Prominent involvement of acetylcholine dynamics in stable olfactory representation across the Drosophila brain

Jiaqi Fan, Yuling Wang, Lingbo Li, Jing He, Zhifeng Zhao, Fei Deng, Guochuan Li, Xinyang Li, Yiliang Zhou, Jiayin Zhao, Ning Huang, Yixin Hu, Yulong Li, Jiamin Wu (), Lu Fang () and Qionghai Dai ()
Additional contact information
Jiaqi Fan: Tsinghua University
Yuling Wang: Tsinghua University
Lingbo Li: Tsinghua University
Jing He: Tsinghua University
Zhifeng Zhao: Tsinghua University
Fei Deng: Peking University
Guochuan Li: Peking University
Xinyang Li: Tsinghua University
Yiliang Zhou: Tsinghua University
Jiayin Zhao: Tsinghua University
Ning Huang: Tsinghua University
Yixin Hu: Tsinghua University
Yulong Li: Peking University
Jiamin Wu: Tsinghua University
Lu Fang: Tsinghua University
Qionghai Dai: Tsinghua University

Nature Communications, 2025, vol. 16, issue 1, 1-17

Abstract: Abstract Despite the vital role of neuromodulators and neurotransmitters in the neural system, their spatiotemporal correlation with neuronal activities across multiple brain regions remain unclear. Here, we employed two-photon synthetic aperture microscopy (2pSAM) and neurochemical indicators to simultaneously record calcium and acetylcholine (ACh)/5-HT dynamics across multiple regions of the Drosophila brain over 2 h. Presenting 3 different odors across multiple trials, our analyses revealed signal-specific differences in responsiveness, functional connectivity, and odor classification accuracy across the brain. We further constructed low-dimensional manifolds to characterize the global odor-related dynamics. Incorporating both calcium and ACh signals enhanced odor classification accuracy in the global low-dimensional manifold and in specific brain regions where their functional connectivity network features exhibited complementary patterns. Moreover, ACh dynamics demonstrated relatively stable temporal characteristics compared to calcium and 5-HT. These results suggest the potential contribution of ACh to consistent odor representations and illustrate the utility of multi-signal imaging in studying neural computation.

Date: 2025
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DOI: 10.1038/s41467-025-63823-2

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