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datasets available to search
ShareScore release 0.9.0
Dataset results
52 results for “Sensory System”
Data from: Sensory evolution of hearing in tettigoniids with differing communication systems
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Data from: Information content is more important than sensory system or physical distance in guiding the long-term evolutionary relationships between signaling modalities in Sceloporus lizards
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Data from: Fine-scale analysis of an assassin bug's behaviour: predatory strategies to bypass the sensory systems of prey
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Sensory neuron lineage mapping and manipulation in the Drosophila olfactory system
GEO Series GSE113997. Drosophila melanogaster. 8 samples. Type: Expression profiling by high throughput sequencing.
Lack of single amino acids transcriptionally tunes sensory systems to enhance microbiota intake
GEO Series GSE270723. Drosophila melanogaster. 1 samples. Type: Expression profiling by high throughput sequencing.
A Glycolytic Shunt via the Pentose Phosphate Pathway is a Metabolic Checkpoint for Nervous System Sensory Homeostasis and Axonal Regeneration
GEO Series GSE299441. Mus musculus. 12 samples. Type: Expression profiling by high throughput sequencing.
Single-cell chromatin conformation capture of mouse sensory neurons in visual and olfactory systems by Dip-C
GEO Series GSE121791. Mus musculus. 409 samples. Type: Other.
Quantifying the Role of Sensory Systems Processing in Post-Stroke Walking Recovery
ClinicalTrials.gov study NCT04553198. IPD Sharing: NO. Countries: 1. Publications: 0.
Piezo2 in sensory neurons regulates systemic and adipose tissue metabolism
GEO Series GSE256369. Mus musculus. 20 samples. Type: Expression profiling by high throughput sequencing.
The microRNA miR-124 controls gene expression in the sensory nervous system of Caenorhabditis elegans
GEO Series GSE16050. Caenorhabditis elegans. 12 samples. Type: Expression profiling by array.
Designing Multi-Sensorial Information Systems: a Dual Case-Study
<p>Replication package and dataset for the paper: Designing Multi-Sensorial Information Systems: a Dual Case-Study</p>
Clinical assessment of the TechArm system on visually impaired and blind children during uni- and multi-sensory perception tasks
<p>Introduction</p> <p>This dataset includes the raw data linked with the paper “Clinical assessment of the TechArm system on visually impaired and blind children during uni- and multi-sensory perception tasks ”.</p> <p>In this paper, we validated the TechArm system on a pediatric population of visually impaired (low-vision and blind), and sighted children.</p> <p>Raw data concerning sighted children are collected in the first sheet, while raw data for visually impaired children are in the second sheet. Encoding is available in the third sheet.</p> <p>Methods</p> <p>8 blind children (B, mean age 10.50 ± 4.21 y.o.), 23 children with low vision (LV, mean age 92 9.87 ± 3.09 y.o.), and 23 age-matched sighted children (S, mean age 9.83 ± 3.01 y.o.) were enrolled in the study. Four TechArm units were used to deliver uni- (audio or tactile) or multi-sensory stimulation (audio-tactile) on the participant’s arm, and subject was asked to evaluate the number of active units (see Martolini et al, Brain Sciences, 2021 for a presentation of the protocol).</p> <p>Results (in brief)</p> <p>Results showed no significant difference among groups (normal or impaired vision). Overall, we observed the best performance in tactile condition, while auditory accuracy was around chance level. Also, we found that the audio-tactile condition is better than the audio condition alone, suggesting that multisensory stimulation is beneficial when perceptual accuracy and precision are low. Interestingly, we observed that for low-vision children the accuracy in audio condition improved proportionally to the severity of the visual impairment. Our findings confirmed the TechArm system's effectiveness in assessing perceptual competencies in sighted and visually impaired children, and its potential to be used to develop personalized rehabilitation programs for people with visual and sensory impairments.</p>
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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.
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.