IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v15y2024i1d10.1038_s41467-024-45971-z.html
   My bibliography  Save this article

Heterogeneity of synaptic connectivity in the fly visual system

Author

Listed:
  • Jacqueline Cornean

    (Johannes-Gutenberg University)

  • Sebastian Molina-Obando

    (Johannes-Gutenberg University)

  • Burak Gür

    (Johannes-Gutenberg University)

  • Annika Bast

    (Johannes-Gutenberg University)

  • Giordano Ramos-Traslosheros

    (Johannes-Gutenberg University
    Harvard Medical School)

  • Jonas Chojetzki

    (Johannes-Gutenberg University)

  • Lena Lörsch

    (Johannes-Gutenberg University)

  • Maria Ioannidou

    (Johannes-Gutenberg University)

  • Rachita Taneja

    (Johannes-Gutenberg University)

  • Christopher Schnaitmann

    (Johannes-Gutenberg University)

  • Marion Silies

    (Johannes-Gutenberg University)

Abstract

Visual systems are homogeneous structures, where repeating columnar units retinotopically cover the visual field. Each of these columns contain many of the same neuron types that are distinguished by anatomic, genetic and – generally – by functional properties. However, there are exceptions to this rule. In the 800 columns of the Drosophila eye, there is an anatomically and genetically identifiable cell type with variable functional properties, Tm9. Since anatomical connectivity shapes functional neuronal properties, we identified the presynaptic inputs of several hundred Tm9s across both optic lobes using the full adult female fly brain (FAFB) electron microscopic dataset and FlyWire connectome. Our work shows that Tm9 has three major and many sparsely distributed inputs. This differs from the presynaptic connectivity of other Tm neurons, which have only one major, and more stereotypic inputs than Tm9. Genetic synapse labeling showed that the heterogeneous wiring exists across individuals. Together, our data argue that the visual system uses heterogeneous, distributed circuit properties to achieve robust visual processing.

Suggested Citation

  • Jacqueline Cornean & Sebastian Molina-Obando & Burak Gür & Annika Bast & Giordano Ramos-Traslosheros & Jonas Chojetzki & Lena Lörsch & Maria Ioannidou & Rachita Taneja & Christopher Schnaitmann & Mari, 2024. "Heterogeneity of synaptic connectivity in the fly visual system," Nature Communications, Nature, vol. 15(1), pages 1-15, December.
  • Handle: RePEc:nat:natcom:v:15:y:2024:i:1:d:10.1038_s41467-024-45971-z
    DOI: 10.1038/s41467-024-45971-z
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41467-024-45971-z
    File Function: Abstract
    Download Restriction: no

    File URL: https://libkey.io/10.1038/s41467-024-45971-z?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. Shin-ya Takemura & Arjun Bharioke & Zhiyuan Lu & Aljoscha Nern & Shiv Vitaladevuni & Patricia K. Rivlin & William T. Katz & Donald J. Olbris & Stephen M. Plaza & Philip Winston & Ting Zhao & Jane Anne, 2013. "A visual motion detection circuit suggested by Drosophila connectomics," Nature, Nature, vol. 500(7461), pages 175-181, August.
    2. Katrin Franke & Philipp Berens & Timm Schubert & Matthias Bethge & Thomas Euler & Tom Baden, 2017. "Inhibition decorrelates visual feature representations in the inner retina," Nature, Nature, vol. 542(7642), pages 439-444, February.
    3. Tom Baden & Philipp Berens & Katrin Franke & Miroslav Román Rosón & Matthias Bethge & Thomas Euler, 2016. "The functional diversity of retinal ganglion cells in the mouse," Nature, Nature, vol. 529(7586), pages 345-350, January.
    4. Ferdi Ridvan Kiral & Gerit Arne Linneweber & Thomas Mathejczyk & Svilen Veselinov Georgiev & Mathias F. Wernet & Bassem A. Hassan & Max Kleist & Peter Robin Hiesinger, 2020. "Autophagy-dependent filopodial kinetics restrict synaptic partner choice during Drosophila brain wiring," Nature Communications, Nature, vol. 11(1), pages 1-14, December.
    5. Giordano Ramos-Traslosheros & Marion Silies, 2021. "The physiological basis for contrast opponency in motion computation in Drosophila," Nature Communications, Nature, vol. 12(1), pages 1-16, December.
    6. Rudy Behnia & Damon A. Clark & Adam G. Carter & Thomas R. Clandinin & Claude Desplan, 2014. "Processing properties of ON and OFF pathways for Drosophila motion detection," Nature, Nature, vol. 512(7515), pages 427-430, August.
    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. 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.
    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. Kit D. Longden & Edward M. Rogers & Aljoscha Nern & Heather Dionne & Michael B. Reiser, 2023. "Different spectral sensitivities of ON- and OFF-motion pathways enhance the detection of approaching color objects in Drosophila," Nature Communications, Nature, vol. 14(1), pages 1-22, December.
    4. Héctor Acarón Ledesma & Jennifer Ding & Swen Oosterboer & Xiaolin Huang & Qiang Chen & Sui Wang & Michael Z. Lin & Wei Wei, 2024. "Dendritic mGluR2 and perisomatic Kv3 signaling regulate dendritic computation of mouse starburst amacrine cells," Nature Communications, Nature, vol. 15(1), pages 1-15, December.
    5. Daniel Soudry & Suraj Keshri & Patrick Stinson & Min-hwan Oh & Garud Iyengar & Liam Paninski, 2015. "Efficient "Shotgun" Inference of Neural Connectivity from Highly Sub-sampled Activity Data," PLOS Computational Biology, Public Library of Science, vol. 11(10), pages 1-30, October.
    6. Antoine Allard & M Ángeles Serrano, 2020. "Navigable maps of structural brain networks across species," PLOS Computational Biology, Public Library of Science, vol. 16(2), pages 1-20, February.
    7. Jason S Prentice & Olivier Marre & Mark L Ioffe & Adrianna R Loback & Gašper Tkačik & Michael J Berry II, 2016. "Error-Robust Modes of the Retinal Population Code," PLOS Computational Biology, Public Library of Science, vol. 12(11), pages 1-32, November.
    8. Jérémie Sibille & Carolin Gehr & Jonathan I. Benichov & Hymavathy Balasubramanian & Kai Lun Teh & Tatiana Lupashina & Daniela Vallentin & Jens Kremkow, 2022. "High-density electrode recordings reveal strong and specific connections between retinal ganglion cells and midbrain neurons," Nature Communications, Nature, vol. 13(1), pages 1-18, December.
    9. Andrew Jo & Sercan Deniz & Jian Xu & Robert M. Duvoisin & Steven H. DeVries & Yongling Zhu, 2023. "A sign-inverted receptive field of inhibitory interneurons provides a pathway for ON-OFF interactions in the retina," Nature Communications, Nature, vol. 14(1), pages 1-16, December.
    10. Yeon Jin Kim & Beth B. Peterson & Joanna D. Crook & Hannah R. Joo & Jiajia Wu & Christian Puller & Farrel R. Robinson & Paul D. Gamlin & King-Wai Yau & Felix Viana & John B. Troy & Robert G. Smith & O, 2022. "Origins of direction selectivity in the primate retina," Nature Communications, Nature, vol. 13(1), pages 1-20, December.
    11. Matías A. Goldin & Baptiste Lefebvre & Samuele Virgili & Mathieu Kim Pham Van Cang & Alexander Ecker & Thierry Mora & Ulisse Ferrari & Olivier Marre, 2022. "Context-dependent selectivity to natural images in the retina," Nature Communications, Nature, vol. 13(1), pages 1-12, December.
    12. Dmitry Molotkov & Leiron Ferrarese & Tom Boissonnet & Hiroki Asari, 2023. "Topographic axonal projection at single-cell precision supports local retinotopy in the mouse superior colliculus," Nature Communications, Nature, vol. 14(1), pages 1-10, December.
    13. Oleksandr Sorochynskyi & Stéphane Deny & Olivier Marre & Ulisse Ferrari, 2021. "Predicting synchronous firing of large neural populations from sequential recordings," PLOS Computational Biology, Public Library of Science, vol. 17(1), pages 1-21, January.
    14. Saha, Papri & Sarkar, Debasish, 2022. "Allometric scaling of von Neumann entropy in animal connectomes and its evolutionary aspect," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 600(C).
    15. John A. Gaynes & Samuel A. Budoff & Michael J. Grybko & Joshua B. Hunt & Alon Poleg-Polsky, 2022. "Classical center-surround receptive fields facilitate novel object detection in retinal bipolar cells," Nature Communications, Nature, vol. 13(1), pages 1-17, December.
    16. Toufiq Parag & Anirban Chakraborty & Stephen Plaza & Louis Scheffer, 2015. "A Context-Aware Delayed Agglomeration Framework for Electron Microscopy Segmentation," PLOS ONE, Public Library of Science, vol. 10(5), pages 1-19, May.
    17. Jen-Chun Hsiang & Ning Shen & Florentina Soto & Daniel Kerschensteiner, 2024. "Distributed feature representations of natural stimuli across parallel retinal pathways," Nature Communications, Nature, vol. 15(1), pages 1-20, December.
    18. Shang, Ke-ke & Small, Michael & Yan, Wei-sheng, 2017. "Link direction for link prediction," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 469(C), pages 767-776.
    19. Lei Wang & Xin Liu & Yin Zhang, 2023. "A communication-efficient and privacy-aware distributed algorithm for sparse PCA," Computational Optimization and Applications, Springer, vol. 85(3), pages 1033-1072, July.
    20. Andrew Jo & Sercan Deniz & Suraj Cherian & Jian Xu & Daiki Futagi & Steven H. DeVries & Yongling Zhu, 2023. "Modular interneuron circuits control motion sensitivity in the mouse retina," Nature Communications, Nature, vol. 14(1), pages 1-17, 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_s41467-024-45971-z. 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.