A Single-Cell Level and Connectome-Derived Computational Model of the Drosophila Brain
Rattachement africain : tw, us. Niveau de preuve : code pays fourni par la source.
Le résumé fourni par la source
Computer simulations play an important role in testing hypotheses, integrating knowledge, and providing predictions of neural circuit functions. While considerable effort has been dedicated into simulating primate or rodent brains, the fruit fly (Drosophila melanogaster) is becoming a promising model animal in computational neuroscience for its small brain size, complex cognitive behavior, and abundancy of data available from genes to circuits. Moreover, several Drosophila connectome projects have generated a large number of neuronal images that account for a significant portion of the brain, making a systematic investigation of the whole brain circuit possible. Supported by FlyCircuit (http://www.flycircuit.tw), one of the largest Drosophila neuron image databases, we began a long-term project with the goal to construct a whole-brain spiking network model of the Drosophila brain. In this paper, we report the outcome of the first phase of the project. We developed the Flysim platform, which 1) identifies the polarity of each neuron arbor, 2) predicts connections between neurons, 3) translates morphology data from the database into physiology parameters for computational modeling, 4) reconstructs a brain-wide network model, which consists of 20,089 neurons and 1,044,020 synapses, and 5) performs computer simulations of the resting state. We compared the reconstructed brain network with a randomized brain network by shuffling the connections of each neuron. We found that the reconstructed brain can be easily stabilized by implementing synaptic short-term depression, while the randomized one exhibited seizure-like firing activity under the same treatment. Furthermore, the reconstructed Drosophila brain was structurally and dynamically more diverse than the randomized one and exhibited both Poisson-like and patterned firing activities. Despite being at its early stage of development, this single-cell level brain model allows us to study some of the fundamental properties of neural networks including network balance, critical behavior, long-term stability, and plasticity.
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Le contrôle bibliographique ouvert
DOI retrouvé dans Crossref DOI retrouvé ; titre concordant.
- Titre Crossref
- A Single-Cell Level and Connectome-Derived Computational Model of the Drosophila Brain
- Date Crossref
- 10/01/2019
- Éditeur
- Frontiers Media SA
- Type
- journal-article
Ce recoupement confirme des métadonnées liées au DOI. Il ne confirme ni la méthode ni les conclusions de l’étude, et il ne compte pas comme une seconde source scientifique indépendante.
Où se fait cette recherche
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National Tsing Hua University Brain Research Center pays non établi dans la noticeUniversité ou école supérieure
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National Center for High-Performance Computing pays non établi dans la noticeStructure de recherche
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Kaohsiung Medical University Department of Biomedical Science and Environmental Biology pays non établi dans la noticeUniversité ou école supérieure
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National Health Research Institutes pays non établi dans la noticeOrganisation à but non lucratif
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University of California San Diego Kavli Institute for Brain and Mind pays non établi dans la noticeUniversité ou école supérieure
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Institute of Physics pays non établi dans la noticeStructure de recherche
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Hsinchu National Center for High-Performance Computing pays non établi dans la noticeÉtablissement de santé
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Institute of Molecular and Genomic Medicine pays non établi dans la noticeStructure de recherche
Brain Research Center — National Tsing Hua University, National Center for High-Performance Computing et Department of Biomedical Science and Environmental Biology — Kaohsiung Medical University, avec 5 autres affiliations.
Une affiliation ne permet pas de déduire la nationalité d’un auteur.