Just because the Drosophila brain has fewer neurons than mice and humans doesn’t mean it’s any less intricate. In fact, recent studies have revealed the mind-boggling complexity of fruit fly neural circuits. To tackle the challenge of modeling these circuits, scientists have developed a programmable ontology that goes beyond just mapping the anatomy of the fly brain. It also encompasses the functional logic of these circuits, providing a language to not only model circuit motifs but also explore their functional logic programmatically. By integrating this programmable ontology with a computing platform called FlyBrainLab, researchers can now delve into the intricacies of the fruit fly brain like never before. The ontological framework also includes NeuroNLP++, a nifty web application that allows users to construct functional brain circuits using plain English queries and data from connectome datasets and scientific literature. This expanded ontology also incorporates a model of odorants and olfactory sensory circuits in the fruit fly brain, as well as the fascinating feedback loops observed throughout different brain regions. By utilizing a comprehensive circuit library, scientists can interactively explore the multitude of feedback loops in the antennal lobe and uncover the hidden secrets of the Drosophila brain!

The Drosophila 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 Drosophila 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 Drosophila 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.

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