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Dataset results
61 results for “visual scale”
Data from: How biological attention mechanisms improve task performance in a large-scale visual system model
How does attentional modulation of neural activity enhance performance? Here we use a deep convolutional neural network as a large-scale model of the visual system to address this question. We model the feature similarity gain model of attention, in which attentional modulation is applied according to neural stimulus tuning. Using a variety of visual tasks, we show that neural modulations of the kind and magnitude observed experimentally lead to performance changes of the kind and magnitude observed experimentally. We find that, at earlier layers, attention applied according to tuning does not successfully propagate through the network, and has a weaker impact on performance than attention applied according to values computed for optimally modulating higher areas. This raises the question of whether biological attention might be applied at least in part to optimize function rather than strictly according to tuning. We suggest a simple experiment to distinguish these alternatives.
Visualizing synaptic plasticity in vivo by large-scale imaging of endogenous AMPA receptors
<p>Elucidating how synaptic molecules such as AMPA receptors mediate neuronal communication and tracking their dynamic expression during behavior is crucial to understand cognition and disease, but current technological barriers preclude large-scale exploration of molecular dynamics in vivo. We have developed a suite of innovative methodologies that break through these barriers: a new knockin mouse line with fluorescently tagged endogenous AMPA receptors, two-photon imaging of hundreds of thousands of labeled synapses in behaving mice, and computer vision-based automatic synapse detection. Using these tools, we can longitudinally track how the strength of populations of synapses changes during behavior. We used this approach to generate an unprecedentedly detailed spatiotemporal map of synapses undergoing changes in strength following sensory experience. More generally, these tools can be used as an optical probe capable of measuring functional synapse strength across entire brain areas during any behavioral paradigm, describing complex system-wide changes with molecular precision.</p>
Pain Comparison Whit Visual Analog Scale (EVA) Between Four Analgesic Methods During Trans Rectal Prostatic Biopsy
ClinicalTrials.gov study NCT03442075. IPD Sharing: NO. Countries: 1. Publications: 6.
The Aim of Study is Translate and Adapt the Visual Analog Scale Foot and Ankle (VAS-FA) Instrument Into Turkish and Psycho-metrically Test Its Reliability and Validity Among Patients Who Had Foot and
ClinicalTrials.gov study NCT03262324. IPD Sharing: UNDECIDED. Countries: 1. Publications: 9.
Development of a Method for Converting Visual Analogue Scale (VAS) Scores for Pain and Mobility to EQ-5D Answers
ClinicalTrials.gov study NCT01424683. IPD Sharing: Not stated. Countries: 1. Publications: 2.
Use of a 10 Points Visual Analogue Food Intake Scale for Children to Assess Intake: Prospective Study
ClinicalTrials.gov study NCT05726422. IPD Sharing: Not stated. Countries: 1. Publications: 4.
Validation of Appetite Method Visual Analogue Scales in Home-setting: VASA-home
ClinicalTrials.gov study NCT05004584. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Evaluation of Analgesic Efficacy of Lidocaine and Diclofenac Spray in Radial Artery Blood Gas Sampling by Visual Analogue Scale and Perfusion Index
ClinicalTrials.gov study NCT06918340. IPD Sharing: YES. Countries: 1. Publications: 1.
Validation of Visual Analog Scales to Measure SatisfactiOn and WELL-being at Work (SoWell-VAS)
ClinicalTrials.gov study NCT05871411. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Establishing Visualization Grading Scale on LESS Cholecystectomy
ClinicalTrials.gov study NCT02264444. IPD Sharing: NO. Countries: 1. Publications: 5.
Data from: How biological attention mechanisms improve task performance in a large-scale visual system model
Open the record for dataset details and reuse information.
Visualizing synaptic plasticity in vivo by large-scale imaging of endogenous AMPA receptors
Open the record for dataset details and reuse information.
ToxicoDB: an integrated database to mine and visualize large-scale toxicogenomic datasets (TGGATEs rat dataset)
<p>This data was generated by Igarashi Y, Nakatsu N, Yamashita T, Ono A, Ohno Y, Urushidani T, Yamada H. Open TG-GATEs: a large-scale toxicogenomics database. Nucleic Acids Res [Internet]. 2015 Jan;43(Database issue):D921–7. Available from: http://dx.doi.org/10.1093/nar/gku955 PMCID: PMC4384023. The data have been curated and analyzed using our open-source R package, <em>ToxicoGx</em> (<a href="http://bioconductor.org/packages/devel/bioc/html/ToxicoGx.html">http://bioconductor.org/packages/devel/bioc/html/ToxicoGx.html</a>) and are available publicly in the <em>ToxicoDB </em>web application (<a href="http://www.toxicodb.ca">www.toxicodb.ca</a>).</p>
ToxicoDB: an integrated database to mine and visualize large-scale toxicogenomic datasets (drug matrix dataset)
<p>This data was generated by Ganter B, Snyder RD, Halbert DN, Lee MD. Toxicogenomics in drug discovery and development: mechanistic analysis of compound/class-dependent effects using the DrugMatrix database. Pharmacogenomics [Internet]. 2006 Oct;7(7):1025–1044. Available from: http://dx.doi.org/10.2217/14622416.7.7.1025 PMID: 17054413. The data have been curated and analyzed using our open-source R package, <em>ToxicoGx</em> (<a href="https://cran.r-project.org/web/packages/ToxicoGx/">cran.r-project.org/web/packages/ToxicoGx</a>) and are available publicly in the <em>ToxicoDB </em>web application (<a href="http://www.toxicodb.ca">www.toxicodb.ca</a>).</p> <p> </p> <p> </p>
Multi-scale optical coherence tomography imaging and visualization of Vermeer's Girl with a Pearl Earring
<p>The data sets, software, and figures accompany the publication:</p> <p>"Multi-scale optical coherence tomography imaging and visualization of Vermeer's Girl with a Pearl Earring", Optics Express 28, 26239 (2020) <a href="https://doi.org/10.1364/OE.390703">https://doi.org/10.1364/OE.390703</a></p> <ul> <li>Fig4_largescaleOCT.pdf, high resolution image of figure 4 of the manuscript</li> <li>Fig5_mediumscaleOCT.pdf, high resolution image of figure 5 of the manuscript</li> <li>Fig6_smallscaleOCT.pdf, high resolution image of figure 6 of the manuscript</li> <li>GWPE_DEMO_V5.zip<br> Zip file of a Windows executable of the virtual rendering of the Girl with the Pearl Earring. The readme file describes the operation of the virtual rendering.</li> <li>Stitching_README.txt Describes the stitching software and the accompanying data sets</li> <li>MS-OCT surface data: <ul> <li>SurfaceStitchedKwadrant11.npy</li> <li>SurfaceStitchedKwadrant12.npy</li> <li>SurfaceStitchedKwadrant21.npy</li> <li>SurfaceStitchedKwadrant22.npy</li> <li>UpperInterfaceMatrixRawdataKwadrant11.npy</li> </ul> </li> <li>MS-OCT thickness data <ul> <li>FullResGlazeStratigraphyThicknessKwadrant11.npy</li> <li>FullResGlazeStratigraphyThicknessKwadrant12.npy</li> <li>FullResGlazeStratigraphyThicknessKwadrant21.npy</li> <li>FullResGlazeStratigraphyThicknessKwadrant22.npy</li> </ul> </li> <li>MS-OCT Scattering strength data <ul> <li>FullResScatteringStrengthKwadrant11.npy</li> <li>FullResScatteringStrengthKwadrant12.npy</li> <li>FullResScatteringStrengthKwadrant21.npy</li> </ul> </li> <li>Main.py, DataAnalysisFunctionsRepository.py, and ReadAndCombineKwadrantData.py are Python files for stitching the four quadrants of data together. Runs in Python >3.5. Full stitching image takes more than an hourFullResScatteringStrengthKwadrant22.npy</li> <li>Plot_measure.py and plot_fit.py<br> Analysis of the BRDF measurements of the black underlayer background (RU1) and glaze layer (RU5). Runs in Python > 3.5</li> <li>Visualization1.ave<br> Video of the multi-scale multi-parameter OCT data set of the Girl</li> <li>Visualization2.mp4<br> Video showing an impression of the interactive demo of the Girl <ul> </ul> </li> </ul>
Figure 3 from: Klein A (2016) Visual Parkinson's Disease Rating Scale: A Universal Iconic Questionnaire for Epidemiological Studies in India. Research Ideas and Outcomes 2: e8834. https://doi.org/10.3897/rio.2.e8834
Figure 3 - Timeline This Gantt chart provides an estimate of the relative timing and duration for achieving each of the Aims.
Figure 1 from: Klein A (2016) Visual Parkinson's Disease Rating Scale: A Universal Iconic Questionnaire for Epidemiological Studies in India. Research Ideas and Outcomes 2: e8834. https://doi.org/10.3897/rio.2.e8834
Figure 1 - First pass at a VPDRS static graphic Figure 1 corresponds to the first self-administered MDS-UPDRS question: 1.7 SLEEP PROBLEMS. Over the past week, have you had trouble going to sleep at night or staying asleep through the night? Consider how rested you felt after waking up in the morning. 0: Normal: No problems. 1: Slight: Sleep problems are present but usually do not cause trouble getting a full night of sleep. 2: Mild: Sleep problems usually cause some difficulties getting a full night of sleep. 3: Moderate: Sleep problems cause a lot of difficulties getting a full night of sleep, but I still usually sleep for more than half the night. 4: Severe: I usually do not sleep for most of the night."
Figure 2 from: Klein A (2016) Visual Parkinson's Disease Rating Scale: A Universal Iconic Questionnaire for Epidemiological Studies in India. Research Ideas and Outcomes 2: e8834. https://doi.org/10.3897/rio.2.e8834
Figure 2 - Prototype for the mobile phone app This screen shows a pre-release version of Node, which will support the VPDRS/UPDRS modules. Here we present a means by which a person administering a questionnaire can securely log into and manipulate patient information locally and through cloud services and lastly an example clinician-administered UPDRS question.
we Use Recovery Time to Assess Post-dialysis Fatigue and we Use Also Two Different Fatigue Scales 1- Visual Analogue Scale 2- Fatigue Severity Scale and we Address Risk Factors of PDF and Apply the Sc
ClinicalTrials.gov study NCT06947681. IPD Sharing: UNDECIDED. Countries: 0. Publications: 3.
A large-scale depth-based multimodel audio-visual corpus in mandarin
<p>A large-scale depth-based multimodel audio-visual corpus in mandarin,.</p> <p>This file have depth-based Lip point data. The rest of the data is being collated and will be made public soon.</p> <pre>If the dataset is useful for your research, please cite our work: @inproceedings{Jianrong2018A, title={A Large-Scale Depth-Based Multimodal Audio-Visual Corpus in Mandarin}, author={Jianrong Wang and Liyuan Wang and Ju Zhang and Jianguo Wei and Ruiguo Yu}, booktitle={2018 IEEE 20th International Conference on High Performance Computing and Communications; IEEE 16th International Conference on Smart City; IEEE 4th International Conference on Data Science and Systems (HPCC/SmartCity/DSS)}, year={2018}, }</pre> <p> </p>
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.