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Coupling of activity, metabolism and behaviour across the Drosophila brain

Author

Listed:
  • Kevin Mann

    (Stanford University)

  • Stephane Deny

    (Stanford University)

  • Surya Ganguli

    (Stanford University
    Stanford University)

  • Thomas R. Clandinin

    (Stanford University)

Abstract

Coordinated activity across networks of neurons is a hallmark of both resting and active behavioural states in many species1–5. These global patterns alter energy metabolism over seconds to hours, which underpins the widespread use of oxygen consumption and glucose uptake as proxies of neural activity6,7. However, whether changes in neural activity are causally related to metabolic flux in intact circuits on the timescales associated with behaviour is unclear. Here we combine two-photon microscopy of the fly brain with sensors that enable the simultaneous measurement of neural activity and metabolic flux, across both resting and active behavioural states. We demonstrate that neural activity drives changes in metabolic flux, creating a tight coupling between these signals that can be measured across brain networks. Using local optogenetic perturbation, we demonstrate that even transient increases in neural activity result in rapid and persistent increases in cytosolic ATP, which suggests that neuronal metabolism predictively allocates resources to anticipate the energy demands of future activity. Finally, our studies reveal that the initiation of even minimal behavioural movements causes large-scale changes in the pattern of neural activity and energy metabolism, which reveals a widespread engagement of the brain. As the relationship between neural activity and energy metabolism is probably evolutionarily ancient and highly conserved, our studies provide a critical foundation for using metabolic proxies to capture changes in neural activity.

Suggested Citation

  • Kevin Mann & Stephane Deny & Surya Ganguli & Thomas R. Clandinin, 2021. "Coupling of activity, metabolism and behaviour across the Drosophila brain," Nature, Nature, vol. 593(7858), pages 244-248, May.
  • Handle: RePEc:nat:nature:v:593:y:2021:i:7858:d:10.1038_s41586-021-03497-0
    DOI: 10.1038/s41586-021-03497-0
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    Cited by:

    1. Manish Saggar & James M. Shine & Raphaël Liégeois & Nico U. F. Dosenbach & Damien Fair, 2022. "Precision dynamical mapping using topological data analysis reveals a hub-like transition state at rest," Nature Communications, Nature, vol. 13(1), pages 1-19, December.
    2. Shivesh Chaudhary & Sihoon Moon & Hang Lu, 2022. "Fast, efficient, and accurate neuro-imaging denoising via supervised deep learning," Nature Communications, Nature, vol. 13(1), pages 1-16, December.
    3. Hadi Vafaii & Francesca Mandino & Gabriel Desrosiers-Grégoire & David O’Connor & Marija Markicevic & Xilin Shen & Xinxin Ge & Peter Herman & Fahmeed Hyder & Xenophon Papademetris & Mallar Chakravarty , 2024. "Multimodal measures of spontaneous brain activity reveal both common and divergent patterns of cortical functional organization," Nature Communications, Nature, vol. 15(1), pages 1-19, December.
    4. Ayelet M. Rosenberg & Manish Saggar & Anna S. Monzel & Jack Devine & Peter Rogu & Aaron Limoges & Alex Junker & Carmen Sandi & Eugene V. Mosharov & Dani Dumitriu & Christoph Anacker & Martin Picard, 2023. "Brain mitochondrial diversity and network organization predict anxiety-like behavior in male mice," Nature Communications, Nature, vol. 14(1), pages 1-19, December.
    5. Shannon Trombley & Jackson Powell & Pavithran Guttipatti & Andrew Matamoros & Xiaohui Lin & Tristan O’Harrow & Tobias Steinschaden & Leann Miles & Qin Wang & Shuchao Wang & Jingyun Qiu & Qingyang Li &, 2023. "Glia instruct axon regeneration via a ternary modulation of neuronal calcium channels in Drosophila," Nature Communications, Nature, vol. 14(1), pages 1-18, December.

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