Bats are fascinating creatures that have evolved to thrive in diverse and challenging environments. They can fly, hunt, and communicate in the dark, using a sophisticated system of sound production and perception.

However, how do they cope with the constant noise that surrounds them, both from their own vocalizations and from other sources?

A new study by researchers from Goethe University Frankfurt reveals some surprising insights into the bat's brain and how it processes sound signals.

Echolocation: A Sonic Superpower
(Photo : ROSLAN RAHMAN/AFP via Getty Images)

One of the most remarkable abilities of bats is echolocation, which allows them to navigate their surroundings by emitting ultrasonic sounds that bounce off solid surfaces and return as echoes.

By interpreting these echoes, they construct an "image" of their environment, detecting obstacles, prey, and predators.

Echolocation is not unique to bats, as some other animals, such as dolphins and whales, also use it. However, bats have developed a high degree of specialization and diversity in their echolocation system, adapting to different habitats and ecological niches.

For example, some bats use low-frequency sounds that can travel long distances and penetrate vegetation, while others use high-frequency sounds that can resolve fine details and avoid interference.

However, echolocation also poses a challenge for bats, as they have to deal with a lot of noise that can mask or distort their echoes.

This noise can come from various sources, such as wind, rain, insects, or other bats. How do bats filter out the relevant signals from the irrelevant ones?

Deviance Detection: A Neural Mechanism for Signal Selection

To answer this question, a team of researchers led by Johannes Wetekam and Professor Manfred Kössl from Goethe University Frankfurt conducted a series of experiments on Seba's short-tailed bat, a species known for its adeptness at navigating through complex environments.

They discovered that the brain of this bat is wired to predict the next signal and reacts more strongly to unexpected signals than to expected ones-a mechanism referred to as deviance detection.

Deviance detection is a cognitive process that enables animals and humans to detect changes or anomalies in their sensory input, such as a sudden loud noise or a flash of light.

It is thought to be important for learning, attention, and survival, as it helps to focus on novel or relevant stimuli and ignore irrelevant or repetitive ones.

The researchers found that deviance detection in bats occurs not only in high-level regions of the brain, such as the cortex, but also in low-level regions, such as the brainstem.

This is surprising, as the brainstem is usually associated with basic functions, such as breathing and heart rate, rather than complex cognitive processes.

The researchers suggest that this may be an evolutionary adaptation that allows bats to process sound signals faster and more efficiently.

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Natural Stimuli: A More Realistic Approach

In their previous studies, the researchers used artificial stimuli, such as pure tones or white noise, to elicit deviance detection in bats.

However, in their latest study, they ventured beyond these simple sounds and explored how deviance detection operates with natural communication and echolocation calls.

They found that when exposed to meaningful stimuli, rather than meaningless ones, there was a pronounced response in the bat's auditory world.

This suggests that deviance detection is not a generic phenomenon, but rather a context-dependent one, that depends on the meaning and relevance of the stimuli for the bat.

For example, a deviation in a communication call may indicate a social or emotional cue, while a deviation in an echolocation call may indicate a change in the environment or a potential threat.

The researchers hope that their findings will contribute to a better understanding of the bat's brain and how it adapts to the noisy world.

They also hope that their study will inspire more research on natural stimuli, rather than artificial ones, as they believe that this is a more realistic and informative approach to study animal cognition and behavior.

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