Adrian DyerDepartment of Physiology, Monash University, Melbourne, VIC, Australia F1000 Associate Faculty Member (since 06 April 2010)
Adrian Dyer is an Associate Faculty Member who works with Faculty Member Marcello Rosa to recommend the scientific literature in their field.ACADEMIC POSITION:
QEII Research Fellow, Department of Psychology
B App Sci, PhD (RMIT University)
Current investigations on insect vision include investigating how honeybees use their vision in complex natural environments to make decisions.
Honeybees are a cost and time efficient animal model for testing how information is processed in a miniature brain containing less than 0.01% of the number of cells found in a human brain. Bees use their ultraviolet, blue and green colour vision to efficiently find flowers in complex environments. This project investigates how colour information is processed by bees, and develops computer models to evaluate how novel solutions might be applicable for robotic vision. The model also allows for testing of how environmental factors, like changes in climate, might affect the way in which bees choose to visit certain flower types, including plants that have important environmental and economic impacts.
To recognise objects a brain must have an internal representation of most likely object appearance. Two ways in which brains may posses this information include a hard wired template system, and/or the neuroplasticity to learn novel objects. Recent investigations on honeybee vision show that this animal can learn to recognise very difficult objects, although currently we do not know how the miniaturised bee brain manages these tasks. This project will reveal changes that occur in the processing of visual objects by the bees brain with increasing experience, with potential applications including robotics or building interfaces between sensors and biological systems.
Current investigations on human vision include studying Forensic Document Examiner visual attention whilst test subjects solve complex visual tasks like discriminating forged signatures from genuine signatures.
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