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.

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.

True malaria prevalence in children under five: Bayesian estimation using data of malaria household surveys from three sub-Saharan countries.

BACKGROUND: Malaria is one of the major causes of childhood death in sub-Saharan countries. A reliable estimation of malaria prevalence is important to guide and monitor progress toward control and elimination. The aim of the study was to estimate the true prevalence of malaria in children under five in the Democratic Republic of the Congo, Uganda and Kenya, using a Bayesian modelling framework that combined in a novel way malaria data from national household surveys with external information about the sensitivity and specificity of the malaria diagnostic methods used in those surveys-i.e., rapid diagnostic tests and light microscopy. METHODS: Data were used from the Demographic and Health Surveys (DHS) and Malaria Indicator Surveys (MIS) conducted in the Democratic Republic of the Congo (DHS 2013-2014), Uganda (MIS 2014-2015) and Kenya (MIS 2015), where information on infection status using rapid diagnostic tests and/or light microscopy was available for 13,573 children. True prevalence was estimated using a Bayesian model that accounted for the conditional dependence between the two diagnostic methods, and the uncertainty of their sensitivities and specificities obtained from expert opinion. RESULTS: The estimated true malaria prevalence was 20% (95% uncertainty interval [UI] 17%-23%) in the Democratic Republic of the Congo, 22% (95% UI 9-32%) in Uganda and 1% (95% UI 0-3%) in Kenya. According to the model estimations, rapid diagnostic tests had a satisfactory sensitivity and specificity, and light microscopy had a variable sensitivity, but a satisfactory specificity. Adding reported history of fever in the previous 14 days as a third diagnostic method to the model did not affect model estimates, highlighting the poor performance of this indicator as a malaria diagnostic. CONCLUSIONS: In the absence of a gold standard test, Bayesian models can assist in the optimal estimation of the malaria burden, using individual results from several tests and expert opinion about the performance of those tests.

Satisfaction and Technology Evaluation of a Telehealth Robotic Program to Optimize Healthy Independent Living for Older Adults.

BACKGROUND AND PURPOSE: With the growth in the aging population, and shortage of primary care providers, telehealth programs are needed to optimize healthy independent living for older adults. The purpose of this study was to evaluate a nurse-led intervention program delivered through a telepresence robot to promote healthy lifestyles and address chronic illness management among older adults living independently in a retirement community. Telepresence robots provide two-way video-mediated communication with remote in-home navigation. DESIGN AND METHODS: Satisfaction and technology evaluation ratings of the Telehealth Community Health Assistance Team (T-CHAT) program, as well as qualitative data from open-ended questions, were obtained from 26 older adults and 7 nurse practitioner students. FINDINGS: On a scale from 1 = strongly disagree to 5 = strongly agree, satisfaction ratings were positive for usefulness (M = 3.90), ease of use (M = 4.16), and acceptability (M = 4.06). Technology evaluation ratings were high for all sessions (M = 4.35). Older adults and nurse practitioner students were highly complementary of the program. Areas for improvement were identified. CONCLUSIONS: The T-CHAT program demonstrated high ratings for satisfaction (usefulness, ease of use, acceptability) and for evaluation of the telepresence robot technology. Further refinement of the T-CHAT program is warranted, as is testing outcomes of this potentially viable mode of healthcare delivery. CLINICAL RELEVANCE: Robotics is the wave of the future and provides an innovative mode of delivery to address health promotion and chronic illness management in older adults. Satisfaction and technology evaluation of robotic technology is paramount prior to implementation of such programs into practice.

Using telehealth to optimize healthy independent living for older adults: A feasibility study.

The purpose of this study was to test feasibility of the Telehealth Community Health Assistance Team (T-CHAT), a nurse-led intervention delivered through a telepresence robot designed to promote healthy independent living among older adults. Using a quasi-experimental design, 21 older adults were divided into a T-CHAT group (n = 11) or a waitlist control group (n = 10). The T-CHAT group received 3 weekly health coaching sessions from a nurse practitioner student through the telepresence robot. Data trends were analyzed using two-way repeated measures analysis of covariance (ANCOVA) with baseline values as co-variates; effect sizes using partial eta squared (η2). Medium to large improvements in unhealthy days, depressive symptoms, sleep, quality of life, and confidence/self-efficacy were found favoring the T-CHAT group. Recruitment and retention strategies were successful, with lessons learned for future studies. Further research is warranted to refine and test efficacy of the T-CHAT program to promote healthy independent living among older adults.

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.

An adjusted bed net coverage indicator with estimations for 23 African countries.

BACKGROUND: Many studies have assessed the level of bed net coverage in populations at risk of malaria infection. These revealed large variations in bed net use across countries, regions and social strata. Such studies are often aimed at identifying populations with low access to bed nets that should be prioritized in future interventions. However, often spatial differences in malaria endemicity are not taken into account. By ignoring variability in malaria endemicity, these studies prioritize populations with little access to bed nets, even if these happen to live in low endemicity areas. Conversely, populations living in regions with high malaria endemicity will receive a lower priority once a seizable proportion is protected by bed nets. Adequately assigning priorities requires accounting for both the current level of bed net coverage and the local malaria endemicity. Indeed, as shown here for 23 African countries, there is no correlation between the level of bed net coverage and the level of malaria endemicity in a region. Therefore, the need for future interventions can not be assessed based on current bed net coverage alone. This paper proposes the Adjusted Bed net Coverage (ABC) statistic as a measure taking into account both local malaria endemicity and the level of bed net coverage. The measure allows setting priorities for future interventions taking into account both local malaria endemicity and bed net coverage. METHODS: A mathematical formulation of the ABC as a weighted difference of bed net coverage and malaria endemicity is presented. The formulation is parameterized based on a model of malaria epidemiology (Smith et al. Trends Parasitol 25:511-516, 2009). By parameterizing the ABC based on this model, the ABC as used in this paper is proxy for the steady-state malaria burden given the current level of bed net coverage. Data on the bed net coverage in under five year olds and malaria endemicity in 23 Sub-Saharan countries is used to show that the ABC prioritizes different populations than the level of bed net coverage by itself. Data from the following countries was used: Angola, Burkina Faso, Burundi, Cameroon, Congo Democratic Republic, Ethiopia, Ghana, Guinea, Kenya, Liberia, Madagascar, Malawi, Mali, Mozambique, Namibia, Nigeria, Rwanda, Senegal, Sierra Leone, Tanzania, Uganda, Zambia and Zimbabwe. The priority order given by the ABC and the bed net coverage are compared at the countries' level, the first level administrative divisions and for five different wealth quintiles. RESULTS: Both at national level and at the level of the administrative divisions the ABC suggests a different priority order for selecting countries and divisions for future interventions. When taking into account malaria endemicity, measures assessing equality in access to bed nets across wealth quintiles, such as slopes of inequality, are prone to change. This suggests that when assessing inequality in access to bed nets one should take into account the local malaria endemicity for populations from different wealth quintiles. CONCLUSION: Accounting for malaria endemicity highlights different countries, regions and socio-economic strata for future intervention than the bed net coverage by itself. Therefore, care should be taken to factor out any effects of local malaria endemicity in assessing bed net coverage and in prioritizing populations for further scale-up of bed net coverage. The ABC is proposed as a simple means to do this that is derived from an existing model of malaria epidemiology.

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.

Rapid learning of spatial representations for goal-directed navigation based on a novel model of hippocampal place fields.

The discovery of place cells and other spatially modulated neurons in the hippocampal complex of rodents has been crucial to elucidating the neural basis of spatial cognition. More recently, the replay of neural sequences encoding previously experienced trajectories has been observed during consummatory behavior-potentially with implications for rapid learning, quick memory consolidation, and behavioral planning. Several promising models for robotic navigation and reinforcement learning have been proposed based on these and previous findings. Most of these models, however, use carefully engineered neural networks, and sometimes require long learning periods. In this paper, we present a self-organizing model incorporating place cells and replay, and demonstrate its utility for rapid one-shot learning in non-trivial environments with obstacles.

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.

A method for estimating the orientation of a directional sound source from source directivity and multi-microphone recordings: principles and application.

Taking into account directivity of real sound sources makes it possible to try solving an interesting and biologically relevant problem: estimating the orientation in three-dimensional space of a directional sound source. The source, of known directivity, produces a broadband signal (in the ultrasonic range, in this application) that is recorded by microphones whose position with respect to source is known. An analytical method to process the recorded signals and estimate source orientation is developed in this paper. Experiments testing method performance in estimating source orientation were performed both in a laboratory environment with a Polaroid transducer as source and in a flight room with a Myotis daubentonii bat. In the first case, results showed the estimation method to be accurate and pointed out its limitations. The latter case is significant as an example biological application of the method for extracting behavioral features from bats; results are compared with alternative calculations based on microphone root-mean-square (rms)-pressure values.

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.

Simulated trust: a cheap social learning strategy.

Animals use heuristic strategies to determine from which conspecifics to learn socially. This leads to directed social learning. Directed social learning protects them from copying non-adaptive information. So far, the strategies of animals, leading to directed social learning, are assumed to rely on (possibly indirect) inferences about the demonstrator's success. As an alternative to this assumption, we propose a strategy that only uses self-established estimates of the pay-offs of behavior. We evaluate the strategy in a number of agent-based simulations. Critically, the strategy's success is warranted by the inclusion of an incremental learning mechanism. Our findings point out new theoretical opportunities to regulate social learning for animals. More broadly, our simulations emphasize the need to include a realistic learning mechanism in game-theoretic studies of social learning strategies, and call for re-evaluation of previous findings.

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.

The frequency effect in second-language visual word recognition.

A lexical decision experiment with Dutch-English bilinguals compared the effect of word frequency on visual word recognition in the first language with that in the second language. Bilinguals showed a considerably larger frequency effect in their second language, even though corpus frequency was matched across languages. Experiment 2 tested monolingual, native speakers of English on the English materials from Experiment 1. This yielded a frequency effect comparable to that of the bilinguals in Dutch (their L1). These results constrain the way in which existing models of word recognition can be extended to unbalanced bilingualism. In particular, the results are compatible with a theory by which the frequency effect originates from implicit learning. They are also compatible with models that attribute frequency effects to serial search in frequency-ordered bins (Murray & Forster, 2004), if these models are extended with the assumption that scanning speed is language dependent, or that bins are not language specific.

Place recognition using batlike sonar.

Echolocating bats have excellent spatial memory and are able to navigate to salient locations using bio-sonar. Navigating and route-following require animals to recognize places. Currently, it is mostly unknown how bats recognize places using echolocation. In this paper, we propose template based place recognition might underlie sonar-based navigation in bats. Under this hypothesis, bats recognize places by remembering their echo signature - rather than their 3D layout. Using a large body of ensonification data collected in three different habitats, we test the viability of this hypothesis assessing two critical properties of the proposed echo signatures: (1) they can be uniquely classified and (2) they vary continuously across space. Based on the results presented, we conclude that the proposed echo signatures satisfy both criteria. We discuss how these two properties of the echo signatures can support navigation and building a cognitive map.

The aerodynamic cost of head morphology in bats: maybe not as bad as it seems.

At first sight, echolocating bats face a difficult trade-off. As flying animals, they would benefit from a streamlined geometric shape to reduce aerodynamic drag and increase flight efficiency. However, as echolocating animals, their pinnae generate the acoustic cues necessary for navigation and foraging. Moreover, species emitting sound through their nostrils often feature elaborate noseleaves that help in focussing the emitted echolocation pulses. Both pinnae and noseleaves reduce the streamlined character of a bat's morphology. It is generally assumed that by compromising the streamlined charactered of the geometry, the head morphology generates substantial drag, thereby reducing flight efficiency. In contrast, it has also been suggested that the pinnae of bats generate lift forces counteracting the detrimental effect of the increased drag. However, very little data exist on the aerodynamic properties of bat pinnae and noseleaves. In this work, the aerodynamic forces generated by the heads of seven species of bats, including noseleaved bats, are measured by testing detailed 3D models in a wind tunnel. Models of Myotis daubentonii, Macrophyllum macrophyllum, Micronycteris microtis, Eptesicus fuscus, Rhinolophus formosae, Rhinolophus rouxi and Phyllostomus discolor are tested. The results confirm that non-streamlined facial morphologies yield considerable drag forces but also generate substantial lift. The net effect is a slight increase in the lift-to-drag ratio. Therefore, there is no evidence of high aerodynamic costs associated with the morphology of bat heads.