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693 results for “vocalizations”
Data from: Vocal and locomotor coordination develops in association with the autonomic nervous system
In adult animals, movement and vocalizations are coordinated, sometimes facilitating, and at other times inhibiting, each other. What is missing is how these different domains of motor control become coordinated over the course of development. We investigated how postural-locomotor behaviors may influence vocal development, and the role played by physiological arousal during their interactions. Using infant marmoset monkeys, we densely sampled vocal, postural and locomotor behaviors and estimated arousal fluctuations from electrocardiographic measures of heart rate. We found that vocalizations matured sooner than postural and locomotor skills, and that vocal-locomotor coordination improved with age and during elevated arousal levels. These results suggest that postural-locomotor maturity is not required for vocal development to occur, and that infants gradually improve coordination between vocalizations and body movement through a process that may be facilitated by arousal level changes.
Data from: Vocal networks remain stable after a disturbance in Emei music frogs
Social network analysis has been widely used to investigate the dynamics of social interactions and the evolution of social complexity across a range of taxa. Anuran species are highly dependent on vocal communication in mate choice; however, these species have rarely been the subject of social network analysis. The present study used social network analysis to investigate whether vocal network structures are consistent in Emei music frog (Babina daunchina) after the introduction of a simulated exotic rival of varying competitiveness into the social group. We broadcasted six categories of artificial calls (either highly sexually attractive calls produced from inside male nests or calls of low sexual attractiveness produced outside nests with three, five or seven notes, respectively) to simulate an intruder with different levels of competitiveness. We then constructed vocal networks for two time periods (before and after the disturbance) and quantified three network metrics (strength, closeness and betweenness) that measure different aspects of individual-level position. We used the mean values of these network metrics to evaluate group-level changes in network structure. We found that the mean strength, mean closeness and mean betweenness were consistent between two time periods in all ponds, despite the fact that the positions of some individuals had changed markedly after disturbance. In addition, there was no significant interaction effect between period and numbers of notes on the three network metrics. These finding suggest that the structure of vocal networks in Emei music frogs remain stable at the group level after a conspecific disturbance, regardless of the intruder's competitiveness.
Dataset: Vocal complexity in the long calls of Bornean orangutans
<div> <p>Data and code used for PeerJ article titled, "Vocal complexity in the long calls of Bornean orangutans"</p> <p> </p> <p><strong>Abstract</strong></p> <p>Vocal complexity is central to many evolutionary hypotheses about animal communication. Yet, quantifying and comparing complexity remains a challenge, particularly when vocal types are highly graded. Male Bornean orangutans (Pongo pygmaeus wurmbii) produce complex and variable “long call” vocalizations comprising multiple sound types that vary within and among individuals. Previous studies described six distinct call (or pulse) types within these complex vocalizations, but none quantified their discreteness or the ability of human observers to reliably classify them. We studied the long calls of 13 individuals to: 1) evaluate and quantify the reliability of audio-visual classification by three well-trained observers, 2) distinguish among call types using supervised classification and unsupervised clustering, and 3) compare the performance of different feature sets. Using 46 acoustic features, we used machine learning (i.e., support vector machines, affinity propagation, and fuzzy c-means) to identify call types and assess their discreteness. We also additionally used Uniform Manifold Approximation and Projection (UMAP) to visualize the separation of pulses using both extracted features and spectrogram representations. We found low inter-observer reliability and poor classification accuracy using Ssupervised approaches, showed low inter-observer reliability and poor classification accuracy, indicating that pulse types were not discrete. We propose an updated pulse type classification scheme approach that is highly reproducible across observers and exhibits high strong classification accuracy using support vector machines. Although the low number of call types suggests long calls are fairly simple, the continuous gradation of sounds seems to greatly boost the complexity of this system. This work responds to calls for more quantitative research to define call types and measure quantifythe gradedness of in animal vocal systems and highlights the need for a more comprehensive framework for studying vocal complexity vis-à-vis graded repertoires. </p> </div>
VocalMind: A Stereotactic EEG Dataset for Vocalized, Mimed, and Imagined Speech in Tonal Language
<p> Speech BCIs based on implanted electrodes hold significant promise for enhancing spoken communication through high temporal resolution and invasive neural sensing. Despite the potential, acquiring such data is challenging due to its invasive nature, and publicly available datasets, particularly for tonal languages, are limited. In this study, we introduce <em>VocalMind</em>, a stereotactic electroencephalography (sEEG) dataset focused on Mandarin Chinese, a tonal language. This dataset includes sEEG-speech parallel recordings from three distinct speech modes, namely vocalized speech, mimed speech, and imagined speech, at both word and sentence levels, totaling over one hour of intracranial neural recordings related to speech production. This paper also presents a baseline model as the reference model for future studies, at the same time, ensuring the integrity of the dataset. The diversity of tasks and the substantial data volume provide a valuable resource for developing advanced algorithms for speech decoding, thereby advancing BCI research for spoken communication.</p>
Context shapes emotion perception and prosocial behavior to real-life laughter and crying vocalizations - Raw data
<p>This repository contains raw data for the manuscript (under review): <i>Context shapes emotion perception and prosocial behavior to real-life laughter and crying vocalizations regardless of their diverse perceptual properties. </i></p><p>Please contact Doron Atias (doron.atias@mail.huji.ac.il) if you have questions concerning the data provided in this repository.</p>
Context shapes emotion perception and prosocial behavior to real-life laughter and crying vocalizations - Code
<p>This R Markdown document includes the code for data presentation in Atias & Aviezer (2024): "Context shapes emotion perception and prosocial behavior to real-life laughter and crying vocalizations regardless of their diverse perceptual properties". Please contact Doron Atias (doron.atias@mail.huji.ac.il) if you have questions.</p>
Code & Data for "Vocal labeling of others by nonhuman primates"
<p>This dataset contains code and data for the figures associated with the paper:</p> <p>"<strong>Vocal labeling of others by nonhuman primates</strong>" </p> <p>Oren <em>et al.</em>, Science (2024) [DOI: <a href="https://www.science.org/doi/10.1126/science.adp3757">10.1126/science.adp3757</a>]</p> <p>The repository includes:</p> <ul> <li>MATLAB code for analysizing phee calls.</li> <li>Data from the main figures of the paper.</li> </ul> <p>Any questions should be directed to the corresponding author of the paper, David Omer (<a rel="noreferrer">david.omer@mail.huji.ac.il</a>).</p>
Analysis of the Effects of Vocal Conditioning Through Semi-occluded Vocal Tract Exercises in Choir Singers
ClinicalTrials.gov study NCT03101449. IPD Sharing: NO. Countries: 1. Publications: 0.
The Effect of Exposure to Aversive Non-verbal Vocalizations on Pain Tolerance
ClinicalTrials.gov study NCT04423874. IPD Sharing: NO. Countries: 1. Publications: 0.
GlideScope® Versus Macintosh Laryngoscope for Post-thyroidectomy Assessment of Vocal Cord Mobility
ClinicalTrials.gov study NCT03834597. IPD Sharing: UNDECIDED. Countries: 1. Publications: 0.
Vocal Feature Analysis Algorithm for COVID-19 Detection
ClinicalTrials.gov study NCT04418544. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Pilot Study for Use of Dysport in Treatment of Vocal Tics in Patients With Tourette's Syndrome
ClinicalTrials.gov study NCT02187679. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Surgical Conditions During Vocal Cord Surgery Requiring Jet Ventilation With Moderate vs. Deep Neuromuscular Block
ClinicalTrials.gov study NCT02888067. IPD Sharing: NO. Countries: 1. Publications: 0.
The Effect of Fish Oil Supplementation on Vocal Performance
ClinicalTrials.gov study NCT05141045. IPD Sharing: NO. Countries: 1. Publications: 0.
Comparative Effects of Vocal and Breathing Exercises on Respiratory Function and Trunk Stability in Women
ClinicalTrials.gov study NCT07175844. IPD Sharing: UNDECIDED. Countries: 1. Publications: 0.
Phase 3 Study of KP-100LI in Subjects With Vocal Fold Scar
ClinicalTrials.gov study NCT05627648. IPD Sharing: Not stated. Countries: 1. Publications: 0.
The Effect of Inhaled Corticosteroids on Vocal Fold Nodules in Children
ClinicalTrials.gov study NCT03040596. IPD Sharing: NO. Countries: 1. Publications: 0.
APrevent Vocal Implant System (VOIS) for Adjustable Treatment of Unilateral Vocal Fold Paralysis (UVFP)
ClinicalTrials.gov study NCT03864757. IPD Sharing: NO. Countries: 1. Publications: 0.
Vocal in Assessment of Endometrium in Postmenopause
ClinicalTrials.gov study NCT03404154. IPD Sharing: NO. Countries: 1. Publications: 0.
Peri-operative BiPAP to Prevent Tracheostomy in High-Risk Bilateral Vocal-Cord Paralysis (BVCP)
ClinicalTrials.gov study NCT07042971. IPD Sharing: UNDECIDED. Countries: 1. Publications: 0.
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
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.