A Drosophila computational brain model reveals sensorimotor processing

Philip K. Shiu (), Gabriella R. Sterne, Nico Spiller, Romain Franconville, Andrea Sandoval, Joie Zhou, Neha Simha, Chan Hyuk Kang, Seongbong Yu, Jinseop S. Kim, Sven Dorkenwald, Arie Matsliah, Philipp Schlegel, Szi-chieh Yu, Claire E. McKellar, Amy Sterling, Marta Costa, Katharina Eichler, Alexander Shakeel Bates, Nils Eckstein, Jan Funke, Gregory S. X. E. Jefferis, Mala Murthy, Salil S. Bidaye, Stefanie Hampel, Andrew M. Seeds and Kristin Scott
Additional contact information
Philip K. Shiu: University of California
Gabriella R. Sterne: University of California
Nico Spiller: Max Planck Florida Institute for Neuroscience
Romain Franconville: HHMI Janelia Research Campus
Andrea Sandoval: University of California
Joie Zhou: University of California
Neha Simha: University of California
Chan Hyuk Kang: Sungkyunkwan University
Seongbong Yu: Sungkyunkwan University
Jinseop S. Kim: Sungkyunkwan University
Sven Dorkenwald: Princeton University
Arie Matsliah: Princeton University
Philipp Schlegel: University of Cambridge
Szi-chieh Yu: Princeton University
Claire E. McKellar: Princeton University
Amy Sterling: Princeton University
Marta Costa: University of Cambridge
Katharina Eichler: Princeton University
Alexander Shakeel Bates: MRC Laboratory of Molecular Biology
Nils Eckstein: HHMI Janelia Research Campus
Jan Funke: HHMI Janelia Research Campus
Gregory S. X. E. Jefferis: University of Cambridge
Mala Murthy: Princeton University
Salil S. Bidaye: Max Planck Florida Institute for Neuroscience
Stefanie Hampel: University of Puerto Rico-Medical Sciences Campus
Andrew M. Seeds: University of Puerto Rico-Medical Sciences Campus
Kristin Scott: University of California

Nature, 2024, vol. 634, issue 8032, 210-219

Abstract: Abstract The recent assembly of the adult Drosophila melanogaster central brain connectome, containing more than 125,000 neurons and 50 million synaptic connections, provides a template for examining sensory processing throughout the brain1,2. Here we create a leaky integrate-and-fire computational model of the entire Drosophila brain, on the basis of neural connectivity and neurotransmitter identity3, to study circuit properties of feeding and grooming behaviours. We show that activation of sugar-sensing or water-sensing gustatory neurons in the computational model accurately predicts neurons that respond to tastes and are required for feeding initiation4. In addition, using the model to activate neurons in the feeding region of the Drosophila brain predicts those that elicit motor neuron firing5—a testable hypothesis that we validate by optogenetic activation and behavioural studies. Activating different classes of gustatory neurons in the model makes accurate predictions of how several taste modalities interact, providing circuit-level insight into aversive and appetitive taste processing. Additionally, we applied this model to mechanosensory circuits and found that computational activation of mechanosensory neurons predicts activation of a small set of neurons comprising the antennal grooming circuit, and accurately describes the circuit response upon activation of different mechanosensory subtypes6–10. Our results demonstrate that modelling brain circuits using only synapse-level connectivity and predicted neurotransmitter identity generates experimentally testable hypotheses and can describe complete sensorimotor transformations.

Date: 2024
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DOI: 10.1038/s41586-024-07763-9

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