Modeling active sensing reveals echo detection even in large groups of bats

Abstract

Active sensing animals perceive their surroundings by emitting probes of energy and analyzing how the environment modulates these probes. However, the probes of conspecifics can jam active sensing, which should cause problems for groups of active sensing animals. This problem was termed the cocktail party nightmare for echolocating bats: as bats listen for the faint returning echoes of their loud calls, these echoes will be masked by the loud calls of other close-by bats. Despite this problem, many bats echolocate in groups and roost socially. Here, we present a biologically parametrized framework to quantify echo detection in groups. Incorporating properties of echolocation, psychoacoustics, acoustics, and group flight, we quantify how well bats flying in groups can detect each other despite jamming. A focal bat in the center of a group can detect neighbors in group sizes of up to 100 bats. With increasing group size, fewer and only the closest and frontal neighbors are detected. Neighbor detection is improved by longer call intervals, shorter call durations, denser groups, and more variable flight and sonar beam directions. Our results provide a quantification of the sensory input of echolocating bats in collective group flight, such as mating swarms or emergences. Our results further generate predictions on the sensory strategies bats may use to reduce jamming in the cocktail party nightmare. Lastly, we suggest that the spatially limited sensory field of echolocators leads to limited interactions within a group, so that collective behavior is achieved by following only nearest neighbors.

A sensorimotor model shows why a spectral jamming avoidance response does not help bats deal with jamming

“…Our work demonstrates the power of simulations to reveal new insight into complex biological systems that are difficult to examine and analyze otherwise. Our model shows that jamming is less of a problem than previously suggested by most researchers (but see Beleyur and Goerlitz, 2019 ). It proves that bats can successfully hunt in the presence of other bats without applying any JAR and shows that applying a JAR has no significant impact on hunting performance and on prey detection.…”

“…The jamming problem is one of the most fundamental challenges raised by researchers of echolocation, but, only a few studies ( Beleyur and Goerlitz, 2019 ; Lin and Abaid, 2015 ; Jarvis et al, 2013 ; Cvikel et al, 2015b ) used a mathematical model to examine the actual chances of being jammed by another bat, and how such jamming would affect hunting performance. Addressing these questions is a difficult task with real bats as even if a microphone is placed on the bat, it is typically not as sensitive as the bat itself and it is not placed inside the ear.…”

“…2.4.5, ( Blauert, 1997 ) ch. 3.1 and ( Mhl and Surlykke, 1989 ), and comprise lower boundaries of real bats’ abilities to cope with masking ( Beleyur and Goerlitz, 2019 ). For simplicity, we used constant thresholds within each window.…”

“…The question of how bats deal with conspecific masking ( Beleyur and Goerlitz, 2019 ; Jones and Conner, 2019 ) and whether they perform a spectral Jamming Avoidance Response (JAR) has been widely studied but is still under dispute. Many studies have suggested that bats change their echolocation frequencies when hunting at the presence of other bats ( Takahashi et al, 2014 ; Ibáñez et al, 2004 ; Chiu et al, 2009 ; Ulanovsky et al, 2004 ) or when exposed to playback of partially or fully overlapping signals ( Gillam et al, 2007 ; Gillam and Montero, 2016 ; Bates et al, 2008 ; Luo and Moss, 2017 ; Corcoran and Conner, 2014 ).…”

Learning interaction rules from multi-animal trajectories via augmented behavioral models

“…As a result, among 138 interactions of all 34 individuals within the leaving and returning groups, there were 46 interactions where the locationally-leading (i.e., flying forward) bats repelled the following bats in the same direction, 27 interactions where the leading bats were attracted from the following bats, 65 ones with no interactions (the results of the following bats were not discussed because it was obvious; see also example results of 27 bats in Figure 2C). Since bats can echo-locate other bats in all directions up to a range of approximately 20 m [43,6], the locationally-leading bats can be influenced by the locationally-following bats in the same direction (if no perception, they cannot be influenced). The results suggest that the groups of flying bats would not show simple leader-follower relationships.…”