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146 results for “Visual systems”

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ClinicalTrials.gov32/100

PAVE (Parallactic Visual-Field Enhancement) System for Treatment of Chronic Visual Field Loss Due to Stroke, Traumatic Brain Injury, or Brain Surgery

ClinicalTrials.gov study NCT07185971. IPD Sharing: UNDECIDED. Countries: 1. Publications: 25.

restrictedIPD-UNDECIDEDFeb 2026View details →
dryad32/100

Data from: The price of looking sexy: visual ecology of a three level predator-prey system

Open the record for dataset details and reuse information.

publicSep 2016View details →
dryad32/100

GLAM: Glycogen-derived Lactate Absorption Map for visual analysis of dense and sparse surface reconstructions of rodent brain structures on desktop systems and virtual environments

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publicMay 2019View details →
dryad32/100

Data from: How biological attention mechanisms improve task performance in a large-scale visual system model

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publicOct 2018View details →
dryad32/100

Data from: Sensory limitations and the maintenance of color polymorphisms: viewing the ‘alba’ female polymorphism through the visual system of male Colias butterflies

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publicDec 2014View details →
dryad32/100

Data from: Cardinalfishes (Apogonidae) show visual system adaptations typical of nocturnally and diurnally active fish

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publicMar 2019View details →
dryad32/100

Data from: The evolution of complexity in the visual systems of stomatopods: insights from transcriptomics

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publicJun 2013View details →
edi32/100

Index of visual monitoring, location, species behavior, and identification of cetaceans from CalCOFI cruises in the California Current System, 2005-2015 (ongoing).

Field observations are carried out to gain understanding of cetacean ecology and habitat. Visual monitoring for cetaceans has been conducted on quarterly CalCOFI cruises since July 2004 using standard line-transect protocol (Burnham et al. 1980;Buckland et al. 1993; Barlow 1995). Visual observers watch during daylight hours, when weather permits (Beaufort sea states 0 to 5 and visibility greater than 1 nautical mile) and while the ship transits between CalCOFI stations.

openCustomMar 2017View details →
zenodo28/100

Molecular Evolution of Tuatara Visual System Datasets: Supporting Data for the Tuatara Genome

<p>Datasets associated with the Molecular Evolution of Tuatara Visual System supplement to the paper: The Tuatara Genome: Insights into Vertebrate Evolution from the Sole Survivor of an Ancient Reptilian Order.</p>

opencc-by-4.0Mar 2019View details →
zenodo28/100

Visualization of the process of lightning initiation in a thundercloud via coalescence of multiple simultaneously developing bipolar streamer/leader systems

<p>This movie visualizes the evolution of 3D streamer / hot-channel systems at 6 km altitude in a uniform upward directed electric field, the&nbsp;magnitude of which is equal to 65 kV/m. Positive and negative streamer channels are shown in green and gray, respectively. Red channels indicate hot leader sections with conductivity exceeding 1 S/m. All three axes are labeled in meters.</p>

opencc-by-4.0Dec 2020View details →
zenodo28/100

2D/3D Visualization Study for Microservice Systems

<p>This dataset contains:</p> <ul> <li>The Visualization Models PoC Source Code.</li> <li>Tools' Screenshots.</li> <li>Protocol Material.</li> <li>Study Data Collection and results.</li> </ul>

opencc-by-4.0Jul 2024View details →
dryad28/100

Data from: Emerging Representational Geometries in the Visual System Predict Reaction Times for Object Categorization

Recognizing an object takes just a fraction of a second, less than the blink of an eye. Applying multivariate pattern analysis, or "brain decoding", methods to magnetoencephalography (MEG) data has allowed researchers to characterize, in high temporal resolution, the emerging representation of objects that underlie our capacity for rapid recognition. Shortly after stimulus onset, exemplar stimuli cluster by category in high-dimensional activation spaces. In these emerging activation spaces, the decodability of exemplar category varies over time, reflecting the brain's transformation of visual inputs into coherent categorical representations. How do these emerging representations relate to categorization behavior? Recently it has been proposed that the distance of an exemplar representation from a categorical boundary in an activation space is critical for perceptual decision-making, and that reaction times should therefore correlate with distance from the boundary. The predictions of this distance hypothesis have been born out in human inferior temporal cortex (IT), an area of the brain crucial for the representation of object categories. The time of peak decoding is the optimal time for category information to be "read out" from the brain's time varying representation of the stimuli. In this study, we tested the distance hypothesis, and specifically whether or not the brain reads out at the optimal time for choice behavior. Using MEG decoding methods, we show that the distance of a pattern of activity from a decision boundary through a high-dimensional activation space correlates with reaction times in a visual categorization task, but only during the period of peak decodability. Our results suggest the brain uses the optimal stimulus representation for choice behavior, and that neural representations for objects are partially constitutive of the decision process in visual perception.

opencc-zeroDec 2014View details →
zenodo28/100

Visualizing the organization and differentiation of the male-specific nervous system of C. elegans

<p>Image volumes and annotations for male NeuroPAL expression.</p> <p>The following image volumes&nbsp;were annotated by Tessa Tekieli and&nbsp;used by Amin Nejatbakhsh&nbsp;to build the male C. <em>elegans</em>&nbsp;atlas for:<br> &quot;Visualizing the organization and differentiation of the male-specific nervous&nbsp;system of C. elegans&quot;.</p> <p>The publication is available here:<br> https://journals.biologists.com/dev/article-abstract/doi/10.1242/dev.199687/271902/Visualizing-the-organization-and-differentiation</p> <p>These image files can be viewed with the NeuroPAL ID software, available at:<br> https://www.hobertlab.org/neuropal/<br> OR<br> https://github.com/amin-nejat/CELL_ID</p> <p>This software was provided for the NeuroPAL publication, &quot;NeuroPAL: A Multicolor&nbsp;Atlas for Whole-Brain Neuronal Identification in C. <em>elegans</em>&quot;.<br> The publication is available here:<br> https://www.cell.com/cell/fulltext/S0092-8674(20)31682-2</p> <p>Please cite the NeuroPAL publication when using the software.</p>

opencc-by-4.0Aug 2021View details →
ClinicalTrials.gov28/100

A Study Assessing the Safety and Effectiveness of IC2000 and SPY Fluorescence Imaging Systems (SPY-PHI) in the Visualization of Lymphatic Vessels and Identification of Lymph Nodes During Sentinel Lymp

ClinicalTrials.gov study NCT03200704. IPD Sharing: Not stated. Countries: 2. Publications: 0.

restrictedIPD-UNDECIDEDFeb 2026View details →
ClinicalTrials.gov28/100

Clinical Study on the Application of a Non-Invasive Micro-Focused Ultrasound With Visualization System for Skin Laxity (ULT-215)

ClinicalTrials.gov study NCT03545412. IPD Sharing: NO. Countries: 0. Publications: 1.

closedIPD-NOFeb 2026View details →
ClinicalTrials.gov28/100

Ultravision Visual Clearing System in Laparoscopic Hysterectomy and Myomectomy

ClinicalTrials.gov study NCT03634306. IPD Sharing: NO. Countries: 1. Publications: 0.

closedIPD-NOFeb 2026View details →
ClinicalTrials.gov28/100

Visual Outcomes and Patient Satisfaction With Implantation of the Clareon Monofocal IOL With the New Clareon Manual Monarch IV IOL Delivery System

ClinicalTrials.gov study NCT05526781. IPD Sharing: NO. Countries: 1. Publications: 0.

closedIPD-NOFeb 2026View details →
ClinicalTrials.gov28/100

Safety and Efficacy of Brimonidine Tartrate Posterior Segment Drug Delivery System in Improving Visual Function

ClinicalTrials.gov study NCT00972374. IPD Sharing: Not stated. Countries: 6. Publications: 0.

restrictedIPD-UNDECIDEDFeb 2026View details →
dryad28/100

Data from: Thalamocortical synapses in the cat visual system in vivo are weak and unreliable

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publicMay 2019View details →
dryad28/100

Data from: Emerging Representational Geometries in the Visual System Predict Reaction Times for Object Categorization

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publicAug 2015View details →

ScienceDex guides

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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.

allen-brain-atlas
neuroscienceopenDocumentation, web resources, and API references are available online.
Last verified 2026-04-30Open record

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.

abode-home-cage
behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.
Last verified 2026-04-30Open record

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.

dandi-nwb
electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.
Last verified 2026-04-30Open record

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.

ibl
behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.
Last verified 2026-04-29Open record

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.

openneuro
neuroscienceopenPublished datasets are available on demand over the internet.
Last verified 2026-04-29Open record