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TitleRecurrent architecture for adaptive regulation of learning in the insect brain.
Publication TypeJournal Article
Year of Publication2020
AuthorsEschbach, Claire, Akira Fushiki, Michael Winding, Casey M. Schneider-Mizell, Mei Shao, Rebecca Arruda, Katharina Eichler, Javier Valdes-Aleman, Tomoko Ohyama, Andreas S. Thum, Bertram Gerber, Richard D. Fetter, James W. Truman, Ashok Litwin-Kumar, Albert Cardona, and Marta Zlatic
JournalNat Neurosci
Volume23
Issue4
Pagination544-555
Date Published2020 04
ISSN1546-1726
KeywordsAnimals, Dopaminergic Neurons, Drosophila, Larva, Learning, Memory, Models, Neurological, Mushroom Bodies, Neural Pathways
Abstract

Dopaminergic neurons (DANs) drive learning across the animal kingdom, but the upstream circuits that regulate their activity and thereby learning remain poorly understood. We provide a synaptic-resolution connectome of the circuitry upstream of all DANs in a learning center, the mushroom body of Drosophila larva. We discover afferent sensory pathways and a large population of neurons that provide feedback from mushroom body output neurons and link distinct memory systems (aversive and appetitive). We combine this with functional studies of DANs and their presynaptic partners and with comprehensive circuit modeling. We find that DANs compare convergent feedback from aversive and appetitive systems, which enables the computation of integrated predictions that may improve future learning. Computational modeling reveals that the discovered feedback motifs increase model flexibility and performance on learning tasks. Our study provides the most detailed view to date of biological circuit motifs that support associative learning.

DOI10.1038/s41593-020-0607-9
Alternate JournalNat Neurosci
PubMed ID32203499
PubMed Central IDPMC7145459
Grant List819650 / ERC_ / European Research Council / International
205050 / WT_ / Wellcome Trust / United Kingdom
/ HHMI / Howard Hughes Medical Institute / United States
RG86459 / WT_ / Wellcome Trust / United Kingdom
205038/A/16/Z / WT_ / Wellcome Trust / United Kingdom
/ WT_ / Wellcome Trust / United Kingdom
205038/Z/16/Z / WT_ / Wellcome Trust / United Kingdom