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Bats, along with other animals that employ echolocation, rely on their ears more than their eyes for orientation and navigation. The creatures send out signals and then listen to the echo bouncing off an item. But just how the animals analyzed a spate of echoes coming off the same object, such as a leafy tree, has eluded scientists. New research suggests that bats are skilled statisticians. They appear to perform a type of statistical analysis on the sum of all the acoustical reflections in order to make sense of their complex surroundings.
When sonar emissions encounter an object, they form a characteristic signal that scientists call an impulse response (IR), which is essentially an acoustical picture. Simpler items result in straightforward IRs, whereas complex surfaces, such as foliage, lead to more chaotic ones. Lutz Wiegrebe of the Ludwig-Maximilians University in Munich and his colleagues tested the ability of lesser spear-nosed bats, Phyllostomus discolor (see image), to respond to computer-generated IRs for a variety of phantom objects. To do this, the researchers tweaked a statistical property known as roughness, which describes the amount of variation within the signal, and analyzed the bats¿ reactions.
They determined that bats can wade through some 4,000 reflected sonic emissions and distinguish among a variety of natural textures¿a conifer is smoother than a broad-leafed tree, for example¿without having to memorize specific reflection patterns. This ability to pick out particular trees has a notable benefit for P. discolor, which feeds on fruit, nectar, pollen and insects. The findings appear in a report published online this week by the Proceedings of the National Academy of Sciences.