Lazar Aurel A, Turkcan Mehmet Kerem, Zhou Yiyin
Department of Electrical Engineering, Columbia University, New York, NY, United States.
Front Neuroinform. 2022 Jun 20;16:853098. doi: 10.3389/fninf.2022.853098. eCollection 2022.
The brain has only a fraction of the number of neurons of higher organisms such as mice and humans. Yet the sheer complexity of its neural circuits recently revealed by large connectomics datasets suggests that computationally modeling the function of fruit fly brain circuits at this scale poses significant challenges. To address these challenges, we present here a programmable ontology that expands the scope of the current brain anatomy ontologies to encompass the functional logic of the fly brain. The programmable ontology provides a language not only for modeling circuit motifs but also for programmatically exploring their functional logic. To achieve this goal, we tightly integrated the programmable ontology with the workflow of the interactive FlyBrainLab computing platform. As part of the programmable ontology, we developed NeuroNLP++, a web application that supports free-form English queries for constructing functional brain circuits fully anchored on the available connectome/synaptome datasets, and the published worldwide literature. In addition, we present a methodology for including a model of the space of odorants into the programmable ontology, and for modeling olfactory sensory circuits of the antenna of the fruit fly brain that detect odorant sources. Furthermore, we describe a methodology for modeling the functional logic of the antennal lobe circuit consisting of a massive number of local feedback loops, a characteristic feature observed across brain regions. Finally, using a circuit library, we demonstrate the power of our methodology for interactively exploring the functional logic of the massive number of feedback loops in the antennal lobe.
果蝇大脑的神经元数量仅为小鼠和人类等高等生物的一小部分。然而，最近大型连接组学数据集揭示的其神经回路的极端复杂性表明，在这个规模上对果蝇大脑回路的功能进行计算建模面临重大挑战。为应对这些挑战，我们在此提出一种可编程本体，它扩展了当前大脑解剖学本体的范围，以涵盖果蝇大脑的功能逻辑。该可编程本体不仅提供了一种用于对回路基序进行建模的语言，还提供了一种以编程方式探索其功能逻辑的语言。为实现这一目标，我们将可编程本体与交互式FlyBrainLab计算平台的工作流程紧密集成。作为可编程本体的一部分，我们开发了NeuroNLP++，这是一个网络应用程序，支持以自由形式的英语查询来构建完全基于可用连接组/突触组数据集以及全球发表的文献的功能性大脑回路。此外，我们提出了一种方法，将气味剂空间模型纳入可编程本体，并对果蝇大脑触角中检测气味源的嗅觉感觉回路进行建模。此外，我们描述了一种方法，用于对由大量局部反馈回路组成的触角叶回路的功能逻辑进行建模，这是在整个大脑区域观察到的一个特征。最后，使用一个电路库，我们展示了我们的方法在交互式探索触角叶中大量反馈回路功能逻辑方面的强大功能。
