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44 results for “visual motion”

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dryad32/100

Data from: Asymmetric ON-OFF processing of visual motion cancels variability induced by the structure of natural scenes

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publicNov 2019View details →
dryad32/100

Data from: Static antennae act as locomotory guides that compensate for visual motion blur in a diurnal, keen-eyed predator

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publicJan 2015View details →
dryad32/100

In the corner of the eye: camouflaging motion in the peripheral visual field

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publicDec 2019View details →
zenodo28/100

Visually Inferring Elasticity from the Motion Trajectory of Bouncing Cubes

<p>Dataset relative to the following publication:</p> <p>Paulun, V.C., &amp; Fleming, R. W. (2020). Visually Inferring Elasticity from the Motion Trajectory of Bouncing Cubes. <em>Journal of Vision, </em>20(6):6, 1&ndash;14, https://doi.org/10.1167/jov.20.6.6</p> <p>One folder contains the stimuli, another folder contains data from the main and control experiment.</p>

opencc-by-4.0May 2020View details →
dryad28/100

Data from: Hummingbirds control hovering flight by stabilizing visual motion

Relatively little is known about how sensory information is used for controlling flight in birds. A powerful method is to immerse an animal in a dynamic virtual reality environment to examine behavioral responses. Here, we investigated the role of vision during free-flight hovering in hummingbirds to determine how optic flow—image movement across the retina—is used to control body position. We filmed hummingbirds hovering in front of a projection screen with the prediction that projecting moving patterns would disrupt hovering stability but stationary patterns would allow the hummingbird to stabilize position. When hovering in the presence of moving gratings and spirals, hummingbirds lost positional stability and responded to the specific orientation of the moving visual stimulus. There was no loss of stability with stationary versions of the same stimulus patterns. When exposed to a single stimulus many times or to a weakened stimulus that combined a moving spiral with a stationary checkerboard, the response to looming motion declined. However, even minimal visual motion was sufficient to cause a loss of positional stability despite prominent stationary features. Collectively, these experiments demonstrate that hummingbirds control hovering position by stabilizing motions in their visual field. The high sensitivity and persistence of this disruptive response is surprising, given that the hummingbird brain is highly specialized for sensory processing and spatial mapping, providing other potential mechanisms for controlling position.

opencc-zeroDec 2014View details →
ClinicalTrials.gov28/100

Sensory Training for Visual Motion Sickness

ClinicalTrials.gov study NCT04420949. IPD Sharing: NO. Countries: 1. Publications: 0.

closedIPD-NOFeb 2026View details →
dryad28/100

Data from: Lesions to right posterior parietal cortex impair visual depth perception from disparity but not motion cues

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publicApr 2017View details →
dryad28/100

Data from: Hummingbirds control hovering flight by stabilizing visual motion

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publicNov 2015View details →
dryad28/100

Data from: Direct evidence for encoding of motion streaks in human visual cortex

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publicMar 2013View details →
dryad28/100

Data from: Do perceptual biases emerge early or late in visual processing? Decision-biases in motion perception

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publicMay 2016View details →
dryad28/100

Data from: Cross-modal influence of mechanosensory input on gaze responses to visual motion in Drosophila

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publicApr 2018View details →
geo24/100

A combinatorial code of transcription factors specifies subtypes of visual motion-sensing neurons in Drosophila

GEO Series GSE147987. Drosophila melanogaster. 10 samples. Type: Expression profiling by high throughput sequencing.

openGEO-OpenApr 2020View details →
zenodo24/100

Data from Schmitt et al. 2018: Preattentive and Predictive Processing of Visual Motion

<p><strong>Dataset associated with the following publication:</strong></p> <p>Schmitt C, Klingenhoefer S, Bremmer F. Preattentive and Predictive Processing of Visual Motion. <em>Sci Rep</em>. 2018;8(1):12399. Published 2018 Aug 17. doi:10.1038/s41598-018-30832-9</p> <p><strong>Description of dataset:</strong></p> <p>The dataset contains preprocessed EEG data recorded from the 15 electrodes (Cz, Fz, FCz, FC1, FC2, F3, F4, FC5, FC6, P3, P4, P7, P8, PO3, PO4) used for analysis in our paper. Data containing eye movements, blinks or a movement response of the participants were removed. As a reference the average signal of the mastoid electrodes TP9 and TP10 was used.</p> <p>In a first preporcessing step data were low pass filtered with a cut-off frequency of 70 Hz and additionally a Notch filter at 50 Hz was applied. In a second step data were aligned to the (re)appearance of the moving target next to the central occluder and cut into 850 ms long epochs ranging from 200 ms before this (re)appearance to 650 ms after this time point. The average signal from a 50 ms long time window starting 50 ms before the (re)appearance was used for a baseline correction of each epoch before epochs were averaged separately for subjects and conditions as a last preprocessing step.&nbsp; &nbsp;</p> <p>Each uploaded file contains data of all 8 participants and all 15 electrodes separately for the four different conditions: 1) target movement to the right in complete trajectory trails (data_movedirR_complete_trajectory.mat); 2) target movement to the left in complete trajectory trails (data_movedirL_complete_trajectory.mat); 3) target movement to the right in half trajectory trails (data_movedirR_half_trajectory.mat); 4) target movement to the left in half trajectory trails (data_movedirL_half_trajectory.mat).</p> <p>Each file contains 30 matrices for the half trajectory conditions and 60 matrices for the complete trajectory conditions. Each matrix presents the data recorded at one electrode, for one type of trial (standard &quot;AllS&quot;, deviant &quot;AllD&quot; or half trajectory &quot;AllH&quot;) and one attention condition (attention to the fixation target, central &quot;1&quot; and attention to the moving target, peripheral &quot;2&quot;). Example: &quot;P3_AllD_1&quot;</p> <p>Each matrix consists of 8 lines representing the 8 participants. Data for the relevant condition was averaged for each participant and is presented in a separate line. The matrices consist of 850 columns representing the length of the presented recording time of 850 ms. Data from 200 ms before to 650 ms after the (re)appearance of the moving target is presented. The uploaded matrices contain values in&nbsp;&micro;V.</p>

opencc-by-4.0Jun 2020View details →
dryad24/100

Data from: Stronger neural modulation by visual motion intensity in autism spectrum disorders

Theories of autism spectrum disorders (ASD) have focused on altered perceptual integration of sensory features as a possible core deficit. Yet, there is little understanding of the neuronal processing of elementary sensory features in ASD. For typically developed individuals, we previously established a direct link between frequency-specific neural activity and the intensity of a specific sensory feature: Gamma-band activity in the visual cortex increased approximately linearly with the strength of visual motion. Using magnetoencephalography (MEG), we investigated whether in individuals with ASD neural activity reflect the coherence, and thus intensity, of visual motion in a similar fashion. Thirteen adult participants with ASD and 14 control participants performed a motion direction discrimination task with increasing levels of motion coherence. A polynomial regression analysis revealed that gamma-band power increased significantly stronger with motion coherence in ASD compared to controls, suggesting excessive visual activation with increasing stimulus intensity originating from motion-responsive visual areas V3, V6 and hMT/V5. Enhanced neural responses with increasing stimulus intensity suggest an enhanced response gain in ASD. Response gain is controlled by excitatory-inhibitory interactions, which also drive high-frequency oscillations in the gamma-band. Thus, our data suggest that a disturbed excitatory-inhibitory balance underlies enhanced neural responses to coherent motion in ASD.

opencc-zeroDec 2014View details →
ClinicalTrials.gov24/100

Real-time Motion Capture and Visual Feedback for Amputation Gait Training

ClinicalTrials.gov study NCT07049198. IPD Sharing: Not stated. Countries: 1. Publications: 0.

restrictedIPD-UNDECIDEDFeb 2026View details →
ClinicalTrials.gov24/100

Validation of Methods for Evaluating Operation Force, Motion and Visual Perception in Weightlessness

ClinicalTrials.gov study NCT02508558. IPD Sharing: Not stated. Countries: 1. Publications: 0.

restrictedIPD-UNDECIDEDFeb 2026View details →
ClinicalTrials.gov24/100

Longitudinal Strain in Addition to Visual Assessment of Wall Motion for Ruling in Ischemia in the Emergency Room

ClinicalTrials.gov study NCT01111643. IPD Sharing: Not stated. Countries: 1. Publications: 0.

restrictedIPD-UNDECIDEDFeb 2026View details →
ClinicalTrials.gov24/100

Accuracy of Visual Range of Motion Estimates

ClinicalTrials.gov study NCT04038450. IPD Sharing: NO. Countries: 1. Publications: 0.

closedIPD-NOFeb 2026View details →
ClinicalTrials.gov24/100

Exploring the Effect of Visual Feedback on Motion Trajectory in a Virtual Reality Environment.

ClinicalTrials.gov study NCT04103957. IPD Sharing: Not stated. Countries: 1. Publications: 0.

restrictedIPD-UNDECIDEDFeb 2026View details →
ClinicalTrials.gov24/100

Human Visual and Vestibular Motion Perception Study

ClinicalTrials.gov study NCT04142697. IPD Sharing: YES. Countries: 1. Publications: 0.

controlledIPD-YESFeb 2026View details →

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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.

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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