@article {70138,
	title = {The Connectome Interpreter Toolkit},
	journal = {bioRxiv},
	year = {2025},
	month = {2025 Sep 30},
	abstract = {<p>Complete synaptic wiring diagrams, or connectomes, of whole brains open new opportunities for studying the structure-function relationship of neural circuits. However, the large number of nodes and edges in the graphs makes the analysis challenging. Here, we present the Connectome Interpreter (https://github.com/YijieYin/connectome_interpreter), an open-source software toolkit for efficient graph traversal to find polysynaptic pathways, compute the effective connectivity and receptive fields for arbitrarily deep neurons, slice out subcircuits, and non-linear but differentiable circuit modeling, implemented using efficient approaches tailored to the high density and size of connectomes such as that of the fruit fly Drosophila melanogaster. Our approach delivers results orders of magnitude faster than conventional methods in consumer computer hardware. We demonstrate the capabilities of our toolkit with select applications, including quantifying the density of polysynaptic connections in the whole adult fruit fly brain, exploring the necessity for non-linearities in circuit modeling, and combining known function of neurons with the connectome to aid in formulating hypotheses of circuit function.</p>
},
	doi = {10.1101/2025.09.29.679410},
	url = {https://www.biorxiv.org/content/early/2025/09/30/2025.09.29.679410},
	author = {Yin, Yijie and Hoeller, Judith and Mathiasen, Alexander and Tsang, Joanna and Charrier, Monique Estelle and Cardona, Albert}
}
