The impact of spike timing precision and spike emission reliability on decoding accuracy.

Precisely timed and reliably emitted spikes are hypothesized to serve multiple functions, including improving the accuracy and reproducibility of encoding stimuli, memories, or behaviours across trials. When these spikes occur as a repeating sequence, they can be used to encode and decode a potential time series. Here, we show both analytically and in simulations that the error incurred in approximating a time series with precisely timed and reliably emitted spikes decreases linearly with the number of neurons or spikes used in the decoding. This was verified numerically with synthetically generated patterns of spikes. Further, we found that if spikes were imprecise in their timing, or unreliable in their emission, the error incurred in decoding with these spikes would be sub-linear. However, if the spike precision or spike reliability increased with network size, the error incurred in decoding a time-series with sequences of spikes would maintain a linear decrease with network size. The spike precision had to increase linearly with network size, while the probability of spike failure had to decrease with the square-root of the network size. Finally, we identified a candidate circuit to test this scaling relationship: the repeating sequences of spikes with sub-millisecond precision in area HVC (proper name) of the zebra finch. This scaling relationship can be tested using both neural data and song-spectrogram-based recordings while taking advantage of the natural fluctuation in HVC network size due to neurogenesis.

Multimodal communication and audience directedness in the greeting behaviour of semi-captive African savannah elephants.

Many species communicate by combining signals into multimodal combinations. Elephants live in multi-level societies where individuals regularly separate and reunite. Upon reunion, elephants often engage in elaborate greeting rituals, where they use vocalisations and body acts produced with different body parts and of various sensory modalities (e.g., audible, tactile). However, whether these body acts represent communicative gestures and whether elephants combine vocalisations and gestures during greeting is still unknown. Here we use separation-reunion events to explore the greeting behaviour of semi-captive elephants (Loxodonta africana). We investigate whether elephants use silent-visual, audible, and tactile gestures directing them at their audience based on their state of visual attention and how they combine these gestures with vocalisations during greeting. We show that elephants select gesture modality appropriately according to their audience's visual attention, suggesting evidence of first-order intentional communicative use. We further show that elephants integrate vocalisations and gestures into different combinations and orders. The most frequent combination consists of rumble vocalisations with ear-flapping gestures, used most often between females. By showing that a species evolutionarily distant to our own primate lineage shows sensitivity to their audience's visual attention in their gesturing and combines gestures with vocalisations, our study advances our understanding of the emergence of first-order intentionality and multimodal communication across taxa.

Contextual and combinatorial structure in sperm whale vocalisations.

Sperm whales (Physeter macrocephalus) are highly social mammals that communicate using sequences of clicks called codas. While a subset of codas have been shown to encode information about caller identity, almost everything else about the sperm whale communication system, including its structure and information-carrying capacity, remains unknown. We show that codas exhibit contextual and combinatorial structure. First, we report previously undescribed features of codas that are sensitive to the conversational context in which they occur, and systematically controlled and imitated across whales. We call these rubato and ornamentation. Second, we show that codas form a combinatorial coding system in which rubato and ornamentation combine with two context-independent features we call rhythm and tempo to produce a large inventory of distinguishable codas. Sperm whale vocalisations are more expressive and structured than previously believed, and built from a repertoire comprising nearly an order of magnitude more distinguishable codas. These results show context-sensitive and combinatorial vocalisation can appear in organisms with divergent evolutionary lineage and vocal apparatus.

Long-term, medium-term and acute stress response of urban populations of Eurasian red squirrels affected by different levels of human disturbance.

Animals in urban areas often encounter novel and potentially stressful conditions. It is important to understand how wildlife cope with anthropogenic disturbance. To investigate this specific adaptation we live-trapped squirrels in two study sites in Warsaw: a forest reserve and an urban park and we estimated stress responses at three levels: long-term and medium-term stress (the level of stress hormones, i.e. cortisol and cortisone concentrations, in hair and feces) and acute reaction to human-induced stress (measured during handling with the aid of the three indices: breath rate, struggle rate, and vocalization). According to GLMM models no difference in the stress hormones level was found between the two populations. The only differences in cortisol concentrations clearly depended on the season, i.e. being higher in autumn and winter comparying to other seasons. There was no influence of sex, or reproductive status on stress hormones. Forest squirrels had significantly higher breath rates, suggesting they were more stressed by handling. There was no difference in the struggle rate between study areas, this index was mostly affected by season (i.e. being highest in winter). First-trapped squirrels vocalized less than during the subsequent trappings. Assumingly, during the first, and more stressful trapping, squirrels used 'freezing' and/or little vocalization, while during next captures they used alarm calls to warn conspecifics. Overall, we showed that the two squirrel populations differed only in terms of their breath rate. This suggests that they did not differ in medium-term and long-term stress in general, but they can differ in acute response to handling. This also suggests that both populations were similarly affected by environmental factors. The lack of clear effects may also be due to population heterogeneity. Thus, in order to assess the effects of anthropogenic stressors a broader range of indicators and diverse analytical methods, including behavioral analyses, should be employed.

Hydroacoustic study of fin whales around the Southern Wake Island: Type, vocal behavior, and temporal evolution from 2010 to 2022.

The progress of fin whale study is hindered by the debate about whether the two typical type-A and type-B calls (characterized by central source frequencies of 17-20 Hz and 20-30 Hz, respectively) originate from a single fin whale or two individual fin whales. Here, hydroacoustic data is employed to study the type, vocal behavior, and temporal evolution of fin whale calls around the Southern Wake Island from 2010 to 2022. It is identified that (1) type-A and type-B calls come from two individuals based on the large source separation of the two calls through high-precision determination of source location; (2) type-A fin whales exhibit vocal influence on type-B fin whales, where type-B fin whales become paired with type-A calls and vocalize regularly when type-A fin whales appear, and type-A fin whales always lead the call sequences; and (3) some type-A fin whales stop calling when another type-A fin whale approaches at a distance of about 1.6 km. During 2010-2022, type-A calls occur every year, whereas type-B calls are prevalent only after November 2018. A culture transmission is proposed from type-A fin whales to type-B fin whales and/or a population increase of type-B fin whales in the region after November 2018.

Extensive data engineering to the rescue: building a multi-species katydid detector from unbalanced, atypical training datasets.

Passive acoustic monitoring (PAM) is a powerful tool for studying ecosystems. However, its effective application in tropical environments, particularly for insects, poses distinct challenges. Neotropical katydids produce complex species-specific calls, spanning mere milliseconds to seconds and spread across broad audible and ultrasonic frequencies. However, subtle differences in inter-pulse intervals or central frequencies are often the only discriminatory traits. These extremities, coupled with low source levels and susceptibility to masking by ambient noise, challenge species identification in PAM recordings. This study aimed to develop a deep learning-based solution to automate the recognition of 31 katydid species of interest in a biodiverse Panamanian forest with over 80 katydid species. Besides the innate challenges, our efforts were also encumbered by a limited and imbalanced initial training dataset comprising domain-mismatched recordings. To overcome these, we applied rigorous data engineering, improving input variance through controlled playback re-recordings and by employing physics-based data augmentation techniques, and tuning signal-processing, model and training parameters to produce a custom well-fit solution. Methods developed here are incorporated into Koogu, an open-source Python-based toolbox for developing deep learning-based bioacoustic analysis solutions. The parametric implementations offer a valuable resource, enhancing the capabilities of PAM for studying insects in tropical ecosystems. This article is part of the theme issue 'Towards a toolkit for global insect biodiversity monitoring'.

Time and habitat structure shape insect acoustic activity in the Amazon.

Insects are the most diverse animal taxon on Earth and play a key role in ecosystem functioning. However, they are often neglected by ecological surveys owing to the difficulties involved in monitoring this small and hyper-diverse taxon. With technological advances in biomonitoring and analytical methods, these shortcomings may finally be addressed. Here, we performed passive acoustic monitoring at 141 sites (eight habitats) to investigate insect acoustic activity in the Viruá National Park, Brazil. We first describe the frequency range occupied by three soniferous insect groups (cicadas, crickets and katydids) to calculate the acoustic evenness index (AEI). Then, we assess how AEI varies spatially and temporally among habitat types, and finally we investigate the relationship between vegetation structure variables and AEI for each insect category. Overall, crickets occupied lower and narrower frequency bands than cicadas and katydids. AEI values varied among insect categories and across space and time. The highest acoustic activity occurred before sunrise and the lowest acoustic activity was recorded in pastures. Canopy cover was positively associated with cricket acoustic activity but not with katydids. Our findings contribute to a better understanding of the role of time, habitat and vegetation structure in shaping insect activity within diverse Amazonian ecosystems. This article is part of the theme issue 'Towards a toolkit for global insect biodiversity monitoring'.

Towards acoustic monitoring of bees: wingbeat sounds are related to species and individual traits.

Global pollinator decline urgently requires effective methods to assess their trends, distribution and behaviour. Passive acoustics is a non-invasive and cost-efficient monitoring tool increasingly employed for monitoring animal communities. However, insect sounds remain highly unexplored, hindering the application of this technique for pollinators. To overcome this shortfall and support future developments, we recorded and characterized wingbeat sounds of a variety of Iberian domestic and wild bees and tested their relationship with taxonomic, morphological, behavioural and environmental traits at inter- and intra-specific levels. Using directional microphones and machine learning, we shed light on the acoustic signature of bee wingbeat sounds and their potential to be used for species identification and monitoring. Our results revealed that frequency of wingbeat sounds is negatively related with body size and environmental temperature (between-species analysis), while it is positively related with experimentally induced stress conditions (within-individual analysis). We also found a characteristic acoustic signature in the European honeybee that supported automated classification of this bee from a pool of wild bees, paving the way for passive acoustic monitoring of pollinators. Overall, these findings confirm that insect sounds during flight activity can provide insights on individual and species traits, and hence suggest novel and promising applications for this endangered animal group. This article is part of the theme issue 'Towards a toolkit for global insect biodiversity monitoring'.

Multi-year soundscape recordings and automated call detection reveals varied impact of moonlight on calling activity of neotropical forest katydids.

Night-time light can have profound ecological effects, even when the source is natural moonlight. The impacts of light can, however, vary substantially by taxon, habitat and geographical region. We used a custom machine learning model built with the Python package Koogu to investigate the in situ effects of moonlight on the calling activity of neotropical forest katydids over multiple years. We prioritised species with calls that were commonly detected in human annotated data, enabling us to evaluate model performance. We focused on eight species of katydids that the model identified with high precision (generally greater than 0.90) and moderate-to-high recall (minimum 0.35), ensuring that detections were generally correct and that many calls were detected. These results suggest that moonlight has modest effects on the amount of calling, with the magnitude and direction of effect varying by species: half of the species showed positive effects of light and half showed negative. These findings emphasize the importance of understanding natural history for anticipating how biological communities respond to moonlight. The methods applied in this project highlight the emerging opportunities for evaluating large quantities of data with machine learning models to address ecological questions over space and time. This article is part of the theme issue 'Towards a toolkit for global insect biodiversity monitoring'.

Bat2Web: A Framework for Real-Time Classification of Bat Species Echolocation Signals Using Audio Sensor Data.

Bats play a pivotal role in maintaining ecological balance, and studying their behaviors offers vital insights into environmental health and aids in conservation efforts. Determining the presence of various bat species in an environment is essential for many bat studies. Specialized audio sensors can be used to record bat echolocation calls that can then be used to identify bat species. However, the complexity of bat calls presents a significant challenge, necessitating expert analysis and extensive time for accurate interpretation. Recent advances in neural networks can help identify bat species automatically from their echolocation calls. Such neural networks can be integrated into a complete end-to-end system that leverages recent internet of things (IoT) technologies with long-range, low-powered communication protocols to implement automated acoustical monitoring. This paper presents the design and implementation of such a system that uses a tiny neural network for interpreting sensor data derived from bat echolocation signals. A highly compact convolutional neural network (CNN) model was developed that demonstrated excellent performance in bat species identification, achieving an F1-score of 0.9578 and an accuracy rate of 97.5%. The neural network was deployed, and its performance was evaluated on various alternative edge devices, including the NVIDIA Jetson Nano and Google Coral.

What's special about human speech? A student exercise for comparing speech production between humans and chimpanzees.

Modern humans and chimpanzees share a common ancestor on the phylogenetic tree, yet chimpanzees do not spontaneously produce speech or speech sounds. The lab exercise presented in this paper was developed for undergraduate students in a course entitled "What's Special About Human Speech?" The exercise is based on acoustic analyses of the words "cup" and "papa" as spoken by Viki, a home-raised, speech-trained chimpanzee, as well as the words spoken by a human. The analyses allow students to relate differences in articulation and vocal abilities between Viki and humans to the known anatomical differences in their vocal systems. Anatomical and articulation differences between humans and Viki include (1) potential tongue movements, (2) presence or absence of laryngeal air sacs, (3) presence or absence of vocal membranes, and (4) exhalation vs inhalation during production.

The domestication of the larynx: The neural crest connection.

Wolves howl and dogs bark, both are able to produce variants of either vocalization, but we see a distinct difference in usage between wild and domesticate. Other domesticates also show distinct changes to their vocal output: domestic cats retain meows, a distinctly subadult trait in wildcats. Such differences in acoustic output are well-known, but the causal mechanisms remain little-studied. Potential links between domestication and vocal output are intriguing for multiple reasons, and offer a unique opportunity to explore a prominent hypothesis in domestication research: the neural crest/domestication syndrome hypothesis. This hypothesis suggests that in the early stages of domestication, selection for tame individuals decreased neural crest cell (NCCs) proliferation and migration, which led to a downregulation of the sympathetic arousal system, and hence reduced fear and reactive aggression. NCCs are a transitory stem cell population crucial during embryonic development that tie to diverse tissue types and organ systems. One of these neural-crest derived systems is the larynx, the main vocal source in mammals. We argue that this connection between NCCs and the larynx provides a powerful test of the predictions of the neural crest/domestication syndrome hypothesis, discriminating its predictions from those of other current hypotheses concerning domestication.

Hearing and vocalizations in a small songbird, the red-cheeked cordon bleu (Uraeginthus bengalus) (L).

The auditory sensitivity of a small songbird, the red-cheeked cordon bleu, was measured using the standard methods of animal psychophysics. Hearing in cordon bleus is similar to other small passerines with best hearing in the frequency region from 2 to 4 kHz and sensitivity declining at the rate of about 10 dB/octave below 2 kHz and about 35 dB/octave as frequency increases from 4 to 9 kHz. While critical ratios are similar to other songbirds, the long-term average power spectrum of cordon bleu song falls above the frequency of best hearing in this species.

A genomic basis of vocal rhythm in birds.

Vocal rhythm plays a fundamental role in sexual selection and species recognition in birds, but little is known of its genetic basis due to the confounding effect of vocal learning in model systems. Uncovering its genetic basis could facilitate identifying genes potentially important in speciation. Here we investigate the genomic underpinnings of rhythm in vocal non-learning Pogoniulus tinkerbirds using 135 individual whole genomes distributed across a southern African hybrid zone. We find rhythm speed is associated with two genes that are also known to affect human speech, Neurexin-1 and Coenzyme Q8A. Models leveraging ancestry reveal these candidate loci also impact rhythmic stability, a trait linked with motor performance which is an indicator of quality. Character displacement in rhythmic stability suggests possible reinforcement against hybridization, supported by evidence of asymmetric assortative mating in the species producing faster, more stable rhythms. Because rhythm is omnipresent in animal communication, candidate genes identified here may shape vocal rhythm across birds and other vertebrates.

Urbanization alters the song propagation of two human-commensal songbird species.

Urban expansion has increased pollution, including both physical (e.g., exhaust, litter) and sensory (e.g., anthropogenic noise) components. Urban avian species tend to increase the frequency and/or amplitude of songs to reduce masking by low-frequency noise. Nevertheless, song propagation to the receiver can also be constrained by the environment. We know relatively little about how this propagation may be altered across species that (1) vary in song complexity and (2) inhabit areas along an urbanization gradient. We investigated differences in song amplitude, attenuation, and active space, or the maximum distance a receiver can detect a signal, in two human-commensal species: the house sparrow (Passer domesticus) and house finch (Haemorhous mexicanus). We described urbanization both discretely and quantitatively to investigate the habitat characteristics most responsible for propagation changes. We found mixed support for our hypothesis of urban-specific degradation of songs. Urban songs propagated with higher amplitude; however, urban song fidelity was species-specific and showed lowered active space for urban house finch songs. Taken together, our results suggest that urban environments may constrain the propagation of vocal signals in species-specific manners. Ultimately, this has implications for the ability of urban birds to communicate with potential mates or kin.

Vocal signatures affected by population identity and environmental sound levels.

Passive acoustic monitoring has improved our understanding of vocalizing organisms in remote habitats and during all weather conditions. Many vocally active species are highly mobile, and their populations overlap. However, distinct vocalizations allow the tracking and discrimination of individuals or populations. Using signature whistles, the individually distinct calls of bottlenose dolphins, we calculated a minimum abundance of individuals, characterized and compared signature whistles from five locations, and determined reoccurrences of individuals throughout the Mid-Atlantic Bight and Chesapeake Bay, USA. We identified 1,888 signature whistles in which the duration, number of extrema, start, end, and minimum frequencies of signature whistles varied significantly by site. All characteristics of signature whistles were deemed important for determining from which site the whistle originated and due to the distinct signature whistle characteristics and lack of spatial mixing of the dolphins detected at the Offshore site, we suspect that these dolphins are of a different population than those at the Coastal and Bay sites. Signature whistles were also found to be shorter when sound levels were higher. Using only the passively recorded vocalizations of this marine top predator, we obtained information about its population and how it is affected by ambient sound levels, which will increase as offshore wind energy is developed. In this rapidly developing area, these calls offer critical management insights for this protected species.

Common dolphin whistle responses to experimental mid-frequency sonar.

Oceanic delphinids that occur in and around Navy operational areas are regularly exposed to intense military sonar broadcast within the frequency range of their hearing. However, empirically measuring the impact of sonar on the behavior of highly social, free-ranging dolphins is challenging. Additionally, baseline variability or the frequency of vocal state-switching among social oceanic dolphins during undisturbed conditions is lacking, making it difficult to attribute changes in vocal behavior to anthropogenic disturbance. Using a network of drifting acoustic buoys in controlled exposure experiments, we investigated the effects of mid-frequency (3-4 kHz) active sonar (MFAS) on whistle production in short-beaked (Delphinus delphis delphis) and long-beaked common dolphins (Delphinus delphis bairdii) in southern California. Given the complexity of acoustic behavior exhibited by these group-living animals, we conducted our response analysis over varying temporal windows (10 min- 5 s) to describe both longer-term and instantaneous changes in sound production. We found that common dolphins exhibited acute and pronounced changes in whistle rate in the 5 s following exposure to simulated Navy MFAS. This response was sustained throughout sequential MFAS exposures within experiments simulating operational conditions, suggesting that dolphins may not habituate to this disturbance. These results indicate that common dolphins exhibit brief yet clearly detectable acoustic responses to MFAS. They also highlight how variable temporal analysis windows-tuned to key aspects of baseline vocal behavior as well as experimental parameters related to MFAS exposure-enable the detection of behavioral responses. We suggest future work with oceanic delphinids explore baseline vocal rates a-priori and use information on the rate of change in vocal behavior to inform the analysis time window over which behavioral responses are measured.

Multiple processes of vocal sensory-motor interaction in primate auditory cortex.

Sensory-motor interactions in the auditory system play an important role in vocal self-monitoring and control. These result from top-down corollary discharges, relaying predictions about vocal timing and acoustics. Recent evidence suggests such signals may be two distinct processes, one suppressing neural activity during vocalization and another enhancing sensitivity to sensory feedback, rather than a single mechanism. Single-neuron recordings have been unable to disambiguate due to overlap of motor signals with sensory inputs. Here, we sought to disentangle these processes in marmoset auditory cortex during production of multi-phrased 'twitter' vocalizations. Temporal responses revealed two timescales of vocal suppression: temporally-precise phasic suppression during phrases and sustained tonic suppression. Both components were present within individual neurons, however, phasic suppression presented broadly regardless of frequency tuning (gating), while tonic was selective for vocal frequencies and feedback (prediction). This suggests that auditory cortex is modulated by concurrent corollary discharges during vocalization, with different computational mechanisms.

Aquatic Soundscape Recordings Reveal Diverse Vocalizations and Nocturnal Activity of an Endangered Frog.

AbstractAutonomous sensors provide opportunities to observe organisms across spatial and temporal scales that humans cannot directly observe. By processing large data streams from autonomous sensors with deep learning methods, researchers can make novel and important natural history discoveries. In this study, we combine automated acoustic monitoring with deep learning models to observe breeding-associated activity in the endangered Sierra Nevada yellow-legged frog (Rana sierrae), a behavior that current surveys do not measure. By deploying inexpensive hydrophones and developing a deep learning model to recognize breeding-associated vocalizations, we discover three undocumented R. sierrae vocalization types and find an unexpected temporal pattern of nocturnal breeding-associated vocal activity. This study exemplifies how the combination of autonomous sensor data and deep learning can shed new light on species' natural history, especially during times or in locations where human observation is limited or impossible.