Tongue-driven sonar beam steering by a lingual-echolocating fruit bat

Abstract

Animals enhance sensory acquisition from a specific direction by movements of head, ears, or eyes. As active sensing animals, echolocating bats also aim their directional sonar beam to selectively “illuminate” a confined volume of space, facilitating efficient information processing by reducing echo interference and clutter. Such sonar beam control is generally achieved by head movements or shape changes of the sound-emitting mouth or nose. However, lingual-echolocating Egyptian fruit bats, Rousettus aegyptiacus, which produce sound by clicking their tongue, can dramatically change beam direction at very short temporal intervals without visible morphological changes. The mechanism supporting this capability has remained a mystery. Here, we measured signals from free-flying Egyptian fruit bats and discovered a systematic angular sweep of beam focus across increasing frequency. This unusual signal structure has not been observed in other animals and cannot be explained by the conventional and widely-used “piston model” that describes the emission pattern of other bat species. Through modeling, we show that the observed beam features can be captured by an array of tongue-driven sound sources located along the side of the mouth, and that the sonar beam direction can be steered parsimoniously by inducing changes to the pattern of phase differences through moving tongue location. The effects are broadly similar to those found in a phased array—an engineering design widely found in human-made sonar systems that enables beam direction changes without changes in the physical transducer assembly. Our study reveals an intriguing parallel between biology and human engineering in solving problems in fundamentally similar ways.

Signatures of echolocation and dietary ecology in the adaptive evolution of skull shape in bats

“…), potentially incorporating both nasal and oral emission 41,74–76 . All pteropodids have lost laryngeal echolocation, although it is worth noting that at least one genus ( Rousettus ) echolocates through tongue-clicks 77 .…”

A Modular Approach to Vocal Learning: Disentangling the Diversity of a Complex Behavioral Trait

“…Although parrots have been shown to have more extensive forebrain circuitry for learned vocal behavior than songbirds (Chakraborty et al, 2015), the extent to which this circuitry plays a role in the control of vocal articulatory structures beyond the syrinx remains unexplored. Among bats, the Egyptian fruit bat (Rousettus aegypticus) similarly displays an exceptional degree of control over the tongue: whereas most bats' echolocation calls are produced from the larynx, in R. aegypticus they are exclusively tongue based (Lee et al, 2017;Yovel et al, 2011). These bats exhibit a capacity for long-term and persistent vocal plasticity of their social communication calls across multiple spectral parameters (Genzel et al, 2019;Prat et al, 2015Prat et al, , 2017, further supporting a potential link between the degree of control over the articulatory filtering structures and the capacity for vocal plasticity.…”

Inflight head stabilization associated with wingbeat cycle and sonar emissions in the Egyptian fruit bat

“…comparable to oculomotor stabilization resulting from the vestibulo-ocular reflex). They also noted that the Egyptian fruit bat sonar beam elevation was directed downward upon landing, which was previously reported in a detailed study of the sonar beam pattern of this species in straight flight (Lee et al, 2017). While these data suggested a strong influence of echolocation in driving head stabilization, the temporal association of sonar emissions with head stabilization was not measured, however, which would be critical to directly establish the sensorimotor link between head stabilization and acoustic gaze.…”

“…10kHz, 1-pole highpass filter) to reduce wind and wing noise. This processing strategy was sufficient for recording the broadband clicks emitted by R. aegyptiacus that typically exhibit peak energy at approximately 35kHz (Lee et al, 2017). This preprocessed audio channel was then digitized at 16-bits and stored in flash memory.…”