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199
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ShareScore release 0.9.0
Dataset results
199 results for “Active Learning”
Data from: Evaluating active learning methods for annotating semantic predications
Open the record for dataset details and reuse information.
Data from: Dopamine promotes motor cortex plasticity and motor skill learning via PLC activation
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Machine learning identifies activation of RUNX/AP-1 as drivers of mesenchymal and fibrotic regulatory programs in gastric cancer
GEO Series GSE264550. Homo sapiens. 25 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
Activation of a Hippocampal CREB-pCREB-miRNA-MEF2 Axis Modulates Individual Variation of Spatial Learning and Memory Capability
GEO Series GSE180203. Mus musculus. 4 samples. Type: Non-coding RNA profiling by array.
Machine learning identifies activation of RUNX/AP-1 as drivers of mesenchymal and fibrotic regulatory programs in gastric cancer (RNA-Seq)
GEO Series GSE266159. Homo sapiens. 13 samples. Type: Expression profiling by high throughput sequencing.
Active learning of enhancer and silencer regulatory grammar in photoreceptors
GEO Series GSE241353. Escherichia coli; Mus musculus. 42 samples. Type: Expression profiling by high throughput sequencing.
How do table shape, group size, and gender affect on-task actions in collaborative learning activities? - Qualitative data
<p>Qualitative data set for the ijCSCL journal paper " <strong>How do table shape, group size, and gender affect on-task actions in collaborative learning activities?</strong> "</p>
Active garment recognition and target grasping point detection using deep learning
<p>Data used in the experiments of the research paper</p> <p>E. Corona, G. Alenyà, T. Gabas, and C. Torras, “Active garment recognition and target grasping point detection using deep learning,” Pattern Recognition, vol. 74, pp. 629–641, 2018. </p>
Neural activity ramps in frontal cortex signal extended motivation during learning
<p>Learning requires the ability to link actions to outcomes. How motivation facilitates learning is not well understood. We designed a behavioral task in which mice self-initiate trials to learn cue-reward contingencies and found that the anterior cingulate region of the prefrontal cortex (ACC) contains motivation-related signals to maximize rewards. In particular, we found that ACC neural activity was consistently tied to trial initiations where mice seek to leave unrewarded cues to reach reward-associated cues. Notably, this neural signal persisted over consecutive unrewarded cues until reward associated cues were reached, and was required for learning. To determine how ACC inherits this motivational signal we performed projection specific photometry recordings from several inputs to ACC during learning. In doing so, we identified a ramp in bulk neural activity in orbitofrontal cortex (OFC) -to-ACC projections as mice received unrewarded cues, which continued ramping across consecutive unrewarded cues, and finally peaked upon reaching a reward associated cue, thus maintaining an extended motivational state. Cellular resolution imaging of OFC confirmed these neural correlates of motivation, and further delineated separate ensembles of neurons that sequentially tiled the ramp. Together, these results identify a mechanism by which OFC maps out task structure to convey an extended motivational state to ACC to facilitate goal-directed learning.</p>
Training Skills in Minimally Invasive, Robotic and Open Surgery: Brain Activation as an Opportunity for Learning
<p>The advantages of the robotic approach in surgery are undisputed. However, during surgical training, how this technique influences the learning curve has not been described. We provide a tentative model for analyzing the learning curves associated with observation and active participation in learning different surgical techniques, using functional imaging. Forty medical students were enrolled and assigned to 4 groups who underwent training in robotic (ROB), laparoscopic (LAP), or open (OPEN) surgery, and a control group that performed motor training without surgical instruments. Surgical/motor training included six 1-h sessions completed over 6 days of the same week. All subjects underwent functional magnetic resonance imaging (fMRI) scanning sessions, before and after surgical training during. Twenty-three participants completed the study. The 3 surgical groups exhibited different learning curves during training. The main effects of the day of training (<em>p</em> < 0.01) and the group (<em>p</em> < 0.01) as well as a significant interaction of day of training group (<em>p</em> < 0.01) were observed. The performance increased in the first 4 days, reaching a peak at day 4, when all groups were considered together. The OPEN group showed the best performance compared to all other groups (<em>p</em> < 0.04). The OPEN group showed a rapid improvement in performance, which peaked at day 4 and decreased on the last day. Similarly, the LAP group showed a steady increase in the number of exercises they completed, which continued for the entire training period and reached a peak on the last day. However, the participants training in ROB surgery, after a performance initially indistinguishable from that of the LAP group, had a dip in their performance, quickly followed by an improvement and reaching a plateau on day 4. fMRI analysis documented the different involvement of the cortical and subcortical areas based on the type of training. Surgical training modified the activation of some brain regions during both observation and the execution of tasks. Differences in the learning curves of the 3 surgical groups were noted. Functional brain activity represents an interesting starting point to guide training programs.</p>
Source Data for the publication: Multi-omics and machine learning reveal context-specific gene regulatory activities of PML::RARA in Acute Promyelocytic Leukemia
<p>Source Data for the publication: Multi-omics and machine learning reveal context-specific gene regulatory activities of PML::RARA in Acute Promyelocytic Leukemia</p>
Uncertainty Driven Dynamics for Active Learning of Interatomic Potentials. Glycine and Acetylacetone Data.
<p>Data generated and analyzed in <strong>M.Kulichenko <em>et. al</em>. Uncertainty Driven Dynamics for Active Learning of Interatomic Potentials. <em>Nat. Comput. Sci </em>(2023).</strong></p> <ul> <li>Glycine data sets (MD-AL and UDD-AL).</li> <li>Acetylacetone MD and UDD trajectories.</li> <li>See README.md for details.</li> </ul> <p> </p> <p> </p> <p> </p>
Preschoolers Learning and Active in PlaY
ClinicalTrials.gov study NCT03279926. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Effects on Emphathy in Physiotherapy Students After Simulation as an Active Method for Learning the Clinical Enterview
ClinicalTrials.gov study NCT05873179. IPD Sharing: NO. Countries: 1. Publications: 0.
Development and Validation of a Deep Learning Algorithm to Evaluate Endoscopic Disease Activity of Ulcerative Colitis.
ClinicalTrials.gov study NCT03973437. IPD Sharing: YES. Countries: 1. Publications: 0.
Preschoolers Learning and Active in PLAY (PLAY Extension)
ClinicalTrials.gov study NCT04772638. IPD Sharing: NO. Countries: 1. Publications: 0.
Effectiveness of Integrating Physically Active Learning Through Co-teaching in Extremadura: ACTIVA-MENTE Project
ClinicalTrials.gov study NCT06590103. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Effects on Anxiety in Physiotherapy Students After Simulation as an Active Method for Learning the Clinical Enterview
ClinicalTrials.gov study NCT05866601. IPD Sharing: NO. Countries: 1. Publications: 0.
Active Learning and EBP Competency in Undergraduate Physiotherapy
ClinicalTrials.gov study NCT06945367. IPD Sharing: NO. Countries: 1. Publications: 0.
A Study to Learn About the Study Medicine (PF-06823859) in Adults With Active CLE or SLE With Skin Symptoms.
ClinicalTrials.gov study NCT05879718. IPD Sharing: YES. Countries: 4. 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.