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42 results for “Provider Behavior”
Dataset of behavioral and neurophysiological data of a virtual sailing task published in: "Providing task instructions during motor training enhances performance and modulates attentional brain networks"
<p>Dataset belonging to the behavioral and neurophysiological data of the publication: "Providing task instructions during motor training enhances performance and modulates attentional brain networks". The two uploaded Zip files contain kinematic and electroencephalographic data of 36 participants for the Obstacle and HorizonTask.</p>
Evolution of a mosquito's hatching behavior to match its human-provided habitat
<p>A subspecies of the yellow fever mosquito, <em>Aedes aegypti</em>, has recently evolved to specialize in biting and living alongside humans. It prefers human odor and breeds in human-provided artificial containers rather than the forest tree holes of its ancestors. Here, we report one way this human specialist has adapted to the distinct ecology of human environments. While eggs of the ancestral subspecies rarely hatch in pure water, those of the derived human-specialist do so readily. We trace this novel behavior to a shift in how eggs respond to dissolved oxygen, low levels of which may signal food abundance. Moreover, we show that while tree holes are consistently low in dissolved oxygen, artificial containers often have much higher levels. There is thus a concordance between the hatching behavior of each subspecies and the aquatic habitat it uses in the wild. We find this behavioral variation is heritable, with both maternal and zygotic effects. The zygotic effect depends on dissolved oxygen concentration (i.e., GxE), pointing to potential changes in oxygen-sensitive circuits. Together, our results suggest that a shift in hatching response contributed to the pernicious success of this human-specialist mosquito and illustrate how animals may rapidly adapt to human-driven changes in the environment.</p>
Data for: Simulation and social network analysis provide insight into the acquisition of tool behavior in hybrid macaques
<p>The pathways through which primates acquire skills are a central focus of cultural evolution studies. The roles of social and genetic inheritance processes in skill acquisition are often confounded by environmental factors. Hybrid macaques from Koram Island, Thailand provide an opportunity to examine the roles of inheritance and social learning to skill acquisition within a single ecological setting. These hybrids are a cross between tool-using Burmese long-tailed (<em>Macaca</em> <em>fascicularis</em> <em>aurea</em>) and non-tool-using common long-tailed macaques (<em>Macaca</em> <em>fascicularis</em> <em>fascicularis</em>). This population provides an opportunity to explore the roles of social learning and inheritance processes while being able to exclude underlying ecological factors. Here, we investigate the roles of social learning and inheritance in tool use prevalence within this population using social network analysis and simulation. Agent-based modeling (ABM) is used to generate expectations for how social/asocial learning and inheritance structure the patterning in a social network. The results of the simulation show that various transmission mechanisms can be differentiated based on associations between individuals in a social network. The results provide an investigative framework for discussing tool-use transmission pathways in the Koram social network. By combining ABM, network analysis, and behavioral data from the field we can investigate the roles social learning and inheritance play in tool acquisition in wild primates. </p>
Cortex-wide neural dynamics predict behavioral states and provide a neural basis for resting-state dynamic functional connectivity
<p><strong>GENERAL INFORMATION</strong></p> <p>This data is described in the following publication: </p> <p><strong>Cortex-wide neural dynamics predict behavioral states and provide a neural basis for resting-state dynamic functional connectivity</strong>, Somayeh Shahsavarani<sup>1,2,5</sup>, David N. Thibodeaux<sup>1,5</sup>, Weihao Xu<sup>1</sup>, Sharon H. Kim<sup>1</sup>, Fatema Lodgher<sup>1</sup>, Chinwendu Nwokeabia<sup>1</sup>, Morgan Cambareri<sup>1</sup>, Alexis J. Yagielski<sup>1</sup>, Hanzhi T. Zhao<sup>1</sup>, Daniel A. Handwerker<sup>2</sup>, Javier Gonzalez-Castillo<sup>2</sup>, Peter A. Bandettini<sup>2,3</sup>, Elizabeth M. C. Hillman<sup>1,4,6,*</sup> Cell Reports (2023): <a href="https://doi.org/10.1016/j.celrep.2023.112527">https://doi.org/10.1016/j.celrep.2023.112527</a></p> <p><br> 1. Mortimer B. Zuckerman Mind Brain Behavior Institute and Department of Biomedical Engineering, Columbia University, New York, NY, USA<br> 2. Section on Functional Imaging Methods, Laboratory of Brain and Cognition, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, USA<br> 3. Functional MRI Core Facility, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, USA<br> 4. Department of Radiology, Columbia University Irving Medical Center, New York, NY, USA<br> 5. These authors contributed equally<br> 6. Lead contact<br> *Correspondence: elizabeth.hillman@columbia.edu</p> <p>Preprocessing and analysis code that generated / can be used with this data is posted at: <br> GitHub: <a href="https://doi.org/10.5281/zenodo.7860561">https://doi.org/10.5281/zenodo.7860561</a></p> <p><strong>DATA OVERVIEW </strong></p> <p>This dataset comprises simultaneous neuronal and hemodynamic data collected using wide-field optical mapping (WFOM) techniques. The data were obtained from head-fixed mice that were allowed to behave spontaneously without any external stimulation. For more detail, please refer to the Readme file.</p>
Data from: Providing long hay in a novel pipe feeder or a bucket reduces some, but not all abnormal oral behaviors in milk-fed dairy calves
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Data for: Simulation and social network analysis provide insight into the acquisition of tool behavior in hybrid macaques
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Evolution of a mosquito’s hatching behavior to match its human-provided habitat
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Data and code from: Life under leaves: Substrate-borne vibrations provide a window into the behavior and ecology of two miniaturized geckos
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Vanellus chilensis dataset accompanying PLOS ONE paper "Automated Sound Recognition Provides Insights into the Behavioral Ecology of a Tropical Bird"
<p>Southern Lapwing <em>Vanellus chilensis</em> dataset accompanying the PLOS ONE article</p> <p>O. Jahn, T. Ganchev, M.I. Marinez and K.L. Schuchmann: Automated Sound Recognition Provides Insights into the Behavioral Ecology of a Tropical Bird. DOI:10.1371/journal.pone.0169041</p> <p>---<br> BL01:<br> Background Library 01 consists of</p> <p>BL01 >> BL_CHVACH_free_final:<br> 54 hand-cleaned (<em>Vanellus chilensis</em>-free) background files and</p> <p>BL01 >> PSC008_forest:<br> 36 original soundscapes recorded inside forest, which may contain a few target signals from overflying lapwings.</p> <p>---<br> PONE_VACH_AnnualCycle_Statistics:<br> Contains the Excel files<br> - 2013CHVACH_BreedingCycle_Statistics_PONE: statistics on <em>V. chilensis</em> activity patterns, Apr. 2013 to Sep. 2013.<br> - 2013CHVACH_FalseNegatives_PONE: determination of the false negative rate based on an expert-annotated sample of 26 soundcsape recordings<br> - 2013CHVACH_FalsePositives_PONE: determination of the false positive rate based on an expert-annotated random sample of 1250 automated <em>V. chilensis</em> detections.</p> <p>---<br> TL01_BIAVCHCHVACH_20130813v2_HandCleaned:<br> Training library for the development of the <em>V. chilensis</em> recognizer, consisting of 90 hand-filtered recordings of the target species.</p> <p>---<br> VACH_Detector_results >> VACHdetectorOutput_PONE.zip:<br> TXT detector output files, listing timestamps of potential <em>V. chilensis</em> sound events.</p> <p>---<br> VACH_FNrate_20160706:<br> Validation library used to determine the false negative rate. The library consists of 26 expert-annotated sound files. Annotations were made in Adobe Audion v3.0.</p> <p>---<br> VL01_VACH_MonoB<br> and<br> VL01_VACH_MonoB:<br> Validation library used for the fine-tuning of the recognizer settings.</p> <p>---<br> Important notes on the annotation of the VACH_FNrate_20160706 library:</p> <p>1) In general, we used the procedure described in Ganchev et al. 2015 for the annotation of VACH validation libraries (see next section).</p> <p>2) However, the detector-generated timestamps were not changed! For the following reasons, it is not possible to use the VACH_FN_rate library as a validation library for the development of improved recognizer versions:</p> <p>(a) The VACH detector overlooked many of the weaker signals within a VACH call series. Therfore the detector-generated annotations are incomplete.<br> (b) For the same reason some automatically-generated detections may refer to a single VACH call event (double hits).</p> <p>Details on the method used for the annotation of the VACH validation libraries are described in Ganchev et al. 2015, pp.6100f: 2.1.3.3.Vanellus chilensis validation dataset.</p>
Assessing Mental Health Providers' Clinical Knowledge and Skills Via an Online Training on LGBTQ-affirmative Cognitive-behavioral Therapy
ClinicalTrials.gov study NCT04559698. IPD Sharing: NO. Countries: 1. Publications: 5.
Data from: Consistent coordination patterns provide near perfect behavior decoding in a comprehensive motor program for insect flight
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Scripts and metadata of the manuscript: Characterization of tmt-opsin2 in medaka fish provides insight into the interplay of light and temperature for behavioral regulation
<p>One of the big challenges in the study of animal behavior is to combine the molecular-level questions of functional genetics, typically performed in the lab, with meaningful combinations of environmental stimuli. Light and temperature are important external cues, influencing the behaviors of organisms. Thus, understanding the combined effect of light and temperature changes on wildtype versus genetically modified animals is a first step to understand the role of individual genes in the ability of animals to cope with changing environments.</p> <p>Many behavioral traits can be extrapolated from behavioral tests performed from automated motion tracking combined with machine learning. The acquired datasets, typically complex and large, can be challenging for subsequent quantitative analyses.</p> <p>Here we investigate medaka behavior of <em>tmt-opsin2</em> mutants versus corresponding wildtypes under different light and temperature conditions using automated tracking combined with a convolutional neuronal network and a Hidden Markov model-based approach. The temperatures in this study can occur in summer versus fall/winter in the natural habitat of medakafish. Under summer-like temperature, <em>tmt-opsin2</em> mutants did not exhibit changes in overall locomotion, consistent with previous observations. However, detailed analyses of fish position revealed that <em>tmt-opsin2 </em>mutants spent more time in central locations of the dish, possibly due to decreased anxiety. Furthermore, a clear difference in location and overall movement was obvious between mutant and wildtypes under colder conditions. These data indicate a role of <em>tmt-opsin2 </em>in behavioral adjustment, at least in part depending on the season.</p>
Figure 3 in Regional Distribution Of A Brain-Encysting Parasite Provides Insight On Parasite-Induced Host Behavioral Manipulation
Figure 3. Correlation between the number of encysted Euhaplorchis californiensis metacercariae on the whole brain of California killifish (Fundulus parvipinnis) and the number of parasites on the diencephalon/ mesencephalon region in experimentally infected F. parvipinnis individuals. The correlation was checked using Spearman's rho (¼ 0.98).
Figure 1 in Regional Distribution Of A Brain-Encysting Parasite Provides Insight On Parasite-Induced Host Behavioral Manipulation
Figure 1. Figure displaying the number of Euhaplorchis californiensis parasites (A), weight (B), and mass parasite density (parasites/g body mass) (C) in experimentally infected and naturally infected fish. Different letters indicate differences in Tukey post-hoc test performed after a 1-way ANOVA; stars indicate significant difference in the Mann–Whitney Utest. On the y-axis, we show the number of parasites (A), body mass in + grams (B), and parasite density (parasites/g body mass) (C), and on the x- axis, we show the different treatment groups: low-infection treatment (n ¼ 8), high-infection treatment (n ¼ 8), experimentally infected (n ¼ 16), and naturally infected (n ¼ 25).
Figure 2 in Regional Distribution Of A Brain-Encysting Parasite Provides Insight On Parasite-Induced Host Behavioral Manipulation
Figure 2. Contrasting Euhaplorchis californiensis brain surface parasite density (A) and parasite numbers (B) in 3 brain regions in both high- and low-infection treatment groups. Different letters indicate the statistical difference between the different brain regions given by a Tukey post-hoc test, and the stars indicate a statistical difference between the 2 infection treatments (low and high). In all groups, n ¼ 8. Brain surface parasite density is defined as the number of parasites per square millimeter of brain surface area.
An Internet-delivered Cognitive-behavioral Intervention Provided Soon After Trauma
ClinicalTrials.gov study NCT03850639. IPD Sharing: NO. Countries: 1. Publications: 1.
Healthcare Provider Behavior and Children's Perioperative Distress
ClinicalTrials.gov study NCT01878747. IPD Sharing: Not stated. Countries: 2. Publications: 1.
Provider-Targeted Behavioral Interventions to Prevent Unsafe Opioid Prescribing for Acute Pain in Primary Care
ClinicalTrials.gov study NCT03537573. IPD Sharing: NO. Countries: 1. Publications: 1.
Measuring Change in Overcoming Implicit Biases in Behavior by Emergency Care Center Providers
ClinicalTrials.gov study NCT06630507. IPD Sharing: NO. Countries: 1. Publications: 5.
Scripts and metadata of the manuscript: Characterization of tmt-opsin2 in medaka fish provides insight into the interplay of light and temperature for behavioral regulation
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ScienceDex guides
Understand access before you commit
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.