A Drosophila computational brain model reveals sensorimotor processing

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 brain<sup>1,2</sup>. Here we create a leaky integrate-and-fire computational model of the entire Drosophila brain, on the basis of neural connectivity and neurotransmitter identity<sup>3</sup>, 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 initiation<sup>4</sup>. In addition, using the model to activate neurons in the feeding region of the Drosophila brain predicts those that elicit motor neuron firing<sup>5</sup>-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 subtypes<sup>6-10</sup>. 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.

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Publication Details

Journal
Nature
Published
2024-10-02
DOI
https://doi.org/10.1038/s41586-024-07763-9
Citations
67
Primary Topic
Neurobiology and Insect Physiology Research
Type
article
Field-Weighted Citation Impact
17.97

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article

A Drosophila computational brain model reveals sensorimotor processing

Kristin Scott, Claire McKellar, Seongbong Yu, Nils Eckstein et al.
67 citations
Nature
Neurobiology and Insect Physiology Research
17.97
article

A Drosophila computational brain model reveals sensorimotor processing

Kristin Scott, Claire McKellar, Seongbong Yu, Nils Eckstein, Szi-chieh Yu, Chan Hyuk Kang, Joie Zhou, Nico Spiller, Philipp Schlegel, Sven Dorkenwald, Jinseop S. Kim, Jan Funke, Neha Simha, Gabriella R Sterne, Stefanie Hampel, Gregory S.X.E. Jefferis, Andrea Sandoval, Amy Sterling, Katharina Eichler, Arie Matsliah, Salil S. Bidaye, Alexander Shakeel Bates, Marta Costa, Philip K. Shiu, Mala Murthy, Romain Franconville, Andrew M. Seeds
article en
67 citations

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 brain<sup>1,2</sup>. Here we create a leaky integrate-and-fire computational model of the entire Drosophila brain, on the basis of neural connectivity and neurotransmitter identity<sup>3</sup>, 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 initiation<sup>4</sup>. In addition, using the model to activate neurons in the feeding region of the Drosophila brain predicts those that elicit motor neuron firing<sup>5</sup>-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 subtypes<sup>6-10</sup>. 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.

NatureVol. 634(8032)
Philips (Finland) (FI), Howard Hughes Medical Institute (US), Harvard University (US), University of Puerto Rico, Medical Sciences Campus (PR), MRC Laboratory of Molecular Biology (GB), Janelia Research Campus (US), Princeton University (US), University of Cambridge (GB), University of Rochester Medical Center (US), University of Oxford (GB), Wellcome Centre for Integrative Neuroimaging (GB), Max Planck Florida Institute for Neuroscience (US), Molecular Sciences Institute (US), Sungkyunkwan University (KR), University of California, Berkeley (US)
National Science Foundation, National Institutes of Health, National Institute of Mental Health
Clean water and sanitation
Openalex Percentile: Top 0%
Neurobiology and Insect Physiology Research
17.97
DOIOpen Access PDFOpenAlex
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