The connectome of an insect brain

Michael Winding; Benjamin D. Pedigo; Christopher L. Barnes; Heather G. Patsolic; Youngser Park; Tom Kazimiers; Akira Fushiki; Ingrid V. Andrade; Avinash Khandelwal; Javier Valdes-Aleman; Feng Li; Nadine Randel; Elizabeth Barsotti; Ana Correia; Richard D. Fetter; Volker Hartenstein; Carey E. Priebe; Joshua T. Vogelstein; Albert Cardona; Marta Zlatic

doi:10.1126/science.add9330

The connectome of an insect brain

Michael Winding^*, Benjamin D. Pedigo, Christopher L. Barnes, Heather G. Patsolic, Youngser Park, Tom Kazimiers, Akira Fushiki, Ingrid V. Andrade, Avinash Khandelwal, Javier Valdes-Aleman, Feng Li, Nadine Randel, Elizabeth Barsotti, Ana Correia, Richard D. Fetter, Volker Hartenstein, Carey E. Priebe, Joshua T. Vogelstein^*, Albert Cardona, Marta Zlatic^*

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

Abstract

Brains contain networks of interconnected neurons and so knowing the network architecture is essential for understanding brain function. We therefore mapped the synaptic-resolution connectome of an entire insect brain (Drosophila larva) with rich behavior, including learning, value computation, and action selection, comprising 3016 neurons and 548,000 synapses. We characterized neuron types, hubs, feedforward and feedback pathways, as well as cross-hemisphere and brain-nerve cord interactions. We found pervasive multisensory and interhemispheric integration, highly recurrent architecture, abundant feedback from descending neurons, and multiple novel circuit motifs. The brain’s most recurrent circuits comprised the input and output neurons of the learning center. Some structural features, including multilayer shortcuts and nested recurrent loops, resembled state-of-the-art deep learning architectures. The identified brain architecture provides a basis for future experimental and theoretical studies of neural circuits.

Original language	English
Article number	eadd9330
Journal	Science
Volume	379
Issue number	6636
DOIs	https://doi.org/10.1126/science.add9330
State	Published - 10 Mar 2023
Externally published	Yes

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Winding, M., Pedigo, B. D., Barnes, C. L., Patsolic, H. G., Park, Y., Kazimiers, T., Fushiki, A., Andrade, I. V., Khandelwal, A., Valdes-Aleman, J., Li, F., Randel, N., Barsotti, E., Correia, A., Fetter, R. D., Hartenstein, V., Priebe, C. E., Vogelstein, J. T., Cardona, A., & Zlatic, M. (2023). The connectome of an insect brain. Science, 379(6636), Article eadd9330. https://doi.org/10.1126/science.add9330

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title = "The connectome of an insect brain",

abstract = "Brains contain networks of interconnected neurons and so knowing the network architecture is essential for understanding brain function. We therefore mapped the synaptic-resolution connectome of an entire insect brain (Drosophila larva) with rich behavior, including learning, value computation, and action selection, comprising 3016 neurons and 548,000 synapses. We characterized neuron types, hubs, feedforward and feedback pathways, as well as cross-hemisphere and brain-nerve cord interactions. We found pervasive multisensory and interhemispheric integration, highly recurrent architecture, abundant feedback from descending neurons, and multiple novel circuit motifs. The brain{\textquoteright}s most recurrent circuits comprised the input and output neurons of the learning center. Some structural features, including multilayer shortcuts and nested recurrent loops, resembled state-of-the-art deep learning architectures. The identified brain architecture provides a basis for future experimental and theoretical studies of neural circuits.",

author = "Michael Winding and Pedigo, {Benjamin D.} and Barnes, {Christopher L.} and Patsolic, {Heather G.} and Youngser Park and Tom Kazimiers and Akira Fushiki and Andrade, {Ingrid V.} and Avinash Khandelwal and Javier Valdes-Aleman and Feng Li and Nadine Randel and Elizabeth Barsotti and Ana Correia and Fetter, {Richard D.} and Volker Hartenstein and Priebe, {Carey E.} and Vogelstein, {Joshua T.} and Albert Cardona and Marta Zlatic",

note = "Publisher Copyright: Copyright {\textcopyright} 2023 The Authors, some rights reserved.",

year = "2023",

month = mar,

day = "10",

doi = "10.1126/science.add9330",

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Winding, M, Pedigo, BD, Barnes, CL, Patsolic, HG, Park, Y, Kazimiers, T, Fushiki, A, Andrade, IV, Khandelwal, A, Valdes-Aleman, J, Li, F, Randel, N, Barsotti, E, Correia, A, Fetter, RD, Hartenstein, V, Priebe, CE, Vogelstein, JT, Cardona, A & Zlatic, M 2023, 'The connectome of an insect brain', Science, vol. 379, no. 6636, eadd9330. https://doi.org/10.1126/science.add9330

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AU - Barnes, Christopher L.

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AU - Fushiki, Akira

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AU - Khandelwal, Avinash

AU - Valdes-Aleman, Javier

AU - Li, Feng

AU - Randel, Nadine

AU - Barsotti, Elizabeth

AU - Correia, Ana

AU - Fetter, Richard D.

AU - Hartenstein, Volker

AU - Priebe, Carey E.

AU - Vogelstein, Joshua T.

AU - Cardona, Albert

AU - Zlatic, Marta

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AB - Brains contain networks of interconnected neurons and so knowing the network architecture is essential for understanding brain function. We therefore mapped the synaptic-resolution connectome of an entire insect brain (Drosophila larva) with rich behavior, including learning, value computation, and action selection, comprising 3016 neurons and 548,000 synapses. We characterized neuron types, hubs, feedforward and feedback pathways, as well as cross-hemisphere and brain-nerve cord interactions. We found pervasive multisensory and interhemispheric integration, highly recurrent architecture, abundant feedback from descending neurons, and multiple novel circuit motifs. The brain’s most recurrent circuits comprised the input and output neurons of the learning center. Some structural features, including multilayer shortcuts and nested recurrent loops, resembled state-of-the-art deep learning architectures. The identified brain architecture provides a basis for future experimental and theoretical studies of neural circuits.

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The connectome of an insect brain

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