Valence and State-Dependent Population Coding in Dopaminergic Neurons in the Fly Mushroom Body.

Drosophila behavioral state calcium imaging dopamine metabolic state mushroom body olfactory system population coding taste valence

Journal

Current biology : CB
ISSN: 1879-0445
Titre abrégé: Curr Biol
Pays: England
ID NLM: 9107782

Informations de publication

Date de publication:
08 06 2020
Historique:
received: 15 10 2019
revised: 13 03 2020
accepted: 16 04 2020
pubmed: 11 5 2020
medline: 11 8 2021
entrez: 11 5 2020
Statut: ppublish

Résumé

Neuromodulation permits flexibility of synapses, neural circuits, and ultimately behavior. One neuromodulator, dopamine, has been studied extensively in its role as a reward signal during learning and memory across animal species. Newer evidence suggests that dopaminergic neurons (DANs) can modulate sensory perception acutely, thereby allowing an animal to adapt its behavior and decision making to its internal and behavioral state. In addition, some data indicate that DANs are not homogeneous but rather convey different types of information as a heterogeneous population. We have investigated DAN population activity and how it could encode relevant information about sensory stimuli and state by taking advantage of the confined anatomy of DANs innervating the mushroom body (MB) of the fly Drosophila melanogaster. Using in vivo calcium imaging and a custom 3D image registration method, we found that the activity of the population of MB DANs encodes innate valence information of an odor or taste as well as the physiological state of the animal. Furthermore, DAN population activity is strongly correlated with movement, consistent with a role of dopamine in conveying behavioral state to the MB. Altogether, our data and analysis suggest that DAN population activities encode innate odor and taste valence, movement, and physiological state in a MB-compartment-specific manner. We propose that dopamine shapes innate perception through combinatorial population coding of sensory valence, physiological, and behavioral context.

Identifiants

pubmed: 32386530
pii: S0960-9822(20)30551-0
doi: 10.1016/j.cub.2020.04.037
pii:
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

2104-2115.e4

Informations de copyright

Copyright © 2020 The Author(s). Published by Elsevier Inc. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of Interests The authors declare no competing interests.

Auteurs

K P Siju (KP)

TUM School of Life Sciences, Technical University of Munich, 85354 Freising, Germany.

Vilim Štih (V)

Sensorimotor Control Group, Max Planck Institute of Neurobiology, 82152 Martinsried, Germany.

Sophie Aimon (S)

TUM School of Life Sciences, Technical University of Munich, 85354 Freising, Germany.

Julijana Gjorgjieva (J)

TUM School of Life Sciences, Technical University of Munich, 85354 Freising, Germany; Computation in Neural Circuits Group, Max Planck Institute for Brain Research, 60438 Frankfurt am Main, Germany.

Ruben Portugues (R)

Sensorimotor Control Group, Max Planck Institute of Neurobiology, 82152 Martinsried, Germany; Institute of Neuroscience, Technical University of Munich, 80802 Munich, Germany; Munich Cluster for Systems Neurology (SyNergy), 80802 Munich, Germany.

Ilona C Grunwald Kadow (IC)

TUM School of Life Sciences, Technical University of Munich, 85354 Freising, Germany; ZIEL-Institute of Food and Health, Technical University of Munich, 85354 Freising, Germany. Electronic address: ilona.grunwald@tum.de.

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Classifications MeSH