Uncovering Relations in High-Dimensional Behavioral Data of Drosophila Melanogaster
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Date
2025
Journal Title
Journal ISSN
Volume Title
Publisher
The Eurographics Association
Abstract
Understanding how behaviour changes under genetic or experimental conditions is a key challenge in behavioural neuroscience. High-throughput tracking enables the collection of high-dimensional datasets describing locomotion, posture, and stimulus orientation in Drosophila melanogaster larvae (fruit fly). However, exploring relations across numerous dimensions remains challenging. We present a Visual Analytics system that integrates coordinated views, type-aware relation metrics, and hierarchical clustering to support relation discovery and validation in behavioural data. The system was initially developed based on prior experience and refined through evaluation with domain experts to address key analysis tasks, including grouping dimensions, exploring behavioural patterns, and validating hypotheses. We demonstrate how it supports both confirmatory and exploratory workflows, enabling users to confirm known effects and uncover novel patterns-such as an unexpected correlation between head-casting behaviour and locomotion speed. This work highlights how tailored visual analysis can advance behavioural research.
Description
@inproceedings{10.2312:vmv.20251234,
booktitle = {Vision, Modeling, and Visualization},
editor = {Egger, Bernhard and Günther, Tobias},
title = {{Uncovering Relations in High-Dimensional Behavioral Data of Drosophila Melanogaster}},
author = {Thane, Michael and Blum, Kai Michael and Lehmann, Dirk J.},
year = {2025},
publisher = {The Eurographics Association},
ISBN = {978-3-03868-294-3},
DOI = {10.2312/vmv.20251234}
}