If you reverse engineer an animal’s behavioural strategy by asking how an animal would solve a task under specific constraints and then work out the optimal solution, you’ll find it’s often the case that animals are pretty close to optimal.
- Guillaume Hennequin
As in economics, there is a law of diminishing returns in neuroscience – doubling the investment going in doesn’t equal double the performance coming out. With a bigger brain comes more available resources that can be allocated to certain tasks, but everything has a cost, and evolution weighs the costs against the benefits in order to make the most efficient system.
“Larger brains are specialised for high performance, so there’s a definite advantage to being bigger and better,” says Professor Simon Laughlin of the Department of Zoology, whose research looks at the cellular costs associated with various neural tasks. “But since most animals actually have very small brains, there must also be advantages to being small.” Indeed, there is strong selection pressure to have the minimum performance required in order to survive and it’s not biologically necessary to be the best, only to be better than the nearest competitor.
So does size matter? Do small insects with relatively few neurons have the same capabilities as much larger animals? “When an animal is limited, is it because their neural system just can’t cope? Or is it because they’re actually optimised for their particular environment?” asks Dr Paloma Gonzalez-Bellido from Cambridge’s Department of Physiology, Development and Neuroscience.
With funding from the US Air Force, Gonzalez-Bellido is studying the hunting behaviours of various flying insects – from tiny killer flies, slightly larger robber flies to large dragonflies – to determine how their visual systems influence their attack strategy, and what sorts of trade-offs they have to make in order to be successful.
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Image: A dragonfly (blue) has a larger brain than a robber fly (green) or a killer fly (yellow), but what are the trade-offs?
Reproduced courtesy of University of Cambridge, Department of Engineering
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