Social Signals – Evolution of active sensing

New signals do not arise from nothing; they often evolve from pre-existing signals and acquire new functions over time. A particularly striking example is bat echolocation, in which bats emit sounds and use the returning echoes to detect and identify objects. A central idea is that echolocation may have evolved from social vocalizations that originally served communication rather than orientation. This transition offers a rare opportunity to understand how new biological functions arise.

We investigate this question by combining sensory ecology experiments with computational approaches. We record bat social vocalizations and echolocation signals in different contexts, analyze the echoes these signals can generate, and test whether ancestral social vocalizations may already have provided useful sensory information. To do so, we combine acoustic recordings, playback experiments, simulations, and machine learning with measurements of auditory brainstem responses. This allows us to trace how echolocation may have emerged from social signals and, more broadly, to better understand how communication and sensory systems evolve in animals.

Collaborating partners

Prof. Dr Yossi Yovel (Co-PI)