Xenopus relies on about 200 so-called lateral-line organs to navigate and detect prey. These organs are located along the sides of its body, and also around its eyes, head and neck. Each lateral-line organ contains 4 to 8 small gelatinous ‘cupulae’, which can be deflected by local movements in the water. This deflection stimulates sensory hair cells at the base of each cupula, which then generate a neuronal response.


Now, Jan-Moritz Franosch and co-workers have created a ‘minimal model’ of the frog’s neuronal activity using a simple algorithm. This model first eliminates noise effects caused by the non-identical wave patterns produced by an insect. It then explains how the frog can reconstruct the shape of a water wave – its ‘waveform’ - to determine the direction of the prey, as well as information about its size and shape. Moreover, the model shows how Xenopus can resolve two overlapping waves – from two different insects for example - with different frequencies because it is able to separate out the component waveforms.

“We found that the frog’s detection system is very robust because it functions even if half of the organs are not working,” team leader Leo van Hemmen told PhysicsWeb. “We hope that by proving that the frog performs waveform reconstruction, biologists will now be able to work out its underlying neuroanatomy.” The team also hopes to apply its results to other aquatic amphibians, fish and even reptiles such as crocodiles.