Dr Steven Wiederman and Associate Professor David O'Carroll from the University's Centre for Neuroscience Research have been studying the underlying processes of insect vision and applying that knowledge in robotics and artificial vision systems.
The findings are that the brains of dragonflies combine opposite pathways - both an ON and OFF switch - when processing information about simple dark objects.
Lead author Wiederman said that to perceive the edges of objects and changes in light or darkness, the brains of many animals, including insects, frogs, and even humans, use two independent pathways, known as ON and OFF channels.
He said that most animals will use a combination of ON switches with other ON switches in the brain, or OFF and OFF, depending on the circumstances.
Wiederman explained that what is shown occurring in the dragonfly's brain is the combination of both OFF and ON switches, which happens in response to simple dark objects, likely to represent potential prey to this aerial predator.
He said that though they've found this new visual circuit in the dragonfly, it's possible that many other animals could also have this circuit for perceiving various objects.
The researchers were able to record their results directly from 'target-selective' neurons in dragonflies' brains. They presented the dragonflies with moving lights that changed in intensity, as well as both light and dark targets.
Wiederman said that that they discovered that the responses to the dark targets were much greater than we expected, and that the dragonfly's ability to respond to a dark moving target is from the correlation of opposite contrast pathways: OFF with ON.
He asserted that the exact mechanisms that occur in the brain for this to happen are of great interest in visual neurosciences generally, as well as for solving engineering applications in target detection and tracking.
Wiederman said that understanding how visual systems work can have a range of outcomes, such as in the development of neural prosthetics and improvements in robot vision.
The findings of the study have been published in The Journal of Neuroscience.