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213
datasets available to search
ShareScore release 0.9.0
Dataset results
213 results for “neural activity”
Identification of Hr38 as a neural activity-induced gene
GEO Series GSE39306. Bombyx mori. 10 samples. Type: Expression profiling by array.
Neural Network for Determination of the Substrate Activation in Enzymes
<p>1. Multiwfn_lap.sh -- a Linux script to run calculation of the Laplacian of electron density grid in the plain of a nucleophile atom and a carbonyl group. </p> <p>2. lapZero150DPI.py - a Python script for visualization of the 2D Laplacian of the electron density map</p> <p>3. crop_image.py - a Python script that crops the image </p> <p>4. 2500_crop_dataset_MolInf.ipynb - a Python notebook that trains the CNN with the dataset_crop_2500-MolInf </p> <p>5. dataset_crop_2500-MolInf.7z - a dataset to train the CNN</p> <p>6. model_crop_2500-MolInf.h5 - trained CNN, ready for utilization </p> <p>7. validation_datasets.zip -- an archive that includes additional datasets for the neural network validation (complexes of the Mpro with substrates containing Ser, Thr and Pro at P2 and a complex of the NDM-1 and imipenem)</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>
Activation of Hedgehog Signaling Promotes Development of Mouse and Human Enteric Neural Crest Cells, Based on Single-Cell Transcriptome Analyses
<p>the key data in our paper "Activation of Hedgehog Signaling Promotes Development of Mouse and Human Enteric Neural Crest Cells, Based on Single-Cell Transcriptome Analyses"</p>
Med-ReLU: A Hybrid Activation Function Tailored for Deep Artificial Neural Networks in Medical Image Segmentation without Parameter Tuning
<p>Background: Deep learning (DL) is derived from the domain of Artificial Neural Network (ANN). It makes one of the most important elements of deep learning algorithms. Deep learning segmentation models are based on layer-by-layer convolution learning attribute representation directed by forward and backward propagation. Throughout the process vital role is played by appropriately chosen activation function (AF) in order to guarantee the robustness of the model learning. However, the existing activation functions are either ineffective in addressing the vanishing gradient problem or get burdened with multiple parameters that need to be manually tuned. Moreover, the current research on activation function design mainly focuses on classification tasks using natural images from the MNIST, CIFAR-10 and CIFAR-100 datasets. Therefore,Med-ReLU as a novel activation function for medical image segmentation, is proposed. The proposed activation function avoids deep learning models from the attacks of dead neurons or from the vanishing gradient problems. Method: Med-ReLU is a hybrid activation function that combines the property of two activation functions of ReLU and Softsign. For positive inputs, Med-ReLU utilizes the linear property just like ReLU to produce an output without vanishing gradient. The negative inputs converge in polynomial ways towards their asymptotes as property of the softsign AF that ensures robust training processing without the problem of dead neurons that rarely activate across the entire training dataset. Results: The training performance and segmentation accuracy of Med-ReLU have been investigated. The proposed function has demonstrated stable training and does not suffer from over-fitting. Hence, Med-ReLU has consistently outperformed the existing state-of-art activation functions in medical image segmentation tasks. Conclusion: Med-ReLU has been designed as a parameter-free activation function for DL image segmentation tasks. This activation function is easy-to-implement on complex and deep learning models. The utility of this research lies in affirming the impact of Med-ReLU on different Artificial Neural Network architectures and for various kinds of anomaly addressing tasks.</p>
Neural Mobilization With Task Based Activities on Upper Limb in Patients With Chronic Stroke.
ClinicalTrials.gov study NCT06131827. IPD Sharing: NO. Countries: 1. Publications: 0.
Effects of rTMS Based on Neural Activation in Language Performance in Stroke Patients With Non-fluent Aphasia
ClinicalTrials.gov study NCT02591719. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Examining the Neural Effects of a Behavioral Intervention for Physical Activity in Multiple Sclerosis
ClinicalTrials.gov study NCT04496804. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Neural Activation and Connectivity in Response to Exercise and Cognitive Training
ClinicalTrials.gov study NCT01603771. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Transduction of Sympathetic Neural Activity in Human Obesity Without Hypertension
ClinicalTrials.gov study NCT06626113. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Shaping Neural Activity Through Parenting
ClinicalTrials.gov study NCT02667522. IPD Sharing: UNDECIDED. Countries: 1. Publications: 0.
Investigation of the Changes of Brain Structure and Function in Premature Ejaculation Patients and the Effects of Dapoxetine on Central Neural Activity in Premature Ejaculation Patients
ClinicalTrials.gov study NCT03583112. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Functional Near-Infrared Spectroscopy (fNIRS) Assessing Neural Activity During Virtual Reality Walking Intervention
ClinicalTrials.gov study NCT06276894. IPD Sharing: NO. Countries: 1. Publications: 0.
Using Perfusion MRI to Measure the Dynamic Changes in Neural Activation Associated With Caloric Vestibular Stimulation
ClinicalTrials.gov study NCT01659073. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Effects of PFC tDCS on Cognitive Control, Attention Lapses and Coordinated Neural Activity in the Theta and Alpha Bands
ClinicalTrials.gov study NCT04885322. IPD Sharing: NO. Countries: 1. Publications: 0.
Neural Activations During Imaginal Exposure in Individuals Fearful of Spiders
ClinicalTrials.gov study NCT03969160. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Coupling of Neural Activity and Retinal Blood Flow in Diabetes
ClinicalTrials.gov study NCT01375166. IPD Sharing: Not stated. Countries: 1. Publications: 0.
SALL4 recruits BAF to activate enhancers required for cranial neural crest cell specification
GEO Series GSE293821. Homo sapiens. 26 samples. Type: Expression profiling by high throughput sequencing; Genome binding/occupancy profiling by high throughput sequencing.
Stra8, an Activity-Dependent Modulator of Neural Circuit, Safeguards Neuronal Integrity
GEO Series GSE274976. Mus musculus. 4 samples. Type: Expression profiling by high throughput sequencing.
Loss of PRC2 enforces a mesenchymal neural crest stem cell phenotype in NF1-deficient cancer through activation of core transcription factors [single-cell RNA-seq]
GEO Series GSE183308. Homo sapiens. 17 samples. Type: Expression profiling by high throughput sequencing.
ScienceDex guides
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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.