Path knockout: an analysis tool for connectome-driven circuit discovery

Neural circuits in the brain transform sensory information into perceptual, emotional and motor output. The connectome — a synaptic-resolution wiring diagram of all neurons in a nervous system — provides a neuroanatomical blueprint for identifying different circuits that mediate specific computations. However, its sheer scale and complexity pose a significant challenge in extracting functionally relevant multi-synaptic pathways. Here we established path knockout, a connectome analysis method that identifies dominant multi-synaptic pathways. Path knockout uses the input fraction of each synaptic connection as a surrogate for the probability that information transfer succeeds across that synapse and calculates approximate probability, or connection strength, that at least one path succeeds among all multi-synaptic paths between defined source and sink neuron populations. It then quantifies the importance of each interneuron by assessing the impact of its removal on the connection strength. We demonstrate that path knockout outperforms other methods for pathway analysis and identifies known and novel interneurons in the Drosophila circuits. Using path knockout, we identified a convergent circuit motif linking sexually dimorphic aggression command neurons to a shared isomorphic visual pursuit pathway. Path knockout is implemented such that it runs in minutes on a standard computer. Thus, path knockout provides a scalable and generalizable framework for connectome-driven circuit discovery.

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Publication Details

Journal
bioRxiv (Cold Spring Harbor Laboratory)
Published
2026-11-03
DOI
https://doi.org/10.64898/2026.10.31.763128
Primary Topic
Neurobiology and Insect Physiology Research
Type
preprint
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preprint

Path knockout: an analysis tool for connectome-driven circuit discovery

Daisuke Hattori, Ryan McGrath
bioRxiv (Cold Spring Harbor Laboratory)
Neurobiology and Insect Physiology Research
preprint

Path knockout: an analysis tool for connectome-driven circuit discovery

Daisuke Hattori, Ryan McGrath
preprint en

Abstract

Neural circuits in the brain transform sensory information into perceptual, emotional and motor output. The connectome — a synaptic-resolution wiring diagram of all neurons in a nervous system — provides a neuroanatomical blueprint for identifying different circuits that mediate specific computations. However, its sheer scale and complexity pose a significant challenge in extracting functionally relevant multi-synaptic pathways. Here we established path knockout, a connectome analysis method that identifies dominant multi-synaptic pathways. Path knockout uses the input fraction of each synaptic connection as a surrogate for the probability that information transfer succeeds across that synapse and calculates approximate probability, or connection strength, that at least one path succeeds among all multi-synaptic paths between defined source and sink neuron populations. It then quantifies the importance of each interneuron by assessing the impact of its removal on the connection strength. We demonstrate that path knockout outperforms other methods for pathway analysis and identifies known and novel interneurons in the Drosophila circuits. Using path knockout, we identified a convergent circuit motif linking sexually dimorphic aggression command neurons to a shared isomorphic visual pursuit pathway. Path knockout is implemented such that it runs in minutes on a standard computer. Thus, path knockout provides a scalable and generalizable framework for connectome-driven circuit discovery.

bioRxiv (Cold Spring Harbor Laboratory)
The University of Texas Southwestern Medical Center (US)
Neurobiology and Insect Physiology Research
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Path knockout: an analysis tool for connectome-driven circuit discovery — Daisuke Hattori, Ryan McGrath · bioRxiv (Cold Spring Harbor Laboratory) (2026) | TGRS Research Map | TGRS