dc.contributor.author
Garner, Dustin
dc.contributor.author
Kind, Emil
dc.contributor.author
Lai, Jennifer Yuet Ha
dc.contributor.author
Nern, Aljoscha
dc.contributor.author
Zhao, Arthur
dc.contributor.author
Houghton, Lucy
dc.contributor.author
Sancer, Gizem
dc.contributor.author
Wolff, Tanya
dc.contributor.author
Rubin, Gerald M.
dc.contributor.author
Wernet, Mathias F.
dc.contributor.author
Kim, Sung Soo
dc.date.accessioned
2024-12-05T11:39:55Z
dc.date.available
2024-12-05T11:39:55Z
dc.identifier.uri
https://refubium.fu-berlin.de/handle/fub188/45888
dc.identifier.uri
http://dx.doi.org/10.17169/refubium-45601
dc.description.abstract
Many animals use visual information to navigate1,2,3,4, but how such information is encoded and integrated by the navigation system remains incompletely understood. In Drosophila melanogaster, EPG neurons in the central complex compute the heading direction5 by integrating visual input from ER neurons6,7,8,9,10,11,12, which are part of the anterior visual pathway (AVP)10,13,14,15,16. Here we densely reconstruct all neurons in the AVP using electron-microscopy data17. The AVP comprises four neuropils, sequentially linked by three major classes of neurons: MeTu neurons10,14,15, which connect the medulla in the optic lobe to the small unit of the anterior optic tubercle (AOTUsu) in the central brain; TuBu neurons9,16, which connect the AOTUsu to the bulb neuropil; and ER neurons6,7,8,9,10,11,12, which connect the bulb to the EPG neurons. On the basis of morphologies, connectivity between neural classes and the locations of synapses, we identify distinct information channels that originate from four types of MeTu neurons, and we further divide these into ten subtypes according to the presynaptic connections in the medulla and the postsynaptic connections in the AOTUsu. Using the connectivity of the entire AVP and the dendritic fields of the MeTu neurons in the optic lobes, we infer potential visual features and the visual area from which any ER neuron receives input. We confirm some of these predictions physiologically. These results provide a strong foundation for understanding how distinct sensory features can be extracted and transformed across multiple processing stages to construct higher-order cognitive representations.
en
dc.format.extent
39 Seiten
dc.rights.uri
https://creativecommons.org/licenses/by/4.0/
dc.subject
Neural circuits
en
dc.subject
Visual system
en
dc.subject.ddc
500 Naturwissenschaften und Mathematik::570 Biowissenschaften; Biologie::570 Biowissenschaften; Biologie
dc.title
Connectomic reconstruction predicts visual features used for navigation
dc.type
Wissenschaftlicher Artikel
dcterms.bibliographicCitation.doi
10.1038/s41586-024-07967-z
dcterms.bibliographicCitation.journaltitle
Nature
dcterms.bibliographicCitation.number
8032
dcterms.bibliographicCitation.pagestart
181
dcterms.bibliographicCitation.pageend
190
dcterms.bibliographicCitation.volume
634
dcterms.bibliographicCitation.url
https://doi.org/10.1038/s41586-024-07967-z
refubium.affiliation
Biologie, Chemie, Pharmazie
refubium.affiliation.other
Institut für Biologie
refubium.resourceType.isindependentpub
no
dcterms.accessRights.openaire
open access
dcterms.isPartOf.eissn
1476-4687
refubium.resourceType.provider
WoS-Alert