Straw Group Research

Neuroethology of insect vision and navigation

Our group is interested in the neural basis of visual and navigation behavior in insects. We are interested in scientific questions such as how and if insects find their way home or to a food resource again. Additionally, we develop technology such as tracking systems, virtual reality arenas and microscopes to extend the limits of what is possible to record from insects (and sometimes in other animals) as they move. Typically this technology development is aimed at allowing us to address a scientific question.

Path integration in freely walking Drosophila

Figure: Displacement experiments reveal that flies return to a wrongly remembered reward location. This shows that flies can use path integration despite other potential confounds such as pheromone cues. (From Titova et al. 2022.)

The abilities of some insects to return to locations with food is remarkable, especially when considering the small size of their brain. While better known for its importance as a genetic model organism than as a great navigator, the fly Drosophila melanogaster was recently discovered to return to a food source when walking in a featureless, dark arena, suggesting the presence of spatial memory abilities related to those of the famous insect navigators – the bees. Thus, we now have the opportunity to study spatial cognition, memory and goal-directed movement in a species which has been at the forefront of genetic research for a century. Evidence from evolutionarily diverse insects – from locusts to beetles, bees and flies – suggests that a key brain region, the central complex, whose architecture shares many features in all these animals, is likely involved in coordinating such navigation. We are characterizing the involvement of genetically accessible neurons in the central complex on path integration in freely walking Drosophila. We are additionally making use of virtual reality for freely walking flies to test the involvement of visual memory and path integration in navigation. By obtaining detailed knowledge about the behavioral capabilities of food search and navigation in Drosophila – an extremely well-studied genetic model organism – we would contribute to an ability to discuss these important behaviors in the context of the relevant neural circuits. Given recent molecular data that shows patterns of developmental expression of key transcription factors seems conserved in patterning the insect central complex and the mammalian basal ganglia, this work may even be relevant for understanding neural control of navigation across bilaterian animals.

Selected publications

Titova AV, Kau BE, Tibor S, Mach J, Vo-Doan TT, Wittlinger M, Straw AD. Displacement experiments provide evidence for path integration in Drosophila. Journal of Experimental Biology (2023) doi:10.1242/jeb.245289 Preprint on bioRxiv.

Neural circuits for Drosophila vision

Figure: Genetic advances, such as the Vienna Tiles GAL4 library, allow targeted expression of specific molecules in defined neurons. Combined with virtual reality experiments, we reverse-engineer the mechanisms and purpose of the fly eye.

The Drosophila visual system is ideally suited for investigations of how nervous systems orchestrate behavior. From powerful genetic tools that enable precise manipulations of individual cell types to decades of deep research across many labs, few sensory systems are better understood or more amendable to precise manipulation. Nevertheless, our knowledge of fly vision is far from complete even though it could help us understand human vision or build better robots. One area of particular interest for the Straw Lab is how visual circuits give rise to natural behavior. While many laboratories record the activity of visual neurons in restrained animals, the results from these powerful but reductionist experiments do not readily allow extrapolation to understanding the flight or walking behavior of freely moving animals. We have shown for example, that head movements are an essential component of freely flight in flies but are dispensible for good performance in a tethered flight assay (Stowers et al. 2017).

Figure: By modifying the visual feedback supplied to freely flying flies, we can make them follow arbitrary trajectories. This permits us to record extremely long trajectories in a confined experimental space, and quantify several aspects of sensory-motor performance.

Selected publications

Linneweber GA, Andriatsilavo M, Dutta SB, Bengochea M, Hellbruegge L, Liu G, Ejsmont RK, Straw AD, Wernet M, Hiesinger PR, Hassan B. A neurodevelopmental origin of behavioral individuality in the Drosophila visual system. Science 367(6482), 1112-1119 (2020) doi:10.1126/science.aaw7182 []
Stowers JR*, Hofbauer M*, Bastien R, Griessner J⁑, Higgins P⁑, Farooqui S⁑, Fischer RM, Nowikovsky K, Haubensak W, Couzin ID, Tessmar-Raible K✎, Straw AD✎. Virtual Reality for Freely Moving Animals. Nature Methods 14, 995–1002 (2017) doi:10.1038/nmeth.4399 [FreemoVR website]
Panser K*, Tirian L*, Schulze F*, Villalba S, Jefferis GSXE, Bühler K, Straw AD. Automatic segmentation of Drosophila neural compartments using GAL4 expression data reveals novel visual pathways. Current Biology 26(15), 1943-1954 (2016) doi:10.1016/j.cub.2016.05.052 See also the braincode website. Open-Access Link. Preprint on bioRxiv.
Fenk LM*, Poehlmann A*, Straw AD. Asymmetric processing of visual motion for simultaneous figure and background responses. Current Biology 24(24), 2913-2919 (2014) doi:10.1016/j.cub.2014.10.042
Censi A*, Straw AD*, Sayaman RW, Murray RM, Dickinson MH. Discriminating external and internal causes for heading changes in freely flying Drosophila. PLOS Computational Biology 9(2), 1-14 (2013) doi:10.1371/journal.pcbi.1002891
Straw AD, Lee S, Dickinson MH. The visual control of altitude in flying Drosophila. Current Biology 20(17), 1550-1556 (2010) doi:10.1016/j.cub.2010.07.025
Titova AV, Straw AD. Contradictory behavioral effects of neuronal perturbations on behavioral responses to linearly polarized light in freely walking Drosophila. bioRxiv (2024) doi:10.1101/2024.03.15.584848
Poehlmann A*, Soselisa S*, Fenk LM, Straw AD. A unifying model to predict multiple object orienting behaviors in tethered flies. bioRxiv (2018) doi:10.1101/379651

Tracking technology

Together with colleagues, Andrew Straw developed ome of the first camera-based insect tracking systems capable of using 3 or more cameras to track the position of an animal in 3D with low latency (Straw et al. 2010). Performing live tracking enables several types of experiments which are not otherwise possible. First, perspective-correct virtual reality becomes possible, which we demonstrated on flies, fish and mice (Stowers et al. 2017). Second, realtime optogenetic stimulation based on computer-controlled behavioral feedback is enabled (Bath et al. 2014). Third, the burden of collecting and storing hours of behavioral data is simplified because instead of storing raw video, already processed data is stored (Straw et al. 2022, Segre et al. 2016). This tracking technology remains in active development in the Straw lab as an open source system called Braid. Furthermore, it forms a central element of the Straw lab's research apparatus, a basis for collaboration with others (e.g. Dakin et al. 2018), and also this or related software is used by other labs.

Selected publications

Wittmann K, Ibrahim MG, Straw AD, Klein A-M, Staab M. Monitoring fast moving animals – building a customized camera system and evaluation toolset. Methods in Ecology and Evolution (2024) doi:10.1111/2041-210X.14322 Data at Code at
Straw AD, Pieters RPM, Muijres FT. Real-Time Tracking of Multiple Moving Mosquitoes. Cold Spring Harbor Protocols (2023) doi:10.1101/pdb.prot107927 URL:
Dakin R*, Segre PS*, Straw AD, Altshuler DL. Morphology, muscle capacity, skill, and maneuvering ability in hummingbirds. Science 359(6376), 653-657 (2018) doi:10.1126/science.aao7104
Stowers JR*, Hofbauer M*, Bastien R, Griessner J⁑, Higgins P⁑, Farooqui S⁑, Fischer RM, Nowikovsky K, Haubensak W, Couzin ID, Tessmar-Raible K✎, Straw AD✎. Virtual Reality for Freely Moving Animals. Nature Methods 14, 995–1002 (2017) doi:10.1038/nmeth.4399 [FreemoVR website]
Segre PS*, Dakin R*, Read TJG, Straw AD, Altshuler DL. Mechanical constraints on flight at high elevation decrease maneuvering performance of hummingbirds. Current Biology 26(24), 3368-3374 (2016) doi:10.1016/j.cub.2016.10.028
Bath DE*, Stowers JR*, Hörmann D, Poehlmann A, Dickson BJ✎, Straw AD✎. FlyMAD: Rapid thermogenetic control of neuronal activity in freely-walking Drosophila. Nature Methods 11(7), 756-762 (2014) doi:10.1038/nmeth.2973
Straw AD, Branson K, Neumann TR, Dickinson MH. Multicamera Realtime 3D Tracking of Multiple Flying Animals. Journal of The Royal Society Interface 8(11), 395-409 (2011) doi:10.1098/rsif.2010.0230

Moving cameras

Moving a camera to follow an animal allows overcoming barriers to high quality imaging imposed by physics. A tradeoff between high spatial resolution versus the size of the recording space fundamentally limits recordings with stationary cameras. Furthermore, motion blur caused by relative motion of the animal and the sensor can be a problem in photon limited scenarios, and such scenarios are common. Therefore, since starting my lab I have worked on combining computer vision with controlling motors to actively track animals with cameras.

Selected publications

Straw AD. Review of methods for animal videography using camera systems that automatically move to follow the animal. Integrative and Comparative Biology (2021) doi:10.1093/icb/icab126
Bath DE*, Stowers JR*, Hörmann D, Poehlmann A, Dickson BJ✎, Straw AD✎. FlyMAD: Rapid thermogenetic control of neuronal activity in freely-walking Drosophila. Nature Methods 11(7), 756-762 (2014) doi:10.1038/nmeth.2973
Vo-Doan TT, Titov VV, Harrap MJM, Lochner S, Straw AD. High Resolution Outdoor Videography of Insects Using Fast Lock-On Tracking. bioRxiv (2023) doi:10.1101/2023.12.20.572558 | Movie 1. High-speed video of bumble bee | Movie S5. Quadcopter-based bee tracking
Vo-Doan TT, Straw AD. Millisecond insect tracking system. arXiv (2020) doi:10.48550/arXiv.2002.12100 | arXiv:2002.12100 | Video on YouTube