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Neuroscience of Insect Vision Laboratory

electrophysiology, flower visitation, motion vision, natural images...

Hoverfly feeding from a canola plant in the Himalayas.
In one of our projects we are trying to determine the
multimodal factors that are involved in flower choice


Research Summary

In the Motion Vision group we use hoverflies to understand how the nervous system codes visual information. We use a range of techniques, such as electrophysiology of single neurons in the fly brain, quantitative behaviour, free flight experiments, and field site measurements. Our neuroethological approach allows us to use behaviourally relevant stimuli in more controlled laboratory experiments.

For full and up-to-the-minute details, please see http://hoverflyvision.weebly.com/


Research Projects

Animal sensory systems are optimally adapted to those features typically encountered in natural surrounds, thus allowing neurons that have a limited bandwidth to encode almost impossibly large input ranges. Importantly, natural scenes are not random, and peripheral visual systems have therefore evolved to reduce the predictable redundancy, with remarkably similar retinal filters in insects and vertebrates. The vertebrate visual cortex is also optimally tuned to the spatial statistics of natural scenes, but much less is known about how the insect brain responds to these. We are addressing this topic using several techniques.

Hoverfly behavior has been remarkably understudied since the pioneering work in the 1970's by Mike Land and Tom Collett. To mitigate this deficiency we have several behavior projects lined up. We have developed a free flight arena, which is big and bright enough for hoverflies to display conspecific interactions. By filming the flies with two cameras we can reconstruct their 3D flight trajectories.

Hoverflies display more elaborate flight behavior than some more commonly studied dipteran flies, such as blowflies and houseflies. Accompanying the more exquisite behavior, we find a specialized repertoire of widefield motion sensitive neurons in the hoverfly. A long-term aim of our research is to investigate whether the different subset of neurons has allowed for further specialization of the extraction of the specific components of self-generated optic flow in the hoverfly system.

The world’s bee and bumblebee populations are declining, though an estimated 80% of European crops are directly dependent on insects for pollination. Preserving and promoting wild pollinators is therefore crucial for sustainable agriculture. In addition to maintaining natural habitats and reducing pesticide use, an increased understanding of why and how wild pollinators utilize certain sources will allow us to propose efficient planting and maintenance strategies that maximize crop pollination. Hoverflies are ecologically important alternative pollinators and provide an extremely valuable alternative to the world’s wavering bee populations.
In this project we utilize a multimodal and multivariate approach to determine the cues that attract hoverflies to specific pollination sites. We have a unique ability to measure multimodal parameters on a very local scale. Our pilot data suggests that a combination of visual, chemical, and abiotic cues create an optimal hoverfly signature for increased attraction to certain sites.

Selected Publications

Nordström K, Dahlbom J, Pragadheesh VS, Ghosh S, Olsson A, Dyakova O, Suresh SK and Olsson SB (2017) In situ modeling of multimodal floral cues attracting wild pollinators across environments. Proceedings of the National Academy of Sciences of the USA, 114(50):13218-13223.


Thyselius M and Nordström K (2016) Hoverfly locomotor activity is resilient to external influence and intrinsic factors. Journal of Comparative Physiology A, 202(1):45-54


Gonzalez-Bellido PT, Fabian ST and Nordström K (2016) Target detection in insects: Optical, neural and behavioral optimizations. Current Opinion in Neurobiology, 41:122-128


Hidayat E, Medvede A and Nordström K (2015) “Identification of the Reichardt Elementary Motion Detector Model”, In Advances in experimental medicine and biology; Signal and Image Analysis for Biomedical and Life Sciences, Eds: C Sun, T Bednarz, TD Pham, P Vallotton and D Wang, Springer Verlag, 01/2015; 823:83-105


Dyakova O, Lee Y-J, Longden KD, Kiselev VG and Nordström K (2015) A higher-order visual neuron tuned to the spatial amplitude spectra of natural scenes. Nature Communications, 6:8522


Wardill T, Knowles K, Barlow L, Tapia G, Nordström K, Olberg R, Gonzalez-Bellido P (2015) The killer fly hunger games: Target size and speed predict decision to pursuit. Brain, Behavior and Evolution, 86(1):28-37


Lee Y-J, Jönsson O and Nordström K (2015) Spatio-temporal dynamics of impulse responses to figure motion in optic flow neurons. PLoS ONE, 10(5):e012626


De Haan R, Lee Y-J and Nordström K (2014) Novel flicker-sensitive visual circuit neurons inhibited by stationary patterns. Journal of Neuroscience, 33(21):8980-8989


Nordström K and Gonzalez-Bellido PT (2013) Invertebrate vision: Peripheral adaptation to repeated object motion. Current Biology, 23(15):R655-R656


Nordström K (2012) Neural specializations for small target detection in insects. Current Opinion in Neurobiology, 22(2):272-278


De Haan R, Lee Y-J and Nordström K (2012) Octopaminergic modulation of contrast sensitivity. Frontiers in Integrative Neuroscience, 6:55



  • Karin Nordstrom, PhD, Grad Cert Educ (Higher Educ)

Support Staff

  • Sarah Nicholas, Research Assistant


  • Marissa Holden, PhD Student

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