Professor David O'Carroll
Vision - Visual Neuroscience - Computational Neuroscience - Biomimetics - Neuromorphic Engineering.
My research investigates how the brain makes sense of the world viewed by the eye. Although I'm interested in general problems that cut across all areas of visual processing, I use insects as an ideal model for tackling problems at theoretical, physiological and behavioural levels. With a visual system that accounts for as much as 30% of the lifted mass, some flying insects invest more in vision than any other animal.
What happens to the abundance of information collected by such large eyes? How has the brain evolved to optimally extract the features from scenes that are most relevant to the behaviour adopted? These are the kind of questions we ask.
In answering these questions by studying the physiology of the brain, we are also collaborating with engineers and industry to develop robust models based on animal vision, for implementation in silicon hardware. We have succesfully developed novel computational systems in software and hardware, including silicon chips that robustly mimic the adaptive motion processing of biological visual pathways and tracking of moving features. Applications for our technology include the aerospace industry, guidance systems for robots and embedded collision avoidance sensors that could be incorporated in future motor vehicles or bionic vision systems. We are also collaborating with neural stem cell researchers to develop an interface between computer chips and living neurons that may one day allow us to develop neural prosthetics (bionic devices) to connect our motion sensing systems directly to the human brain.
For publication lists and download links to articles, please see:
- O'Carroll, D.
Feature detecting neurons in dragonflies.
- O'Carroll, D.C.,
Bidwell, N.J., Laughlin, S.B., & Warrant, E.J., (1996)
detectors matched to visual ecology.
Nature 382: 63-66,
- Dacke M, Nilsson
DE, Warrant EJ, Blest AD, Land MF, O'Carroll DC (1999)
form part of a compass organ in spiders
. Nature 401: 470-473,
- Harris, R.A.,
O'Carroll, D.C., & Laughlin, S.B., (2000)
Contrast gain reduction in fly
Neuron 28: 595-606
- Nordström, K &
O'Carroll D.C. (2009) Feature Detection and the Hypercomplex Property in
Insects. Trends in Neurosciences 32: 383-391 doi:10.1016/j.tins.2009.03.004
- Nordström, K,
Barnett, PD & O'Carroll D.C. (2006)
Insect detection of small targets
moving in visual clutter.
PLoS Biology 4: 378-386
- Barnett P.D.,
Nordström K, & O'Carroll D.C. (2007)
Retinotopic organization of
small-field-target-detecting neurons in the insect visual system.
Biology 17 (7): 569-578,
- Nordström, K,
Barnett, P.D, Moyer de Miguel, I., Brinkworth, R.S.A & O’Carroll, D.C.
Sexual Dimorphism in the Hoverfly Motion Vision Pathway.
18, 661–667, doi:10.1016/j.cub.2008.03.061
- Brinkworth R.S.A.
& O’Carroll D.C. (2009) Robust Models for Velocity Coding in Natural Scenes
Inspired by Insect Biology. PLoS Computational Biology 5(11):e1000555,
- Barnett, P.D.,
Nordström, K, & O’Carroll, D.C. (2010) Motion adaptation and the velocity
coding of natural scenes. Current Biology. 20: 994-999, doi:10.1016/j.cub.2010.03.072
- Wiederman, S.D., & O’Carroll, D.C. (2013) Selective Attention in an Insect Visual Neuron. Current Biology 23: 156-161, doi:10.1016/j.cub.2012.11.048
Expertise for Media Contact
|Categories||Medicine & Medical Research, Science & Technology|
|Expertise||Visual processing; motion detection; visual adaption; pattern analysis; vision; neuromorphic engineering; artificial vision; bio-inspired vision;|
|Notes||Alt phone: (08) 8303 5328|
Entry last updated: Sunday, 24 May 2015
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