Variability in the rigid pinna motions of hipposiderid bats and their impact on sensory information encoding

Theoretical investigation of active listening behavior based on the echolocation of CF-FM bats

Bats perceive the three-dimensional environment by emitting ultrasound pulses from their nose or mouth and receiving echoes through both ears. To determine the position of a target object, it is necessary to know the distance and direction of the target. Certain bat species that use a combined signal of long constant frequency and short frequency modulated ultrasounds synchronize their pinnae movement with pulse emission, and this behavior has been regarded as helpful for localizing the elevation angle of a reflective sound source. However, the significance of bats' ear motions remains unclear. In this study, we construct a model of an active listening system including the motion of the ears, and conduct mathematical investigations to clarify the importance of ear motion in direction detection of the reflective sound source. In the simulations, direction detection under rigid ear movements with interaural level differences was mathematically investigated by assuming that bats accomplish direction detection using the amplitude modulation in the echoes caused by ear movements. In particular, the ear motion conditions required for direction detection are theoretically investigated through exhaustive simulations of the pseudo-motion of the ears, rather than simulations of the actual ear motions of bats. The theory suggests that only certain ear motions, namely three-axis rotation, allow for accurate and robust direction detection. Our theoretical analysis also strongly supports the behavior whereby bats move their pinnae in the antiphase mode. In addition, we suggest that simple shaped hearing directionality and well-selected uncomplicated ear motions are sufficient to achieve precise and robust direction detection. Our findings and mathematical approach have the potential to be used in the design of active sensing systems in various engineering fields.

Biomimetic detection of dynamic signatures in foliage echoes

Certain bat species (familyRhinolophidae) dynamically deform their emission baffles (noseleaves) and reception baffles (pinnae) during echolocation. Prior research using numerical models, laboratory characterizations, and experiments with simple targets have suggested that this dynamics may manifest itself in time-variant echo signatures. Since the pronounced random nature of echoes from natural targets such as foliage has not been reflected in these experiments, we have collected a large number (>55 000) of foliage echoes outdoors with a sonar head that mimics the dynamic periphery in bats. The echo data was processed with a custom auditory processing model to create spike-based echo representations. Deep-learning classifiers were able to estimate the dynamic state of the periphery, i.e., static or dynamic, based on single echoes with accuracies of up to 80%. This suggests that the effects of the peripheral dynamics are present in the bat brains and could hence be used by the animals. The best classification performances were obtained for data obtained within a spatially confined area. Hence, if the bat brains suffer from the same generalization issues, they would have to have a way to adapt their neural echo processing to such local fluctuations to exploit the dynamic effects successfully.

A biomimetic soft robotic pinna for emulating dynamic reception behavior of horseshoe bats

Encoding of sensory information is fundamental to closing the performance gap between man-made and biological sensing. It has been hypothesized that the coupling of sensing and actuation, a phenomenon observed in bats among other species, is critical to accomplishing this. Using horseshoe bats as a model, we have developed a biomimetic pinna model with a soft actuation system along with a prototype strain sensor for enabling motor feedback. The actuation system used three individually controlled pneumatic actuators per pinna which actuated different portions of the baffle. This prototype produced eight different possible motions that were shown to have significant effects on incoming sound and could hence function as a substrate for adaptive sensing. The range of possible motions could be expanded by adjusting the fill and release parameters of the actuation system. Additionally, the strain sensor was able to represent the deformation of the pinna as measurements from this sensor were highly correlated with deformation estimates based on stereo vision. However, the relationship between displacements of points on the pinna and the sensor output was nonlinear. The improvements embodied in the system discussed here could lead to enhancements in the ability of autonomous systems to encode relevant information about the real world.