A leaky integrate-and-fire computational model based on the connectome of the entire adult Drosophila brain reveals insights into sensorimotor processing.

Autor: Shiu PK; Department of Molecular and Cell Biology and Helen Wills Neuroscience Institute, University of California, Berkeley, CA, USA., Sterne GR; Department of Molecular and Cell Biology and Helen Wills Neuroscience Institute, University of California, Berkeley, CA, USA.; University of Rochester Medical Center, Department of Biomedical Genetics., Spiller N; Max Planck Florida Institute for Neuroscience, Jupiter, FL, USA., Franconville R; HHMI Janelia Research Campus, Ashburn, USA., Sandoval A; Department of Molecular and Cell Biology and Helen Wills Neuroscience Institute, University of California, Berkeley, CA, USA., Zhou J; Department of Molecular and Cell Biology and Helen Wills Neuroscience Institute, University of California, Berkeley, CA, USA., Simha N; Department of Molecular and Cell Biology and Helen Wills Neuroscience Institute, University of California, Berkeley, CA, USA., Kang CH; Department of Biological Sciences, Sungkyunkwan University, Suwon, 16419, South Korea., Yu S; Department of Biological Sciences, Sungkyunkwan University, Suwon, 16419, South Korea., Kim JS; Department of Biological Sciences, Sungkyunkwan University, Suwon, 16419, South Korea., Dorkenwald S; Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA.; Computer Science Department, Princeton University, Princeton, NJ, USA., Matsliah A; Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA., Schlegel P; Department of Zoology, University of Cambridge.; Neurobiology Division, MRC Laboratory of Molecular Biology, Cambridge., Szi-Chieh Y; Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA., McKellar CE; Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA., Sterling A; Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA., Costa M; Department of Zoology, University of Cambridge., Eichler K; Department of Zoology, University of Cambridge., Jefferis GSXE; Department of Zoology, University of Cambridge.; Neurobiology Division, MRC Laboratory of Molecular Biology, Cambridge., Murthy M; Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA., Bates AS; Neurobiology Division, MRC Laboratory of Molecular Biology, Cambridge.; Centre for Neural Circuits and Behaviour, The University of Oxford.; Department of Neurobiology and Howard Hughes Medical Institute, Harvard Medical School, Boston, MA, USA., Eckstein N; HHMI Janelia Research Campus, Ashburn, USA., Funke J; HHMI Janelia Research Campus, Ashburn, USA., Bidaye SS; Max Planck Florida Institute for Neuroscience, Jupiter, FL, USA., Hampel S; Institute of Neurobiology, University of Puerto Rico-Medical Sciences Campus, San Juan, Puerto Rico., Seeds AM; Institute of Neurobiology, University of Puerto Rico-Medical Sciences Campus, San Juan, Puerto Rico., Scott K; Department of Molecular and Cell Biology and Helen Wills Neuroscience Institute, University of California, Berkeley, CA, USA.
Jazyk: angličtina
Zdroj: BioRxiv : the preprint server for biology [bioRxiv] 2023 May 02. Date of Electronic Publication: 2023 May 02.
DOI: 10.1101/2023.05.02.539144
Abstrakt: The forthcoming assembly of the adult Drosophila melanogaster central brain connectome, containing over 125,000 neurons and 50 million synaptic connections, provides a template for examining sensory processing throughout the brain. Here, we create a leaky integrate-and-fire computational model of the entire Drosophila brain, based on neural connectivity and neurotransmitter identity, to study circuit properties of feeding and grooming behaviors. 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. Computational activation of neurons in the feeding region of the Drosophila brain predicts those that elicit motor neuron firing, a testable hypothesis that we validate by optogenetic activation and behavioral studies. Moreover, computational activation of different classes of gustatory neurons makes accurate predictions of how multiple taste modalities interact, providing circuit-level insight into aversive and appetitive taste processing. Our computational model predicts that the sugar and water pathways form a partially shared appetitive feeding initiation pathway, which our calcium imaging and behavioral experiments confirm. 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 that do not overlap with gustatory circuits, and accurately describes the circuit response upon activation of different mechanosensory subtypes. Our results demonstrate that modeling brain circuits purely from connectivity and predicted neurotransmitter identity generates experimentally testable hypotheses and can accurately describe complete sensorimotor transformations.
Databáze: MEDLINE