Echolocating bats accumulate information from acoustic snapshots to predict auditory object motion Angeles Sallesa,1,2, Clarice Anna Diebolda,2, and Cynthia F. Mossa aDepartment of Psychological and Brain Sciences, Johns Hopkins University, Baltimore, MD 21218 Edited by Ranulfo Romo, National Autonomous University of Mexico, Mexico City, D.F., Mexico, and approved October 1, 2020 (received for review June 8, 2020) Unlike other predators that use vision as their primary sensory echo reception (6). Bats actively modify the duration, direction, system, bats compute the three-dimensional (3D) position of flying timing, intensity, and spectral content of their calls in response to insects from discrete echo snapshots, which raises questions about information carried by echoes, which allows them to flexibly react to the strategies they employ to track and intercept erratically mov- changes in the environment, such as the trajectory of a target (7). ing prey from interrupted sensory information. Here, we devised The big brown bat, Eptesicus fuscus, produces frequency-modulated an ethologically inspired behavioral paradigm to directly test the echolocation signals to hunt for flying insects (8). When the big hypothesis that echolocating bats build internal prediction models brown bat approaches prey and initiates target capture, it increases from dynamic acoustic stimuli to anticipate the future location of the rate of its sonar calls and locks its sonar beam aim, aligned with moving auditory targets. We quantified the direction of the bat’s the head, onto the target ∼300 ms before contact (6, 9). This animal head/sonar beam aim and echolocation call rate as it tracked a therefore presents a powerful model to investigate internal models target that moved across its sonar field and applied mathematical of target motion, which govern auditory tracking strategies. models to differentiate between nonpredictive and predictive When a bat is tracking free-flying insect prey, it must rely on tracking behaviors. We discovered that big brown bats accumulate brief and interrupted echo snapshots while also accommodating information across echo sequences to anticipate an auditory tar- the acoustic and neural delays inherent to sonar imaging, as well get’s future position. Further, when a moving target is hidden as abrupt changes in a target’s trajectory and temporary occlu- from view by an occluder during a portion of its trajectory, the sions. The delays include the time it takes for a sonar call to bat continues to track its position using an internal model of the travel through the air from the bat to an object, the returning ’ PSYCHOLOGICAL AND COGNITIVE SCIENCES target s motion path. Our findings also reveal that the bat in- echo to arrive at the bat’s ears, and the brain to process echo creases sonar call rate when its prediction of target trajectory is features and to generate a motor response. The acoustic and violated by a sudden change in target velocity. This shows that the neural delays can add up to over 100 ms for each sonar snapshot bat rapidly adapts its sonar behavior to update internal models of (7), during which time the spatial location of the target relative auditory target trajectories, which would enable tracking of eva- to the bat has likely changed. Moreover, insects may show erratic sive prey. Collectively, these results demonstrate that the echolo- flight behaviors and move behind obstacles. How does the bat cating big brown bat integrates acoustic snapshots over time to ’ overcome these challenges? The fact that bats commonly execute build prediction models of a moving auditory target s trajectory successful prey captures, despite acoustic and neural delays, and enable prey capture under conditions of uncertainty. leads us to hypothesize that they accumulate information about target motion from a sequence of echoes to build internal prediction Eptesicus fuscus | predictive models | biosonar | prey tracking | auditory localization Significance ensing and action operate in concert to enable a broad suite Research on visual tracking of moving stimuli has contributed of animal behaviors, such as navigation, reaching, and object S to our understanding of sensory-guided behaviors; however, tracking. Decades of research on visual tracking of two-dimensional the processes that support auditory object tracking in natural moving stimuli have contributed to our understanding of sensory- three-dimensional environments remain largely unknown. This guided behaviors; however, the mechanisms that support auditory is important, not only to diverse groups of animals, but also to object tracking in natural three-dimensional (3D) environments humans that rely on hearing to track objects in their environ- remain largely unknown. This is important, not only to animals, but ment. For visually impaired individuals, hearing is paramount also to humans who rely on hearing to track objects in their envi- for auditory object tracking and navigation, and in recent ronment. For visually impaired individuals, hearing is paramount years, mobility training programs for the blind include in- for auditory object tracking and navigation, and many blind hu- struction on echolocation using tongue clicks. In this work, we mans use echolocation, the production of sound (often tongue provide conclusive demonstration that echolocating bats use clicking) to generate echoes that provide information about the predictive strategies to track moving auditory objects, which environment (1, 2). Here, we report discoveries on auditory object can inform future comparative work on auditory motion tracking from studies of the echolocating bat, a powerful and processing. tractable model system for quantifying 3D object localization under conditions of uncertainty. The bat relies on active acoustic sensing Author contributions: A.S. and C.F.M. designed research; A.S. and C.A.D. performed re- to compute the 3D trajectory of insects flying in and around veg- search; A.S., C.A.D., and C.F.M. contributed new reagents/analytic tools; A.S. and C.A.D. etation from sequences of acoustic “snapshots,” which it uses to analyzed data; and A.S., C.A.D., and C.F.M. wrote the paper. guide interception. Notably, the bat’ssonartrackingbehaviors The authors declare no competing interest. provide a direct metric of its spatial gaze at discrete instants in time. This article is a PNAS Direct Submission. Echolocating bats employ an active audiomotor feedback system Published under the PNAS license. to localize and track targets in their environment. By emitting dis- 1To whom correspondence may be addressed. Email: [email protected]. crete ultrasonic signals, bats probe their surroundings and listen to 2A.S. and C.A.D. contributed equally to this work. the features of “acoustic snapshots” returning from objects (3–5). This article contains supporting information online at https://www.pnas.org/lookup/suppl/ Successful tracking requires the coordination of dynamic echolo- doi:10.1073/pnas.2011719117/-/DCSupplemental. cation behavior and head aim to control sonar beam direction and www.pnas.org/cgi/doi/10.1073/pnas.2011719117 PNAS Latest Articles | 1of10 Downloaded by guest on September 27, 2021 models of insect trajectories. Indirect support for predictive strate- gies used by echolocating bats comes mainly from reconstructed prey-capture events in the laboratory (10, 11) and mathematical models based on biological data from foraging bats (12, 13). Yet, previous experimental tests of sonar target tracking behaviors reported that echolocating bats use a nonpredictive strategy, based on information processed from the last returning echo, and this finding has never been replicated (14, 15). Here, using an etholog- ically inspired behavioral paradigm, we directly test the hypothesis that the echolocating bat accumulates information about target position from acoustic snapshots over time to predict an auditory object’strajectory. By using internal models to extrapolate the future position of an auditory object, bats can compensate for the delays due to the travel time of sound in air, neural processing of echo features, and motor response times. We hypothesize that bats integrate acoustic information to build predictive models that allow for the anticipatory tracking of targets moving across their acoustic field. We propose that such internal models permit anticipatory head aim, even when the target trajectory is temporarily occluded. In this work, we settle a longstanding controversy over bat sonar tracking strategies with empirical data, demonstrating that bats acquire information over streams of discrete echoes to anticipate the future location of a moving target, even when the object is temporarily occluded. Additionally, we show that when changes in target velocity occur, bats update their internal models by sampling echo information about target position at an increased rate. Results Evidence for Predictive Tracking of Targets with Simple Motion Paths. Bats were trained to track a moving target traveling along a simple trajectory across their acoustic field. During testing, six different target motions (standard simple motion, slow simple motion, catch [no target motion], velocity change fast, velocity change slow, back-and-forth motion) and occlusion conditions were presented to the bat randomly (Materials and Methods). The randomization of trials during testing prevented the bats from learning the motion path of an object and instead, required that they actively track the target according