LarVA
An interactive visual analytics system for exploring and annotating behavioural embeddings of Drosophila larvae. It supports the interpretation of movement patterns through linked views of behavioural features and embedding spaces.
Introduction
I am a research associate at Ostfalia University of Applied Sciences and a doctoral researcher at the Institute of Visual Computing, Graz University of Technology.
I develop visual analytics methods for exploring high-dimensional behavioural data. My work combines interactive visualisation, machine learning, and quantitative behavioural analysis to help researchers connect patterns in data with observable animal behaviour. Much of my research concerns Drosophila larvae and questions in behavioural neurobiology.
Research
Visual analytics for behavioural data
I investigate how interactive visualisations can support the exploration and interpretation of complex behavioural recordings. My work includes analysing relationships between behavioural features, exploring low-dimensional embeddings, and annotating behavioural patterns.
Behavioural representations and video evidence
I study representations of movement and behavioural sequences, with an emphasis on connecting computational results to the underlying video recordings. Current work explores temporal representations and visual analysis workflows for large behavioural datasets.
Quantitative behavioural neurobiology
In collaboration with experimental researchers, I analyse individual differences in locomotion, learning and memory, and behavioural modulation. Ongoing work also examines behavioural variation across Drosophila species, substrates, and social contexts.
Publications
Preprints
- Sen, E., Königsmann, S., Besharatifar, M., Ciuraszkiewicz, A., Demirci, S., Güler, A. I., Niewalda, T., Schleyer, M., Thane, M., König, C., Thoener, J., & Gerber, B. (2026). Starvation modulates associative short-term memory of Drosophila in a task-dependent manner. bioRxiv. preprint · doi
2026
- Kolms, J., Blum, K. M., Thane, M., Kurczveil, T., & Lehmann, D. J. (2026). Energy Optimized Green Light Assist in Varying Traffic Scenarios Using Reinforcement Learning. In SUMO Conference.
2025
- Thane, M., Blum, K. M., & Lehmann, D. J. (2025). Uncovering Relations in High-Dimensional Behavioral Data of Drosophila melanogaster. In VMV — Vision, Modeling and Visualization. doi · video
- Bormann, A., Körner, M. B., Dahse, A.-K., Gläß, S., Irmer, J., Lede, V., Alenfelder, J., Lehmann, J., Hall, D. C. N., Thane, M., Schleyer, M., Kostenis, E., Schöneberg, T., Bigl, M., Langenhan, T., Ljaschenko, D., & Scholz, N. (2025). Intron retention of an adhesion GPCR generates 1TM isoforms required for 7TM-GPCR function. Cell Reports, 44(1), 115078. doi
2023
- Thane, M., Blum, K. M., & Lehmann, D. J. (2023). CatNetVis: Semantic Visual Exploration of Categorical High-Dimensional Data with Force-Directed Graph Layouts. In EuroVis Short Papers. doi · demo · video
- Thane, M., Paisios, E., Stöter, T., Krüger, A.-R., Gläß, S., Dahse, A.-K., Scholz, N., Gerber, B., Lehmann, D. J., & Schleyer, M. (2023). High-resolution analysis of individual Drosophila melanogaster larvae uncovers individual variability in locomotion and its neurogenetic modulation. Open Biology, 13(4), 220308. doi
2019
- Thane, M., Viswanathan, V., Meyer, T. C., Paisios, E., & Schleyer, M. (2019). Modulations of microbehaviour by associative memory strength in Drosophila larvae. PLOS ONE, 14(10), e0224154. doi
Software and research systems
RelationExplorer
A visual analytics system for exploring relationships in high-dimensional behavioural data. It combines measures of association, clustering, and coordinated views to support the analysis of numerical and categorical attributes.
CatNetVis
A visual exploration approach for categorical high-dimensional data using semantic relationships and force-directed graph layouts.
KumaQ
An interactive map for exploring wildlife sightings in Hokkaido, Japan, across space and time.
Teaching and supervision
- DIGIT Project — Digital Technologies (M.Sc.), Clausthal University of Technology: Project support in Summer 2025, Winter 2025/26, Summer 2026, and Winter 2026/27.
- Computer Science Team Project (B.Sc.), Ostfalia University of Applied Sciences: Student project supervision in Summer 2023, Winter 2023/24, Winter 2025/26, and Summer 2026.
- Stream Processing (B.Sc.), Ostfalia University of Applied Sciences: Supporting the coordination of practical exercises in Winter 2026/27; previous teaching support and preparation of teaching materials.
- Lecture delivery: Teaching contributions in Summer 2026.
- Computer Vision (B.Sc.): Lecture delivery and course support.
- Data Engineering (B.Sc.): Lecture delivery and course support.
Contact
Michael Thane
Ostfalia University of Applied Sciences
Faculty of Computer Science
Wolfenbüttel, Germany
m.thane@ostfalia.de
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