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ShareScore release 0.9.0
Dataset results
65 results for “information visualization”
Remembering Risk Using Visual Risk Display of MINS to Obtain Informed Consent to Undergo Elective Surgery
ClinicalTrials.gov study NCT05098535. IPD Sharing: NO. Countries: 1. Publications: 1.
Data from: Analysis and visualization of H7 influenza using genomic, evolutionary and geographic information in a modular web service
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Data from: Disentangling olfactory and visual information used by field foraging birds
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Collective detection based on visual information in animal groups
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Data from: How lovebirds maneuver through lateral gusts with minimal visual information
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Data from: Assessing the potential information content of multicomponent visual signals: a machine learning approach
Careful investigation of the form of animal signals can offer novel insights into their function. Here, we deconstruct the face patterns of a tribe of primates, the guenons (Cercopithecini), and examine the information that is potentially available in the perceptual dimensions of their multicomponent displays. Using standardized colour-calibrated images of guenon faces, we measure variation in appearance both within and between species. Overall face pattern was quantified using the computer vision 'eigenface' technique, and eyebrow and nose-spot focal traits were described using computational image segmentation and shape analysis. Discriminant function analyses established whether these perceptual dimensions could be used to reliably classify species identity, individual identity, age and sex, and, if so, identify the dimensions that carry this information. Across the 12 species studied, we found that both overall face pattern and focal trait differences could be used to categorize species and individuals reliably, whereas correct classification of age category and sex was not possible. This pattern makes sense, as guenons often form mixed-species groups in which familiar conspecifics develop complex differentiated social relationships but where the presence of heterospecifics creates hybridization risk. Our approach should be broadly applicable to the investigation of visual signal function across the animal kingdom.
Influence of Prior Visual Information on Exploratory Movement Direction in Texture Perception
<p>Raw data of all individual participants</p>
Data from: Pigment molecular composition reveals significant information for visual communication
<p>1. Melanins are the most common pigments in vertebrates and, as such, fufill multiple adaptive functions, including honest signaling. This is the case of male pied flycatchers Ficedula hypoleuca, whose dorsal plumage, composed of black and grey feathers pigmented by eumelanin, is sexually selected by females regarding the proportion of black.</p> <p>2. However, the basis of such mating preferences and other associations with life-history traits are unknown. </p> <p>3. Here I take advantage of recent advances in Raman spectroscopy analysis to investigate the monomeric composition of eumelanin, constituted by 5,6-dihydroxyindole (DHI) and 5,6-dihydroxyindole-2-carboxylic acid (DHICA) subunits, in male pied flycatchers. </p> <p>4. I found that plumage blackness (percentage of dorsal black feathers) increases with the DHICA:DHI ratio of the constituent black freathers, but not with that of grey feathers. The repeatability of DHICA:DHI measurements in black feathers is two times that in grey feathers. </p> <p>5. Eumelanin chemistry may thus constitute the basis of signal honesty in pied flycatchers, as females preferentially mate with males with higher relative DHICA feather contents and this may be related to the lower pro-oxidant effect of DHICA. Given the the ubiquitous nature of melanin-based pigmentation phenotypes, the monomeric composition of eumelanin should therefore be considered, instead of eumelanin as a whole, for a better understanding of how and why phenotypes are linked to life-history traits in animals.</p>
Figure 3 in Visual Comparison for Information Visualization
Figure 3: The design space provides three primary categories (juxtaposition, superposition, and explicit representation) with the three intermediary categories. The visualization is taken from our database of systems that we have researched. Our database includes a number of representative systems from the Information Visualization literature whose designs explicitly support the comparison of complex objects, which demonstrates the diversity of the systems.
Figure 2 in Visual Comparison for Information Visualization
Figure 2: Two networks (illustrated as node-link diagrams) are compared using designs of the six categories, with some of the major types in categories shown. These designs are meant as an illustration to define the category/type, not as being representative of a successful strategy for comparing two small networks.
Figure 1 in Visual Comparison for Information Visualization
Figure 1: A simple example of comparative visualizations: comparing two time series. For example, the data might represent measurements from two sensors (X and Y) taken over time. The three basic approaches for comparative visualization are (a) juxtaposition, (b) superposition, (c,d) explicit encoding of relationships. Two new representations from fusion are shown: (c) signal subtraction and (d) a time alignment curve, such as produced by dynamic time warping.
Visual Information Restoration and Rehabilitation Via Sensory Substitution Technology in Children
ClinicalTrials.gov study NCT03002597. IPD Sharing: UNDECIDED. Countries: 1. Publications: 0.
Visual Information Processing in Schizophrenia Patients With Visual Hallucinations
ClinicalTrials.gov study NCT03188133. IPD Sharing: NO. Countries: 0. Publications: 4.
Data from: Assessing the potential information content of multicomponent visual signals: a machine learning approach
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Data from: Pigment molecular composition reveals significant information for visual communication
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Data from: Prediction error and repetition suppression have distinct effects on neural representations of visual information
Predictive coding theories argue that recent experience establishes expectations in the brain that generate prediction errors when violated. Prediction errors provide a possible explanation for repetition suppression, where evoked neural activity is attenuated across repeated presentations of the same stimulus. The predictive coding account argues repetition suppression arises because repeated stimuli are expected, whereas non-repeated stimuli are unexpected and thus elicit larger neural responses. Here we employed electroencephalography in humans to test the predictive coding account of repetition suppression by presenting sequences of visual gratings with orientations that were expected either to repeat or change in separate blocks of trials. We applied multivariate forward modelling to determine how orientation selectivity was affected by repetition and prediction. Unexpected stimuli were associated with significantly enhanced orientation selectivity, whereas selectivity was unaffected for repeated stimuli. Our results suggest that repetition suppression and expectation have separable effects on neural representations of visual feature information.
Effect of a Visual Nutrient Profiling System on Recall of Nutrition Information
ClinicalTrials.gov study NCT01486147. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Remembering Risk: Using Visual Risk Display of MINS to Obtain Informed Consent to Undergo Elective Surgery
ClinicalTrials.gov study NCT04247841. IPD Sharing: NO. Countries: 1. Publications: 0.
Evaluation of Verbal and Visual Information Techniques
ClinicalTrials.gov study NCT04017689. IPD Sharing: NO. Countries: 1. Publications: 0.
Benefits of Early Proprioceptive Re-education Without Visual Information After Total Knee Arthroplasty
ClinicalTrials.gov study NCT06936267. IPD Sharing: NO. Countries: 1. Publications: 0.
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.