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.

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.

Why Hantavirus Prevalence Does Not Always Increase With Host Density: Modeling the Role of Host Spatial Behavior and Maternal Antibodies

For wildlife diseases, one often relies on host density to predict host infection prevalence and the subsequent force of infection to humans in the case of zoonoses. Indeed, if transmission is mainly indirect, i.e., by way of the environment, the force of infection is expected to increase with host density, yet the laborious field data supporting this theoretical claim are often absent. Hantaviruses are among those zoonoses that have been studied extensively over the past decades, as they pose a significant threat to humans. In Europe, the most widespread hantavirus is the Puumala virus (PUUV), which is carried by the bank vole and causes nephropathia epidemica (NE) in humans. Extensive field campaigns have been carried out in Central Finland to shed light on this supposed relationship between bank vole density and PUUV prevalence and to identify other drivers for the infection dynamics. This resulted in the surprising observation that the relationship between bank vole density and PUUV prevalence is not purely monotonic on an annual basis, contrary to what previous models predicted: a higher vole density does not necessary result in a higher infection prevalence, nor in an increased number of humans reported having NE. Here, we advance a novel individual-based spatially-explicit model which takes into account the immunity provided by maternal antibodies and which simulates the spatial behavior of the host, both possible causes for this discrepancy that were not accounted for in previous models. We show that the reduced prevalence in peak years can be attributed to transient immunity, and that the density-dependent spatial vole behavior, i.e., the fact that home ranges are smaller in high density years, plays only a minor role. The applicability of the model is not limited to the study and prediction of PUUV (and NE) occurrence in Europe, as it could be easily adapted to model other rodent-borne diseases, either with indirect or direct transmission.

An Optimized Spatial Sampling Strategy for Wide-View Planar Array 3-D Sonar Sensors

Array-based imaging sonar sensors often have the advantage that the sampling directions in which sensor data are processed can be arbitrarily chosen. The associated computational cost of the imaging algorithm scales linearly with the number of sampled directions, though, which may limit the use of such sensors for real-time applications such as robotics. This is especially true in the case of wide-field sensors, which generally require a larger number of sampled directions (e.g., to cover the full frontal hemisphere). For this reason, it is necessary to optimize the set of sampling directions and reduce its number to a minimum. In this article, we propose a spatial sampling strategy for array-based sonar sensors, which considers the point-spread function of the array sensor to obtain such a minimal set. We apply this strategy to optimize the set of sampling directions for a specific planar array sonar sensor and compare the efficiency of the resulting sampling grid with two commonly used sampling strategies.

Density dependence and persistence of Morogoro arenavirus transmission in a fluctuating population of its reservoir host

A key aim in wildlife disease ecology is to understand how host and parasite characteristics influence parasite transmission and persistence. Variation in host population density can have strong impacts on transmission and outbreaks, and theory predicts particular transmission-density patterns depending on how parasites are transmitted between individuals. Here, we present the results of a study on the dynamics of Morogoro arenavirus in a population of multimammate mice (Mastomys natalensis). This widespread African rodent, which is also the reservoir host of Lassa arenavirus in West Africa, is known for its strong seasonal density fluctuations driven by food availability. We investigated to what degree virus transmission changes with host population density and how the virus might be able to persist during periods of low host density. A seven-year capture-mark-recapture study was conducted in Tanzania where rodents were trapped monthly and screened for the presence of antibodies against Morogoro virus. Observed seasonal seroprevalence patterns were compared with those generated by mathematical transmission models to test different hypotheses regarding the degree of density dependence and the role of chronically infected individuals. We observed that Morogoro virus seroprevalence correlates positively with host density with a lag of 1-4 months. Model results suggest that the observed seasonal seroprevalence dynamics can be best explained by a combination of vertical and horizontal transmission and that a small number of animals need to be infected chronically to ensure viral persistence. Transmission dynamics and viral persistence were best explained by the existence of both acutely and chronically infected individuals and by seasonally changing transmission rates. Due to the presence of chronically infected rodents, rodent control is unlikely to be a feasible approach for eliminating arenaviruses such as Lassa virus from Mastomys populations.

The shape of the contact-density function matters when modelling parasite transmission in fluctuating populations

Models of disease transmission in a population with changing densities must assume a relation between infectious contacts and density. Typically, a choice is made between a constant (frequency-dependence) and a linear (density-dependence) contact-density function, but it is becoming increasingly clear that intermediate, nonlinear functions are more realistic. It is currently not clear, however, what the exact consequences would be of different contact-density functions in fluctuating populations. By combining field data on rodent host (Mastomys natalensis) demography, experimentally derived contact-density data, and laboratory and field data on Morogoro virus infection dynamics, we explored the effects of different contact-density function shapes on transmission dynamics and invasion/persistence. While invasion and persistence were clearly affected by the shape of the function, the effects on outbreak characteristics such as infection prevalence and seroprevalence were less obvious. This means that it may be difficult to distinguish between the different shapes based on how well models fit to real data. The shape of the transmission-density function should therefore be chosen with care, and is ideally based on existing information such as a previously quantified contact- or transmission-density relationship or the underlying biology of the host species in relation to the infectious agent.

Arenavirus Dynamics in Experimentally and Naturally Infected Rodents

Infectious diseases of wildlife are typically studied using data on antibody and pathogen levels. In order to interpret these data, it is necessary to know the course of antibodies and pathogen levels after infection. Such data are typically collected using experimental infection studies in which host individuals are inoculated in the laboratory and sampled over an extended period, but because laboratory conditions are controlled and much less variable than natural conditions, the immune response and pathogen dynamics may differ. Here, we compared Morogoro arenavirus infection patterns between naturally and experimentally infected multimammate mice (Mastomys natalensis). Longitudinal samples were collected during three months of bi-weekly trapping in Morogoro, Tanzania, and antibody titer and viral RNA presence were determined. The time of infection was estimated from these data using a recently developed Bayesian approach, which allowed us to assess whether the natural temporal patterns match the previously observed patterns in the laboratory. A good match was found for 52% of naturally infected individuals, while most of the mismatches can be explained by the presence of chronically infected individuals (35%), maternal antibodies (10%), and an antibody detection limit (25%). These results suggest that while laboratory data are useful for interpreting field samples, there can still be differences due to conditions that were not tested in the laboratory.

Estimating Time of Infection Using Prior Serological and Individual Information Can Greatly Improve Incidence Estimation of Human and Wildlife Infections

Diseases of humans and wildlife are typically tracked and studied through incidence, the number of new infections per time unit. Estimating incidence is not without difficulties, as asymptomatic infections, low sampling intervals and low sample sizes can introduce large estimation errors. After infection, biomarkers such as antibodies or pathogens often change predictably over time, and this temporal pattern can contain information about the time since infection that could improve incidence estimation. Antibody level and avidity have been used to estimate time since infection and to recreate incidence, but the errors on these estimates using currently existing methods are generally large. Using a semi-parametric model in a Bayesian framework, we introduce a method that allows the use of multiple sources of information (such as antibody level, pathogen presence in different organs, individual age, season) for estimating individual time since infection. When sufficient background data are available, this method can greatly improve incidence estimation, which we show using arenavirus infection in multimammate mice as a test case. The method performs well, especially compared to the situation in which seroconversion events between sampling sessions are the main data source. The possibility to implement several sources of information allows the use of data that are in many cases already available, which means that existing incidence data can be improved without the need for additional sampling efforts or laboratory assays.

Spatial distribution patterns of plague hosts: point pattern analysis of the burrows of great gerbils in Kazakhstan

AIM

The spatial structure of a population can strongly influence the dynamics of infectious diseases, yet rarely is the underlying structure quantified. A case in point is plague, an infectious zoonotic disease caused by the bacterium Yersinia pestis. Plague dynamics within the Central Asian desert plague focus have been extensively modelled in recent years, but always with strong uniformity assumptions about the distribution of its primary reservoir host, the great gerbil (Rhombomys opimus). Yet, while clustering of this species' burrows due to social or ecological processes could have potentially significant effects on model outcomes, there is currently nothing known about the spatial distribution of inhabited burrows. Here, we address this knowledge gap by describing key aspects of the spatial patterns of great gerbil burrows in Kazakhstan.

LOCATION

Kazakhstan.

METHODS

Burrows were classified as either occupied or empty in 98 squares of four different sizes: 200 m (side length), 250 m, 500 m and 590-1020 m. We used Ripley's K statistic to determine whether and at what scale there was clustering of occupied burrows, and semi-variograms to quantify spatial patterns in occupied burrows at scales of 250 m to 9 km.

RESULTS

Significant spatial clustering of occupied burrows occurred in 25% and 75% of squares of 500 m and 590-1020 m, respectively, but not in smaller squares. In clustered squares, the clustering criterion peaked around 250 m. Semi-variograms showed that burrow density was auto-correlated up to a distance of 7 km and occupied density up to 2.5 km.

MAIN CONCLUSIONS

These results demonstrate that there is statistically significant spatial clustering of occupied burrows and that the uniformity assumptions of previous plague models should be reconsidered to assess its significance for plague transmission. This field evidence will allow for more realistic approaches to disease ecology models for both this system and for other structured host populations.

Plague epizootic cycles in Central Asia

Infection thresholds, widely used in disease epidemiology, may operate on host abundance and, if present, on vector abundance. For wildlife populations, host and vector abundances often vary greatly across years and consequently the threshold may be crossed regularly, both up- and downward. Moreover, vector and host abundances may be interdependent, which may affect the infection dynamics. Theory predicts that if the relevant abundance, or combination of abundances, is above the threshold, then the infection is able to spread; if not, it is bound to fade out. In practice, though, the observed level of infection may depend more on past than on current abundances. Here, we study the temporal dynamics of plague (Yersinia pestis infection), its vector (flea) and its host (great gerbil) in the PreBalkhash region in Kazakhstan. We describe how host and vector abundances interact over time and how this interaction drives the dynamics of the system around the infection threshold, consequently affecting the proportion of plague-infected sectors. We also explore the importance of the interplay between biological and detectability delays in generating the observed dynamics.

An investigation of matching symmetry in the human pinnae with possible implications for 3D ear recognition and sound localization

The human external ears, or pinnae, have an intriguing shape and, like most parts of the human external body, bilateral symmetry is observed between left and right. It is a well-known part of our auditory sensory system and mediates the spatial localization of incoming sounds in 3D from monaural cues due to its shape-specific filtering as well as binaural cues due to the paired bilateral locations of the left and right ears. Another less broadly appreciated aspect of the human pinna shape is its uniqueness from one individual to another, which is on the level of what is seen in fingerprints and facial features. This makes pinnae very useful in human identification, which is of great interest in biometrics and forensics. Anatomically, the type of symmetry observed is known as matching symmetry, with structures present as separate mirror copies on both sides of the body, and in this work we report the first such investigation of the human pinna in 3D. Within the framework of geometric morphometrics, we started by partitioning ear shape, represented in a spatially dense way, into patterns of symmetry and asymmetry, following a two-factor anova design. Matching symmetry was measured in all substructures of the pinna anatomy. However, substructures that 'stick out' such as the helix, tragus, and lobule also contained a fair degree of asymmetry. In contrast, substructures such as the conchae, antitragus, and antihelix expressed relatively stronger degrees of symmetric variation in relation to their levels of asymmetry. Insights gained from this study were injected into an accompanying identification setup exploiting matching symmetry where improved performance is demonstrated. Finally, possible implications of the results in the context of ear recognition as well as sound localization are discussed.

A novel method to reduce time investment when processing videos from camera trap studies

Camera traps have proven very useful in ecological, conservation and behavioral research. Camera traps non-invasively record presence and behavior of animals in their natural environment. Since the introduction of digital cameras, large amounts of data can be stored. Unfortunately, processing protocols did not evolve as fast as the technical capabilities of the cameras. We used camera traps to record videos of Eurasian beavers (Castor fiber). However, a large number of recordings did not contain the target species, but instead empty recordings or other species (together non-target recordings), making the removal of these recordings unacceptably time consuming. In this paper we propose a method to partially eliminate non-target recordings without having to watch the recordings, in order to reduce workload. Discrimination between recordings of target species and non-target recordings was based on detecting variation (changes in pixel values from frame to frame) in the recordings. Because of the size of the target species, we supposed that recordings with the target species contain on average much more movements than non-target recordings. Two different filter methods were tested and compared. We show that a partial discrimination can be made between target and non-target recordings based on variation in pixel values and that environmental conditions and filter methods influence the amount of non-target recordings that can be identified and discarded. By allowing a loss of 5% to 20% of recordings containing the target species, in ideal circumstances, 53% to 76% of non-target recordings can be identified and discarded. We conclude that adding an extra processing step in the camera trap protocol can result in large time savings. Since we are convinced that the use of camera traps will become increasingly important in the future, this filter method can benefit many researchers, using it in different contexts across the globe, on both videos and photographs.

An ideal-observer model of human sound localization

In recent years, a great deal of research within the field of sound localization has been aimed at finding the acoustic cues that human listeners use to localize sounds and understanding the mechanisms by which they process these cues. In this paper, we propose a complementary approach by constructing an ideal-observer model, by which we mean a model that performs optimal information processing within a Bayesian context. The model considers all available spatial information contained within the acoustic signals encoded by each ear. Parameters for the optimal Bayesian model are determined based on psychoacoustic discrimination experiments on interaural time difference and sound intensity. Without regard as to how the human auditory system actually processes information, we examine the best possible localization performance that could be achieved based only on analysis of the input information, given the constraints of the normal auditory system. We show that the model performance is generally in good agreement with the actual human localization performance, as assessed in a meta-analysis of many localization experiments (Best et al. in Principles and applications of spatial hearing, pp 14-23. World Scientific Publishing, Singapore, 2011). We believe this approach can shed new light on the optimality (or otherwise) of human sound localization, especially with regard to the level of uncertainty in the input information. Moreover, the proposed model allows one to study the relative importance of various (combinations of) acoustic cues for spatial localization and enables a prediction of which cues are most informative and therefore likely to be used by humans in various circumstances.

Density thresholds for Mopeia virus invasion and persistence in its host Mastomys natalensis

Well-established theoretical models predict host density thresholds for invasion and persistence of parasites with a density-dependent transmission. Studying such thresholds in reality, however, is not obvious because it requires long-term data for several fluctuating populations of different size. We developed a spatially explicit and individual-based SEIR model of Mopeia virus in multimammate mice Mastomys natalensis. This is an interesting model system for studying abundance thresholds because the host is the most common African rodent, populations fluctuate considerably and the virus is closely related to Lassa virus but non-pathogenic to humans so can be studied safely in the field. The simulations show that, while host density clearly is important, sharp thresholds are only to be expected for persistence (and not for invasion), since at short time-spans (as during invasion), stochasticity is determining. Besides host density, also the spatial extent of the host population is important. We observe the repeated local occurrence of herd immunity, leading to a decrease in transmission of the virus, while even a limited amount of dispersal can have a strong influence in spreading and re-igniting the transmission. The model is most sensitive to the duration of the infectious stage, the size of the home range and the transmission coefficient, so these are important factors to determine experimentally in the future.

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.

On population encoding and decoding of auditory information for bat echolocation

In this article, we study the neural encoding of acoustic information for FM-bats (such as Eptesicus fuscus) in simulation. In echolocation research, the frequency-time sound representation as expressed by the spectrogram is often considered as input. The rationale behind this is that a similar representation is present in the cochlea, i.e. the receptor potential of the inner hair cells (IHC) along the length of the cochlea, and hence similar acoustic information is relayed to the brain. In this article, we study to what extent the latter assumption is true. The receptor potential is converted into neural activity of the synapting auditory nerve cells (ANC), and information might be lost in this conversion process. Especially for FM-bats, this information transmission is not trivial: in contrast to other mammals, they detect short transient signals, and consequently neural activity can only be integrated over very limited time intervals. To quantify the amount of information transmitted we design a neural network-based algorithm to reconstruct the IHC receptor potentials from the spiking activity of the synapting auditory neurons. Both the receptor potential and the resulting neural activity are simulated using Meddis' peripheral model. Comparing the reconstruction to the IHC receptor potential, we quantify the information transmission of the bat hearing system and investigate how this depends on the intensity of the incoming signal, the distribution of auditory neurons, and previous masking stimulation (adaptation). In addition, we show how this approach allows to inspect which spectral features survive neural encoding and hence can be relevant for echolocation.

Simulated head related transfer function of the phyllostomid bat Phyllostomus discolor

This paper presents a calculation of the head related transfer function (HRTF) for the frontal hemisphere of the phyllostomid bat Phyllostomus discolor using an acoustic field simulation tool based on the boundary element method. From the calculated HRTF results, binaural interaural intensity differences (IIDs) are derived.

THE RESULTS

Region of highest sensitivity, HRTF patterns, and IID patterns are shown to be in good agreement with earlier experimental measurements on other specimens of the same bat species, i.e., the differences are within the interspecies variability range. Next, it is argued that the proposed simulation method offers distinct advantages over acoustic measurements on real bat specimens. To illustrate this, it is shown how computer manipulation of the virtual morphology model allows a more detailed comprehension of bat spatial hearing by investigating the effects of different head parts on the HRTF. From this analysis it is concluded that for this species the pinna has a significantly larger effect on the HRTF and IID patterns than the head itself. This conclusion argues in favor of a series of recent simulation studies based on pinna morphology only [R. Muller, J. Acoust. Soc. Am. 116, 3701-3712 (2004); Muller et al., ibid 119, 4083-4092 (2006)].