Connectome-constrained networks predict neural activity across the fly visual system

Lappalainen, Janne K.; Tschopp, Fabian; Prakhya, Sridhama; McGill, Mason; Nern, Aljoscha; Shinomiya, Kazunori; Takemura, Shin-ya; Gruntman, Eyal; Macke, Jakob H.; Turaga, Srinivas C.

doi:10.1038/s41586-024-07939-3

articleNatureSep 11, 2024HYBRID OA

Connectome-constrained networks predict neural activity across the fly visual system

JKJanne K. Lappalainen FTFabian Tschopp SPSridhama Prakhya MMMason McGill ANAljoscha Nern

Howard Hughes Medical Institute · Janelia Research Campus · +6 more institutions

PubMed

Indexed incrossrefpubmed

Abstract

Abstract We can now measure the connectivity of every neuron in a neural circuit 1–9 , but we cannot measure other biological details, including the dynamical characteristics of each neuron. The degree to which measurements of connectivity alone can inform the understanding of neural computation is an open question 10 . Here we show that with experimental measurements of only the connectivity of a biological neural network, we can predict the neural activity underlying a specified neural computation. We constructed a model neural network with the experimentally determined connectivity for 64 cell types in the motion pathways of the fruit fly optic lobe 1–5 but with unknown parameters for the single-neuron and…

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Keywords

Connectome
Artificial neural network
Computer science
Artificial intelligence
Models of neural computation
Biological neural network
Neuron
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