Auditory cortical regions show resting-state functional connectivity with the default mode-like network in echolocating bats.

Echolocating bats are among the most social and vocal of all mammals. These animals are ideal subjects for functional MRI (fMRI) studies of auditory social communication given their relatively hypertrophic limbic and auditory neural structures and their reduced ability to hear MRI gradient noise. Yet, no resting-state networks relevant to social cognition (e.g., default mode-like networks or DMLNs) have been identified in bats since there are few, if any, fMRI studies in the chiropteran order. Here, we acquired fMRI data at 7 Tesla from nine lightly anesthetized pale spear-nosed bats (Phyllostomus discolor). We applied independent components analysis (ICA) to reveal resting-state networks and measured neural activity elicited by noise ripples (on: 10 ms; off: 10 ms) that span this species' ultrasonic hearing range (20 to 130 kHz). Resting-state networks pervaded auditory, parietal, and occipital cortices, along with the hippocampus, cerebellum, basal ganglia, and auditory brainstem. Two midline networks formed an apparent DMLN. Additionally, we found four predominantly auditory/parietal cortical networks, of which two were left-lateralized and two right-lateralized. Regions within four auditory/parietal cortical networks are known to respond to social calls. Along with the auditory brainstem, regions within these four cortical networks responded to ultrasonic noise ripples. Iterative analyses revealed consistent, significant functional connectivity between the left, but not right, auditory/parietal cortical networks and DMLN nodes, especially the anterior-most cingulate cortex. Thus, a resting-state network implicated in social cognition displays more distributed functional connectivity across left, relative to right, hemispheric cortical substrates of audition and communication in this highly social and vocal species.

Bioinspired sonar reflectors as guiding beacons for autonomous navigation.

Sonar sensors are universally applied in autonomous vehicles such as robots and driverless cars as they are inexpensive, energy-efficient, and provide accurate range measurements; however, they have some limitations. Their measurements can lead to ambiguous estimates and echo clutter can hamper target detection. In nature, echolocating bats experience similar problems when searching for food, especially if their food source is close to vegetation, as is the case for gleaning bats and nectar-feeding bats. However, nature has come up with solutions to overcome clutter problems and acoustically guide bats. Several bat-pollinated plants have evolved specially shaped floral parts that act as sonar reflectors, making the plants acoustically conspicuous. Here we show that artificial sonar beacons inspired by floral shapes streamline the navigation efficacy of sonar-guided robot systems. We developed floral-inspired reflector forms and demonstrate their functionality in 2 proof-of-principle experiments. First we show that the reflectors are easily recognized among dense clutter, and second we show that it is possible to discern different reflector shapes and use this identification to guide a robot through an unfamiliar environment. Bioinspired sonar reflectors could have a wide range of applications that could significantly advance sonar-guided systems.

Efficient encoding of spectrotemporal information for bat echolocation.

In most animals, natural stimuli are characterized by a high degree of redundancy, limiting the ensemble of ecologically valid stimuli to a significantly reduced subspace of the representation space. Neural encodings can exploit this redundancy and increase sensing efficiency by generating low-dimensional representations that retain all information essential to support behavior. In this study, we investigate whether such an efficient encoding can be found to support a broad range of echolocation tasks in bats. Starting from an ensemble of echo signals collected with a biomimetic sonar system in natural indoor and outdoor environments, we use independent component analysis to derive a low-dimensional encoding of the output of a cochlear model. We show that this compressive encoding retains all essential information. To this end, we simulate a range of psycho-acoustic experiments with bats. In these simulations, we train a set of neural networks to use the encoded echoes as input while performing the experiments. The results show that the neural networks' performance is at least as good as that of the bats. We conclude that our results indicate that efficient encoding of echo information is feasible and, given its many advantages, very likely to be employed by bats. Previous studies have demonstrated that low-dimensional encodings allow for task resolution at a relatively high level. In contrast to previous work in this area, we show that high performance can also be achieved when low-dimensional filters are derived from a data set of realistic echo signals, not tailored to specific experimental conditions.

Avoidance of non-localizable obstacles in echolocating bats: A robotic model.

Most objects and vegetation making up the habitats of echolocating bats return a multitude of overlapping echoes. Recent evidence suggests that the limited temporal and spatial resolution of bio-sonar prevents bats from separately perceiving the objects giving rise to these overlapping echoes. Therefore, bats often operate under conditions where their ability to localize obstacles is severely limited. Nevertheless, bats excel at avoiding complex obstacles. In this paper, we present a robotic model of bat obstacle avoidance using interaural level differences and distance to the nearest obstacle as the minimal set of cues. In contrast to previous robotic models of bats, the current robot does not attempt to localize obstacles. We evaluate two obstacle avoidance strategies. First, the Fixed Head Strategy keeps the acoustic gaze direction aligned with the direction of flight. Second, the Delayed Linear Adaptive Law (DLAL) Strategy uses acoustic gaze scanning, as observed in hunting bats. Acoustic gaze scanning has been suggested to aid the bat in hunting for prey. Here, we evaluate its adaptive value for obstacle avoidance when obstacles can not be localized. The robot's obstacle avoidance performance is assessed in two environments mimicking (highly cluttered) experimental setups commonly used in behavioral experiments: a rectangular arena containing multiple complex cylindrical reflecting surfaces and a corridor lined with complex reflecting surfaces. The results indicate that distance to the nearest object and interaural level differences allows steering the robot clear of obstacles in environments that return non-localizable echoes. Furthermore, we found that using acoustic gaze scanning reduced performance, suggesting that gaze scanning might not be beneficial under conditions where the animal has limited access to angular information, which is in line with behavioral evidence.

Optic and echo-acoustic flow interact in bats.

Echolocating bats are known to fly and forage in complete darkness, using the echoes of their actively emitted calls to navigate and to detect prey. However, under dim light conditions many bats can also rely on vision. Many flying animals have been shown to navigate by optic flow information and, recently, bats were shown to exploit echo-acoustic flow to navigate through dark habitats. Here, we show for the bat Phyllostomus discolor that, in lighted habitats where self-motion-induced optic flow is strong, optic and echo-acoustic flow interact to guide navigation. Echo-acoustic flow showed a surprisingly strong effect compared with optic flow. We thus demonstrate multimodal interaction between two far-ranging spatial senses, vision and echolocation, available in this combination almost exclusively in bats and toothed whales. Our results highlight the importance of merging information from different sensory systems in a sensory-specialist animal to successfully navigate and hunt under difficult conditions.

Low-cost synchronization of high-speed audio and video recordings in bio-acoustic experiments.

In this paper, we present a method for synchronizing high-speed audio and video recordings of bio-acoustic experiments. By embedding a random signal into the recorded video and audio data, robust synchronization of a diverse set of sensor streams can be performed without the need to keep detailed records. The synchronization can be performed using recording devices without dedicated synchronization inputs. We demonstrate the efficacy of the approach in two sets of experiments: behavioral experiments on different species of echolocating bats and the recordings of field crickets. We present the general operating principle of the synchronization method, discuss its synchronization strength and provide insights into how to construct such a device using off-the-shelf components.

Modeling bat prey capture in echolocating bats: The feasibility of reactive pursuit.

Echolocating bats are the only mammals engaging in airborne pursuit. In this paper, we implement a reactive model of sonar based prey pursuit in bats. Our simulations include a realistic prey localization mechanism as well as a model of the bat's motor behavior. In contrast to previous work, our model incorporates bats' ability to execute rapid saccadic scanning motions keeping the prey within its field of view. Decoupling the flight direction from the gaze direction allows our model to capture erratically moving prey using reactive control. We conclude that the rapid shifts in gaze direction allow bats to deal with the narrow field of view provided by their sonar system.

Sensorimotor Model of Obstacle Avoidance in Echolocating Bats.

Bat echolocation is an ability consisting of many subtasks such as navigation, prey detection and object recognition. Understanding the echolocation capabilities of bats comes down to isolating the minimal set of acoustic cues needed to complete each task. For some tasks, the minimal cues have already been identified. However, while a number of possible cues have been suggested, little is known about the minimal cues supporting obstacle avoidance in echolocating bats. In this paper, we propose that the Interaural Intensity Difference (IID) and travel time of the first millisecond of the echo train are sufficient cues for obstacle avoidance. We describe a simple control algorithm based on the use of these cues in combination with alternating ear positions modeled after the constant frequency bat Rhinolophus rouxii. Using spatial simulations (2D and 3D), we show that simple phonotaxis can steer a bat clear from obstacles without performing a reconstruction of the 3D layout of the scene. As such, this paper presents the first computationally explicit explanation for obstacle avoidance validated in complex simulated environments. Based on additional simulations modelling the FM bat Phyllostomus discolor, we conjecture that the proposed cues can be exploited by constant frequency (CF) bats and frequency modulated (FM) bats alike. We hypothesize that using a low level yet robust cue for obstacle avoidance allows bats to comply with the hard real-time constraints of this basic behaviour.

Conditional Entropy and Location Error in Indoor Localization Using Probabilistic Wi-Fi Fingerprinting.

Localization systems are increasingly valuable, but their location estimates are only useful when the uncertainty of the estimate is known. This uncertainty is currently calculated as the location error given a ground truth, which is then used as a static measure in sometimes very different environments. In contrast, we propose the use of the conditional entropy of a posterior probability distribution as a complementary measure of uncertainty. This measure has the advantage of being dynamic, i.e., it can be calculated during localization based on individual sensor measurements, does not require a ground truth, and can be applied to discrete localization algorithms. Furthermore, for every consistent location estimation algorithm, both the location error and the conditional entropy measures must be related, i.e., a low entropy should always correspond with a small location error, while a high entropy can correspond with either a small or large location error. We validate this relationship experimentally by calculating both measures of uncertainty in three publicly available datasets using probabilistic Wi-Fi fingerprinting with eight different implementations of the sensor model. We show that the discrepancy between these measures, i.e., many location estimates having a high location error while simultaneously having a low conditional entropy, is largest for the least realistic implementations of the probabilistic sensor model. Based on the results presented in this paper, we conclude that conditional entropy, being dynamic, complementary to location error, and applicable to both continuous and discrete localization, provides an important extra means of characterizing a localization method.

Augmented topological maps for three-dimensional navigation.

We describe an augmented topological map as an alternative for the proposed bicoded map. Inverting causality, the special nature of the vertical dimension is then no longer fixed a priori and the cause of specific navigation behavior, but a consequence of the combination of the specific geometry of the experimental environment and the motor capabilities of the experimental animals.

Astrocyte's self-repairing characteristics improve working memory in spiking neuronal networks.

Astrocytes play a significant role in the working memory (WM) mechanism, yet their contribution to spiking neuron-astrocyte networks (SNAN) is underexplored. This study proposes a non-probabilistic SNAN incorporating a self-repairing (SR) mechanism through endocannabinoid pathways to facilitate WM function. Four experiments were conducted with different damaging patterns, replicating close-to-realistic synaptic impairments. Simulation results suggest that the SR process enhances WM performance by improving the consistency of neuronal firing. Moreover, the intercellular astrocytic [Ca]2+ transmission via gap junctions improves WM and SR processes. With increasing damage, WM and SR activities initially fail for non-matched samples and then for smaller and minimally overlapping matched samples. Simulation results also indicate that the inclusion of the SR mechanism in both random and continuous forms of damage improves the resilience of the WM by approximately 20%. This study highlights the importance of astrocytes in synaptically impaired networks.

Dynamic spectral cues do not affect human sound localization during small head movements.

Natural listening involves a constant deployment of small head movement. Spatial listening is facilitated by head movements, especially when resolving front-back confusions, an otherwise common issue during sound localization under head-still conditions. The present study investigated which acoustic cues are utilized by human listeners to localize sounds using small head movements (below ±10° around the center). Seven normal-hearing subjects participated in a sound localization experiment in a virtual reality environment. Four acoustic cue stimulus conditions were presented (full spectrum, flattened spectrum, frozen spectrum, free-field) under three movement conditions (no movement, head rotations over the yaw axis and over the pitch axis). Localization performance was assessed using three metrics: lateral and polar precision error and front-back confusion rate. Analysis through mixed-effects models showed that even small yaw rotations provide a remarkable decrease in front-back confusion rate, whereas pitch rotations did not show much of an effect. Furthermore, MSS cues improved localization performance even in the presence of dITD cues. However, performance was similar between stimuli with and without dMSS cues. This indicates that human listeners utilize the MSS cues before the head moves, but do not rely on dMSS cues to localize sounds when utilizing small head movements.

Dominant glint based prey localization in horseshoe bats: a possible strategy for noise rejection.

Rhinolophidae or Horseshoe bats emit long and narrowband calls. Fluttering insect prey generates echoes in which amplitude and frequency shifts are present, i.e. glints. These glints are reliable cues about the presence of prey and also encode certain properties of the prey. In this paper, we propose that these glints, i.e. the dominant glints, are also reliable signals upon which to base prey localization. In contrast to the spectral cues used by many other bats, the localization cues in Rhinolophidae are most likely provided by self-induced amplitude modulations generated by pinnae movement. Amplitude variations in the echo not introduced by the moving pinnae can be considered as noise interfering with the localization process. The amplitude of the dominant glints is very stable. Therefore, these parts of the echoes contain very little noise. However, using only the dominant glints potentially comes at a cost. Depending on the flutter rate of the insect, a limited number of dominant glints will be present in each echo giving the bat a limited number of sample points on which to base localization. We evaluate the feasibility of a strategy under which Rhinolophidae use only dominant glints. We use a computational model of the echolocation task faced by Rhinolophidae. Our model includes the spatial filtering of the echoes by the morphology of the sonar apparatus of Rhinolophus rouxii as well as the amplitude modulations introduced by pinnae movements. Using this model, we evaluate whether the dominant glints provide Rhinolophidae with enough information to perform localization. Our simulations show that Rhinolophidae can use dominant glints in the echoes as carriers for self-induced amplitude modulations serving as localization cues. In particular, it is shown that the reduction in noise achieved by using only the dominant glints outweighs the information loss that occurs by sampling the echo.

Compressive sensing: a strategy for fluttering target discrimination employed by bats emitting broadband calls.

When foraging, so-called FM-bats emit sequences of frequency modulated (FM) calls in order to detect, identify, and localize edible prey. Once a potential target has been detected, various call and call sequence parameters, such as frequency sweep, pulse duration, and inter pulse interval (IPI) vary. In this paper, the possible functions of the variation of the IPI are studied. In particular, it is conjectured that the IPI patterns are an adaptive behavior that optimizes the signal design parameters in order to improve information retrieval. Such an irregular sampling strategy would be useful whenever bats need to characterize signal modulation (e.g., the wing beat of an insect) using a call emission rate lower than the signal modulation of interest. This problem can be recast as extracting features, in this case the joint acoustic and modulation frequency representation, from signals sampled at frequencies well below the Nyquist cut-off frequency. To study the possibility of such target classification using a sub-Nyquist sampling scheme, results derived in the context of compressive sensing are used. Processing echoes collected from both rotating computer fans and fluttering locusts, it is shown that such a strategy would allow FM-bats to discriminate between targets based on their different fluttering rates.

Communication breakdown: Limits of spectro-temporal resolution for the perception of bat communication calls.

During vocal communication, the spectro-temporal structure of vocalizations conveys important contextual information. Bats excel in the use of sounds for echolocation by meticulous encoding of signals in the temporal domain. We therefore hypothesized that for social communication as well, bats would excel at detecting minute distortions in the spectro-temporal structure of calls. To test this hypothesis, we systematically introduced spectro-temporal distortion to communication calls of Phyllostomus discolor bats. We broke down each call into windows of the same length and randomized the phase spectrum inside each window. The overall degree of spectro-temporal distortion in communication calls increased with window length. Modelling the bat auditory periphery revealed that cochlear mechanisms allow discrimination of fast spectro-temporal envelopes. We evaluated model predictions with experimental psychophysical and neurophysiological data. We first assessed bats' performance in discriminating original versions of calls from increasingly distorted versions of the same calls. We further examined cortical responses to determine additional specializations for call discrimination at the cortical level. Psychophysical and cortical responses concurred with model predictions, revealing discrimination thresholds in the range of 8-15 ms randomization-window length. Our data suggest that specialized cortical areas are not necessary to impart psychophysical resilience to temporal distortion in communication calls.

Morphology-induced information transfer in bat sonar.

It has been argued that an important part of understanding bat echolocation comes down to understanding the morphology of the bat sound processing apparatus. In this Letter we present a method based on information theory that allows us to assess target localization performance of bat sonar, without a priori knowledge on the position, size, or shape of the reflecting target. We demonstrate this method using simulated directivity patterns of the frequency-modulated bat Micronycteris microtis. The results of this analysis indicate that the morphology of this bat's sound processing apparatus has evolved to be a compromise between sensitivity and accuracy with the pinnae and the noseleaf playing different roles.

Cyto- and myeloarchitectural brain atlas of the pale spear-nosed bat (Phyllostomus discolor) in CT Aided Stereotaxic Coordinates.

The pale spear-nosed bat Phyllostomus discolor, a microchiropteran bat, is well established as an animal model for research on the auditory system, echolocation and social communication of species-specific vocalizations. We have created a brain atlas of Phyllostomus discolor that provides high-quality histological material for identification of brain structures in reliable stereotaxic coordinates to strengthen neurobiological studies of this key species. The new atlas combines high-resolution images of frontal sections alternately stained for cell bodies (Nissl) and myelinated fibers (Gallyas) at 49 rostrocaudal levels, at intervals of 350 µm. To facilitate comparisons with other species, brain structures were named according to the widely accepted Paxinos nomenclature and previous neuroanatomical studies of other bat species. Outlines of auditory cortical fields, as defined in earlier studies, were mapped onto atlas sections and onto the brain surface, together with the architectonic subdivisions of the neocortex. X-ray computerized tomography (CT) of the bat's head was used to establish the relationship between coordinates of brain structures and the skull. We used profile lines and the occipital crest as skull landmarks to line up skull and brain in standard atlas coordinates. An easily reproducible protocol allows sectioning of experimental brains in the standard frontal plane of the atlas. An electronic version of the atlas plates and supplementary material is available from https://doi.org/10.12751/g-node.8bbcxy.

Determining biosonar images using sparse representations.

Echolocating bats are thought to be able to create an image of their environment by emitting pulses and analyzing the reflected echoes. In this paper, the theory of sparse representations and its more recent further development into compressed sensing are applied to this biosonar image formation task. Considering the target image representation as sparse allows formulation of this inverse problem as a convex optimization problem for which well defined and efficient solution methods have been established. The resulting technique, referred to as L1-minimization, is applied to simulated data to analyze its performance relative to delay accuracy and delay resolution experiments. This method performs comparably to the coherent receiver for the delay accuracy experiments, is quite robust to noise, and can reconstruct complex target impulse responses as generated by many closely spaced reflectors with different reflection strengths. This same technique, in addition to reconstructing biosonar target images, can be used to simultaneously localize these complex targets by interpreting location cues induced by the bat's head related transfer function. Finally, a tentative explanation is proposed for specific bat behavioral experiments in terms of the properties of target images as reconstructed by the L1-minimization method.

Bats Actively Use Leaves as Specular Reflectors to Detect Acoustically Camouflaged Prey.

Filtering relevant signals from noisy sensory input is a crucial challenge for animals [1, 2]. Many bats are acoustic specialists relying on sound to find prey. They discern salient acoustic signals from irrelevant background masking noise. It has long been considered a sensory impossibility for bats to use solely echolocation for the detection of silent and motionless prey resting directly on foliage due to the masking effects of background echoes [3, 4]. Some bats, however, do successfully perform this seemingly impossible task [5], raising the question-what underlying acoustic and behavioral mechanisms do bats use to solve this conundrum? To address this question, we used biomimetic sonar to record high-resolution measurements of echoes from insects resting on leaves. Based on our echo recordings, we predicted optimal approach angles from which masking echoes can best be avoided. In behavioral experiments, we put these predictions to test. We recorded the prey approach behavior of wild bats in a flight cage equipped with an ultrasonic microphone synchronized with two high-speed cameras for 3D flightpath reconstructions. Bats approached prey from our predicted optimal oblique angles, using the leaf as a specular reflector to uncover previously acoustically hidden prey. Our findings disclose key behavioral and acoustic mechanisms enabling the detection of prey echoes that background clutter would otherwise mask. This work adds to the fundamental understanding of how bat echolocation strategies can override acoustic camouflage by silent, motionless prey, thus providing new insights into the evolutionary arms race between predators and their prey.