  • Mariangela Panniello

    (Optical Approaches to Brain Function Laboratory, Istituto Italiano di Tecnologia)

  • Dania Vecchia

    (Optical Approaches to Brain Function Laboratory, Istituto Italiano di Tecnologia)

  • Tommaso Fellin

    (Optical Approaches to Brain Function Laboratory, Istituto Italiano di Tecnologia)

Abstract

In vivo two-photon calcium imaging is a powerful approach in neuroscience. However, processing two-photon calcium imaging data is computationally intensive and time-consuming, making online frame-by-frame analysis challenging. This is especially true for large field-of-view (FOV) imaging. Here, we present CITE-On (Cell Identification and Trace Extraction Online), a convolutional neural network-based algorithm for fast automatic cell identification, segmentation, identity tracking, and trace extraction in two-photon calcium imaging data. CITE-On processes thousands of cells online, including during mesoscopic two-photon imaging, and extracts functional measurements from most neurons in the FOV. Applied to publicly available datasets, the offline version of CITE-On achieves performance similar to that of state-of-the-art methods for offline analysis. Moreover, CITE-On generalizes across calcium indicators, brain regions, and acquisition parameters in anesthetized and awake head-fixed mice. CITE-On represents a powerful tool to speed up image analysis and facilitate closed-loop approaches, for example in combined all-optical imaging and manipulation experiments.

Suggested Citation

  • 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.
    • Handle: RePEc:nat:natcom:v:13:y:2022:i:1:d:10.1038_s41467-022-29180-0
    DOI: 10.1038/s41467-022-29180-0
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41467-022-29180-0
    File Function: Abstract
    Download Restriction: no
    File URL: https://libkey.io/10.1038/s41467-022-29180-0?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. Kenichi Ohki & Sooyoung Chung & Yeang H. Ch'ng & Prakash Kara & R. Clay Reid, 2005. "Functional imaging with cellular resolution reveals precise micro-architecture in visual cortex," Nature, Nature, vol. 433(7026), pages 597-603, February.
    2. Luke E Rogerson & Zhijian Zhao & Katrin Franke & Thomas Euler & Philipp Berens, 2019. "Bayesian hypothesis testing and experimental design for two-photon imaging data," PLOS Computational Biology, Public Library of Science, vol. 15(8), pages 1-27, August.
    3. 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.
    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. Elaine Tring & Konnie K. Duan & Dario L. Ringach, 2022. "ON/OFF domains shape receptive field structure in mouse visual cortex," Nature Communications, Nature, vol. 13(1), pages 1-11, December.
    2. Yulin Shi & Zoran Nenadic & Xiangmin Xu, 2010. "Novel Use of Matched Filtering for Synaptic Event Detection and Extraction," PLOS ONE, Public Library of Science, vol. 5(11), pages 1-15, November.
    3. David Swygart & Wan-Qing Yu & Shunsuke Takeuchi & Rachel O. L. Wong & Gregory W. Schwartz, 2024. "A presynaptic source drives differing levels of surround suppression in two mouse retinal ganglion cell types," Nature Communications, Nature, vol. 15(1), pages 1-20, December.
    4. Lars Reichl & Dominik Heide & Siegrid Löwel & Justin C Crowley & Matthias Kaschube & Fred Wolf, 2012. "Coordinated Optimization of Visual Cortical Maps (I) Symmetry-based Analysis," PLOS Computational Biology, Public Library of Science, vol. 8(11), pages 1-24, November.
    5. Jimin Wu & Yuzhi Chen & Ashok Veeraraghavan & Eyal Seidemann & Jacob T. Robinson, 2024. "Mesoscopic calcium imaging in a head-unrestrained male non-human primate using a lensless microscope," Nature Communications, Nature, vol. 15(1), pages 1-14, December.
    6. Meng Wang & Ke Liu & Junxia Pan & Jialin Li & Pei Sun & Yongsheng Zhang & Longhui Li & Wenyan Guo & Qianqian Xin & Zhikai Zhao & Yurong Liu & Zhenqiao Zhou & Jing Lyu & Ting Zheng & Yunyun Han & Chunq, 2022. "Brain-wide projection reconstruction of single functionally defined neurons," Nature Communications, Nature, vol. 13(1), pages 1-14, December.
    7. 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.
    8. Javier G. Orlandi & Mohammad Abdolrahmani & Ryo Aoki & Dmitry R. Lyamzin & Andrea Benucci, 2023. "Distributed context-dependent choice information in mouse posterior cortex," Nature Communications, Nature, vol. 14(1), pages 1-16, December.
    9. 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.
    10. 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.
    11. Yajie Liang & Rongwen Lu & Katharine Borges & Na Ji, 2023. "Stimulus edges induce orientation tuning in superior colliculus," Nature Communications, Nature, vol. 14(1), pages 1-13, December.
    12. James Trousdale & Yu Hu & Eric Shea-Brown & Krešimir Josić, 2012. "Impact of Network Structure and Cellular Response on Spike Time Correlations," PLOS Computational Biology, Public Library of Science, vol. 8(3), pages 1-15, March.
    13. Sichen Tao & Yuki Todo & Zheng Tang & Bin Li & Zhiming Zhang & Riku Inoue, 2022. "A Novel Artificial Visual System for Motion Direction Detection in Grayscale Images," Mathematics, MDPI, vol. 10(16), pages 1-32, August.
    14. 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.

    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:13:y:2022:i:1:d:10.1038_s41467-022-29180-0. 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.