Shiu Philip K, Sterne Gabriella R, Spiller Nico, Franconville Romain, Sandoval Andrea, Zhou Joie, Simha Neha, Kang Chan Hyuk, Yu Seongbong, Kim Jinseop S, Dorkenwald Sven, Matsliah Arie, Schlegel Philipp, Yu Szi-Chieh, McKellar Claire E, Sterling Amy, Costa Marta, Eichler Katharina, Bates Alexander Shakeel, Eckstein Nils, Funke Jan, Jefferis Gregory S X E, Murthy Mala, Bidaye Salil S, Hampel Stefanie, Seeds Andrew M, Scott Kristin
Department of Molecular and Cell Biology and Helen Wills Neuroscience Institute, University of California, Berkeley, CA, USA.
Eon Systems, San Francisco, CA, USA.
Nature. 2024 Oct;634(8032):210-219. doi: 10.1038/s41586-024-07763-9. Epub 2024 Oct 2.
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. Here we create a leaky integrate-and-fire computational model of the entire Drosophila brain, on the basis of neural connectivity and neurotransmitter identity, 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. In addition, using the model to activate 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 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. 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.
最近构建的成年黑腹果蝇中枢脑连接体包含超过12.5万个神经元和5000万个突触连接，为研究全脑的感觉处理提供了一个模板。在此，我们基于神经连接性和神经递质特性，创建了一个完整果蝇脑的泄漏整合-激发计算模型，以研究摄食和梳理行为的回路特性。我们表明，计算模型中糖感知或水感知味觉神经元的激活准确预测了对味道有反应且是启动摄食所必需的神经元。此外，利用该模型激活果蝇脑摄食区域的神经元可预测那些引发运动神经元放电的神经元——这是一个可通过光遗传学激活和行为研究验证的可测试假设。在模型中激活不同类别的味觉神经元能准确预测几种味觉模式如何相互作用，从而在回路层面深入了解厌恶和喜好味觉处理。此外，我们将此模型应用于机械感觉回路，发现机械感觉神经元的计算激活预测了包含触角梳理回路的一小部分神经元的激活，并准确描述了激活不同机械感觉亚型时的回路反应。我们的结果表明，仅使用突触层面的连接性和预测的神经递质特性对脑回路进行建模可生成可通过实验验证的假设，并能描述完整的感觉运动转换。
