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101 results for “Echolocation”
Echolocation call parameters of Daubenton's bats during exposure to masking noise
<p>Echolocating bats hunt prey on the wing under conditions of poor lighting by emission of loud calls and subsequent auditory processing of weak returning echoes. To do so, they need adequate echo-to-noise ratios (ENRs) to detect and distinguish target echoes from masking noise. Early obstacle avoidance experiments report high resilience to masking in free-flying bats, but whether this is due to spectral or spatiotemporal release from masking, advanced auditory signal detection or an increase in call amplitude (Lombard effect) remains unresolved. We hypothesized that bats with no spectral, spatial or temporal release from masking noise, defend a certain ENR via a Lombard effect. We trained four bats (<em>Myotis daubentonii</em>) to approach and land on a target that broadcasted broadband noise at four different levels. An array of seven microphones enabled acoustic localization of the bats and source level estimation of their approach calls. Call duration and peak frequency did not change, but average call source levels (SL<sub>RMS</sub>, at 0.1 m as dB re. 20 μPa, root-mean-square) increased, from 112 dB in the no-noise treatment, to 118 dB (maximum 129 dB) at the maximum noise level of 94 dB. The magnitude of the Lombard effect was small (0.13 dB SL<sub>RMS</sub>/dB of noise), resulting in mean broadband and narrowband ENRs of -11 and 8 dB respectively at the highest noise level. Despite these poor ENRs, the bats still performed echo-guided landings, making us conclude that they are very resilient to masking even when they cannot avoid it spectrally, spatially or temporally.</p>
Fig. 3 in New record of Rhinolophus chiewkweeae (Chiroptera: Rhinolophidae) from the east coast of Peninsular Malaysia with new information on their echolocation calls, genetics and their taxonomy
Fig. 3. Phylogenetic tree of selected Rhinolophus, Hipposideros and Coelops (Kimura-2-parameter model)
Fig. 2 in New record of Rhinolophus chiewkweeae (Chiroptera: Rhinolophidae) from the east coast of Peninsular Malaysia with new information on their echolocation calls, genetics and their taxonomy
Fig. 2. Inset map highlighted in grey shows the Malaysian country boundary. Area coloured in grey with vertical diagonal lines highlight Peninsular Malaysia whereas area coloured in grey without the lines highlight Malaysian Borneo. Larger map of Peninsular Malaysia on the right shows the collection sites of Rhinolophus chiewkweeae. 1=Lubok Semilan, Kedah; 2=Wang Kelian State Park, Perlis; 3=Weng Subcatchment Area, Kedah; 4=Asahan Forest Reserve, Melaka; 5=Gunung Ledang, Johor; 6=Labis Forest Reserve, Johor; 7=Sungai Buweh, Terengganu (This study).
Fig. 5 in New record of Rhinolophus chiewkweeae (Chiroptera: Rhinolophidae) from the east coast of Peninsular Malaysia with new information on their echolocation calls, genetics and their taxonomy
Fig. 5. The echolocation call of Rhinolophus chiewkweeae. Legend: H 1 (first harmonic), H2 (second harmonic), H3 (third harmonic) and H4 (fourth harmonic).
Fig. 4 in New record of Rhinolophus chiewkweeae (Chiroptera: Rhinolophidae) from the east coast of Peninsular Malaysia with new information on their echolocation calls, genetics and their taxonomy
Fig. 4. Lateral, dorsal and ventral views of Rhinolophus chiewkweeae skull from Sungai Buweh, Lawit. Scale bar = 5mm
Fig. 1. Cytochrome-b in Extensive diversification across islands in the echolocating Aerodramus swiftlets
Fig. 1. Cytochrome-b maximum-likelihood tree topology. Branch support is given as Bayesian posterior probability (multiplied by 100 for ease of reading) / Maximum Likelihood bootstrap / Maximum Parsimony bootstrap. Only posterior probabilities>75 and bootstrap values>65 are given. Asterisk refers to a specimen of A. fuciphagus vestitus which possesses an introgressed mtDNA haplotype from A. salangana natunae (see text).
Echolocating toothed whales use ultra-fast echo-kinetic responses to track evasive prey
<p>Visual predators rely on fast-acting optokinetic responses to track and capture agile prey. Most toothed whales, however, rely on echolocation for hunting and have converged on biosonar clicking rates reaching 500/s during prey pu rsuits. If echoes are processed on a click by click basis, as assumed, neural responses 100x faster than those in vision are required to keep pace with this information flow. Using high resolution bio-logging of wild predator prey interactions we show that toothed whales adjust clicking rates to track prey movement within 50 200 ms of prey escape responses. Hypothesising that these stereotyped biosonar adjustments are elicited by sudden prey accelerations, we measured echo kinetic responses from trained harb our porpoises to a moving target and found similar latencies. High biosonar sampling rates are, therefore, not supported by extreme speeds of neural processing and muscular responses. Instead, the neuro kinetic response times in echolocation are similar to those of tracking responses in vision, suggesting a common neural underpinning.</p>
Hourly detections of echolocation clicks in Hawaiian Island HARP data from Hawai`i, Kaua`i, and Manawai with species labels
<p>This dataset consists of counts of detections of echolocation clicks at three sites in the Hawaiian Islands Archipelago. These sites are Hawaii, Kauai, and Manawai (also known as Pearl and Hermes Reef). Echolocation clicks have been labeled using a neural network classifier that was trained and tested on data from the Hawaiian Islands and can successfully identify many species of regionally present odontocetes. During the labeling process, clicks were grouped into one-minute bins and each bin was given a species' label. The data provided here is further binned at an hourly level, where counts of a given species represent the number of one-minute bins within a given hour that were labeled as that species (up to a maximum of 60). One file is provided per site, and files are in .csv format that can be read using any desired coding language.<span> </span></p>
Data from: Narwhal (Monodon monoceros) echolocation click rates to support cue counting passive acoustic density estimation
<p class="MsoNormal"><span>The datasets correspond to the data used to obtain the results shown in the manuscript "Narwhal (<em>Monodon monoceros</em>) echolocation click rates to support cue counting passive acoustic density estimation".</span></p> <p class="MsoNormal"><span>When the manuscript is accepted we will also edit and add here the full reference including the DOI of the publication.</span></p>
HARP North Atlantic beaked whales: Echolocation click collection for machine learning
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Echolocating toothed whales use ultra-fast echo-kinetic responses to track evasive prey
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Echolocation call parameters of Daubenton's bats during exposure to masking noise
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Hourly detections of echolocation clicks in Hawaiian Island HARP data from Hawai`i, Kaua`i, and Manawai with species labels
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Data from: Narwhal (Monodon monoceros) echolocation click rates to support cue counting passive acoustic density estimation
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The SONOZOTZ project: assembling an echolocation calls library for bats in a megadiverse country
<p><span><span><span><span><span><span><span><span><span><span><span>Bat acoustic libraries are important tools that assemble echolocation calls to allow the comparison and discrimination to confirm species identifications. The Sonozotz project represents the first nation-wide library of bat echolocation calls for a megadiverse country. It was assembled following a standardized recording protocol that aimed to cover different recording habitats, recording techniques, and call variation inherent to individuals. The Sonozotz project included 69 species of echolocating bats, a high species richness that represents 50% of bat species found in the country. We include recommendations on how the database can be used and how the sampling methods can be potentially replicated in countries with similar environmental and geographic conditions. To our knowledge, this represents the most exhaustive effort to date to document and compile the diversity of bat echolocation calls for a megadiverse country. This database will be useful to address a range of ecological questions including the effects of anthropogenic activities on bat communities through the analysis of bat sound.</span></span></span></span></span></span></span></span></span></span></span></p>
Dataset accompanying: Echolocation click parameters and biosonar behaviour of the dwarf sperm whale (Kogia sima)
<p>This dataset accompanies the manuscript "Echolocation click parameters and biosonar behaviour of the dwarf sperm whale (<em>Kogia sima</em>)." All source parameters of on-axis clicks are available in MATLAB files, for both the deep water (n=46) and shallow harbour (n=870) datasets. The deep water dataset was collected using a 7-channel vertical hydrophone array in the Bahamas, and the shallow harbour dataset was collected using a single-channel recorder in South Africa. Metadeta explaining the variables are found within the MATLAB files under 'Comments'. Details on data collection, curation and analysis can be found in the Malinka et al., Kogia publication (https://jeb.biologists.org/content/224/6/jeb240689).</p> <p>For comments/questions, please contact chloe.e.malinka [at] bio.au.dk</p>
Data from: Retinotopic-like maps of spatial sound in primary 'visual' cortex of blind human echolocators
The functional specialisations of cortical sensory areas were traditionally viewed as being tied to specific modalities. A radically different emerging view is that the brain is organized by task rather than sensory modality, but it has not yet been shown that this applies to primary sensory cortices. Here we report such evidence by showing that primary 'visual' cortex can be adapted to map spatial locations of sound in blind humans who regularly perceive space through sound echoes. Specifically, we objectively quantify the similarity between measured stimulus maps for sound eccentricity and predicted stimulus maps for visual eccentricity in primary 'visual' cortex (using a probabilistic atlas based on cortical anatomy) to find that stimulus maps for sound in expert echolocators are directly comparable to those for vision in sighted people. Furthermore, the degree of this similarity is positively related with echolocation ability. We also rule out explanations based on top-down modulation of brain activity – e.g. through imagery. This result is clear evidence that task-specific organization can extend even to primary sensory cortices, and in this way is pivotal in our reinterpretation of the functional organisation of the human brain.
Data from: Evolution of cranial telescoping in echolocating whales (Cetacea: Odontoceti)
Odontocete (echolocating whale) skulls exhibit extreme posterior displacement and overlapping of facial bones, here referred to as retrograde cranial telescoping. To examine retrograde cranial telescoping across 40 million years of whale evolution, we collected 3D scans of whale skulls spanning odontocete evolution. We used a sliding semilandmark morphometric approach with Procrustes superimposition and PCA to capture and describe the morphological variation present in the facial region, followed by Ancestral Character State Reconstruction (ACSR) and evolutionary model fitting on significant components to determine how retrograde cranial telescoping evolved. The first PC score explains the majority of variation associated with telescoping and reflects the posterior migration of the external nares and premaxilla alongside expansion of the maxilla and frontal. The earliest diverging fossil odontocetes were found to exhibit a lesser degree of cranial telescoping than later diverging but contemporary whale taxa. Major shifts in PC scores and centroid size are identified at the base of Odontoceti, and early burst and punctuated equilibrium models best fit the evolution of retrograde telescoping. This indicates that the Oligocene was a period of unusually high diversity and evolution in whale skull morphology, with little subsequent evolution in telescoping.
Data from: Inconspicuous echolocation in hoary bats (Lasiurus cinereus)
Echolocation allows bats to occupy diverse nocturnal niches. Bats almost always use echolocation, even when other sensory stimuli are available to guide navigation. Here, using arrays of calibrated infrared cameras and ultrasonic microphones, we demonstrate that hoary bats (Lasiurus cinereus) use previously unknown echolocation behaviors that challenge our current understanding of echolocation. We describe a novel call type ("micro" calls) that has three orders of magnitude less sound energy than other bat calls used in open habitats. We also document bats flying close to microphones (< 3 m) without producing detectable echolocation calls. Acoustic modeling indicates that bats are not producing calls that exceed 70-75 dB at 0.1 m, a level that would have little or no known use for a bat flying in the open at speeds exceeding 7 m s-1. This indicates that hoary bats sometimes fly without echolocation. We speculate that bats reduce echolocation output to avoid eavesdropping by conspecifics during the mating season. These findings might partly explain why tens of thousands of hoary bats are killed at wind turbines each year. They also challenge the long-standing assumption that bats—model organisms for sensory specialization—are reliant on sonar for nocturnal navigation.
Echolocation clicks and anthropogenic detections with neural network labels in Hawaiian Island HARP data from Kona, Kaua`i, and Pearl and Hermes Reef
<p><span>This dataset consists of echolocation clicks and detections of anthropogenic signals at three sites in the Hawaiian Islands Archipelago. These sites are </span><span>Hawaii/Hawaii_K, </span><span>Kauai/KA, and </span><span>Pearl and Hermes Reef/PHR. </span><span>Echolocation clicks were grouped into 5 minute bins, for which summary data is provided. Files are in .mat format that can be read using any desired coding language using a netcdf reading script. Files are separated by site, deployment, and neural network class (i.e. sitedeployment_cbins_class or site_deployment_cbins_class). Manual labels are provided.</span></p>
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Allen Brain Atlas
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DANDI Archive for NWB datasets
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International Brain Laboratory public data
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OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.