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362 results for “risk analysis”
Materials for "Poor nutritional condition promotes high-risk behaviours: A systematic review and meta-analysis"
<p>This contains a permanent record of dataset and analysis code for the study:</p> <p>Moran, N. P., Sánchez‐Tójar, A., Schielzeth, H., & Reinhold, K. (2021). Poor nutritional condition promotes high‐risk behaviours: a systematic review and meta‐analysis. <em>Biological Reviews</em>, <em>96</em>(1), 269-288.</p> <p>Full data analysis records are available on https://osf.io/3tphj/</p> <p>This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 836937. Also, this research was funded by the German Research Foundation (DFG) as part of the SFB TRR 212 (NC³) – Project numbers 316099922 and 396782608.</p>
Clinical evidence for high-risk CE-marked medical devices for glucose management: a systematic review and meta-analysis
<p><strong><span>Aims: </span></strong><span>High-risk medical devices are increasingly used in diabetes management, but<span><span> there are no specific European recommendations on how they should be evaluated. Within</span></span> the Coordinating Research and Evidence for Medical Devices (CORE-MD) project, we conducted a systematic review and meta-analysis evaluating CE-marked high-risk devices for glucose management. </span></p> <p><strong><span>Materials and Methods: </span></strong><span>We<span> identified interventional and observational studies evaluating the </span>efficacy and safety of 8 automated insulin delivery (AID) systems, 2 implantable insulin pumps, and 3 implantable continuous glucose monitoring (CGM) devices.<span> </span></span><span>We meta-analysed randomized controlled trials (RCTs) comparing AID systems with other treatments.</span></p> <p><strong><span>Results:</span></strong><span> 99 studies published from 2009–2022 were included, comprising 83 on AID systems, 6 on insulin pumps, and 10 on CGM; 43% reported industry funding;30% were pre-market; 45% had a comparator group. 33% were RCTs, 25% non-randomized trials, and 41% observational studies. Median sample size was 52 (interquartile range 25–111), age 37.8 years (17–45.5), and study duration 13 weeks (4.5–26). AID systems lowered HbA1c by 0.3 percentage points (absolute mean difference [MD]=-0.3; 9 RCTs; I<sup>2</sup>=85%) and increased time in target range for sensor glucose level by 10.5 percentage points (MD=10.5; 14 RCTs; I<sup>2</sup>=89%). 69% of studies reported on at least one safety outcome.</span></p> <p><strong><span>Conclusions:</span></strong><span> High-risk devices for glucose monitoring or insulin dosing, in particular AID systems, improve glucose control safely but evidence on diabetes-related end organ damage is lacking due to short study durations. Methodological heterogeneity highlights the need for d<span><span>eveloping standards for future pre- and post-market investigations of diabetes-specific high-risk medical devices.</span></span></span></p>
Data and analysis for: "Persistent Spatial Clustering and Predictors of Pediatric La Crosse Virus Neuroinvasive Disease Risk in Eastern Tennessee and Western North Carolina, 2003–2020"
<p>This is the initial release of the data and code corresponding to the manuscript submitted to PLoS Neglected Tropical Diseases. <strong>Please refer to the README.md file</strong> for a description of the contents of this repository and how to use them. The README file can be opened with a text editor, or viewed directly in the GitHub repository. The data and code are provided within a project directory with a reproducible R package library for ease and accuracy of reproducibility. </p> <p><strong>Ethics Approval</strong></p> <p>This study was approved by the University of Tennessee, Knoxville Institutional Review Board (UTK IRB-22-07079-XP) and the Tennessee Department of Health Institutional Review Board (TDH IRB 2021-0314). Data provided here is de-identified and aggregated (both temporally and spatially) to protect the privacy of individuals included in the study, in concordance with IRB and Data Use Agreements.</p>
Local risks from Arctic permafrost thaw – Results from a transdisciplinary, comparative analysis
<p>This dataset underpins the findings of a transdisciplinary and comparative assessment of permafrost thaw risks across four distinct Arctic regions: Longyearbyen (Svalbard, Norway), the Avannaata Municipality (Greenland), the Beaufort Sea region and Mackenzie River Delta (Canada), and the Bulunskiy District of the Sakha Republic (Yakutiya, Russia). Information on permafrost thaw risks was gathered from multiple disciplines and stakeholders over a five-year period from 2019 to 2023, and classified via thematic network analysis (Attride-Stirling, 2001). The identified risks were subsequently verified and ranked by scientists and local experts through an iterative process and a series of workshops (see Ingeman-Nielsen et al., 2024 in Related Works).</p> <p>The dataset contains the results of the thematic network analysis and ranking of permafrost thaw risks specific to each Arctic region. Provided as an .xlsx file, it consists of six main sheets comprising the following information:</p> <ul> <li>Global theme - Physical Processes</li> <li>Ranking - Physical Processes</li> <li>Global theme - Key Hazards</li> <li>Global theme - Societal Consequences</li> <li>Ranking - Consequences</li> <li>List of Actions Needed</li> </ul> <p>Additional details about the methodological approach and dataset can be found in the accompanying README document.</p> <p> </p>
Data associated with the article 'Intervention factors associated with efficacy, when targeting oral language comprehension of children with or at risk for (Developmental) Language Disorder: A meta-analysis'
<p>The efficacy of oral language comprehension interventions varies, but the reasons for this variation have received little attention. A meta-analysis was conducted to examine intervention factors associated with the efficacy (as expressed with effect sizes) of oral language comprehension interventions in children under the age of 18 with or at risk for (Developmental) Language Disorder, (D)LD.</p> <p>The meta-analysis article together with this additional material comprise the content needed for a thorough understanding and replication of the results.</p> <p>This dataset is based on two systematic scoping reviews on oral language comprehension interventions (Tarvainen et al., 2020, 2021). Further information from the sourced articles was extracted for this study titled ‘Intervention factors associated with efficacy, when targeting oral language comprehension of children with or at risk for (Developmental) Language Disorder: A meta-analysis’. </p> <p>In the future, we hope that this data is used with a growing body of oral language comprehension interventions to conduct further and more detailed examinations of intervention factors associated with efficacy.</p> <p>References:</p> <p>Tarvainen, S., Launonen, K., & Stolt, S. (2021). Oral language comprehension interventions in school-age children and adolescents with developmental language disorder: A systematic scoping review. <em>Autism & Developmental Language Impairments</em>, <em>6</em>, 1–24. https://doi.org/10.1177/23969415211010423</p> <p>Tarvainen, S., Stolt, S., & Launonen, K. (2020). Oral language comprehension interventions in 1–8-year-old children with language disorders or difficulties: A systematic scoping review. <em>Autism & Developmental Language Impairments</em>, <em>5</em>, 1–24. https://doi.org/10.1177/2396941520946</p> <p> </p>
RICCH: An Interactive Analysis Tool for Risk and Impacts of Climate Change on Hydropower Database
<p>The "RICCH: An Interactive Analysis Tool for Risk and Impacts of Climate Change on Hydropower" Database, referred to as the RICCH Database, includes a "Hydropower Plants Database" and the incorporation of future hydropower usable capacity for 542 hydropower plants in the Global South. The "Hydropower Plants Database" includes the main design and location characteristics of 542 hydropower plants across 52 countries. Additionally, we incorporate the results of future usable capacity simulations using a multi-model ensemble of 21 Global Climate Models (GCMs) and two representative concentration pathways (RCPs). We use a multi-model ensemble of 21 GCMs from NASA's NEX GDDP dataset RCP 4.5 and RCP 8.5. We aggregate the mean monthly usable capacity (MW) for each model and scenario, for the early century (2010-2039), mid-century (2040-2069), and the end-of-the-century (2070-2099). We include these results for every power plant in the RICCH database. </p> <p><em>Example: Itaipu (power plant in Brazil) has a record for its simulated mean monthly usable capacity for January (1) in the early century (2010-2039), under GCM ACCESS1_0 and RCP 4.5.</em></p>
Van Dijk et al. (2021), A meta-analysis of projected global food demand and population at risk of hunger for the period 2010–2050, data and scripts
<p>This repository contains all data and R scripts to reproduce the figures in Van Dijk et al. (2021), A meta-analysis of global food demand and population at risk of hunger projections for the period 2010-2050, Nature Food. More specifically, it includes two databases: (1) A database with standardized information to describe the characteristics of 57 studies that were identified by the systematic literature review and (2) The Global Food Security Projections Database v1.0.1 with harmonized projections for three global food security indicators: food consumption in kcal per capita and total kcal, and population at risk of hunger. The database also includes projections for total global population that are required to derive the global food security indicators.</p> <p>The two scripts (nf_figures.r and nf_meta_regression.r) can be used to reproduce the figures and tables in the main paper and the supplementary information. Please start with the first script, which sources the second script. </p> <p>This is the first version of the Global Food Projections Database. We expect to update the data, including additional studies and variables in the future. For issues and suggestions, please contact michiel.vandijk@wur.nl.</p> <p> </p>
A common NFKB1 variant detected through antibody analysis in UK Biobank predicts risk of infection and allergy: Summary statistics - Health records
<p>Infectious agents contribute significantly to the global burden of diseases, through both acute infection and their chronic sequelae. We leveraged the UK Biobank to identify genetic loci that influence humoral immune response to multiple infections. From 45 genome-wide association studies in 9,611 participants from UK Biobank, we identified NFKB1 as a locus associated with quantitative antibody responses to multiple pathogens including those from the herpes, retro- and polyoma-virus families. An insertion-deletion variant thought to affect NFKB1 expression (rs28362491), was mapped as the likely causal variant. This variant has persisted throughout hominid evolution and could play a key role in regulation of the immune response. Using 121 infection and inflammation related traits in 487,297 UK Biobank participants, we show that the deletion allele was associated with an increased risk of infection from diverse pathogens but had a protective effect against allergic disease. We propose that altered expression of NFKB1, as a result of the deletion, modulates haematopoietic pathways, and likely impacts cell survival, antibody production, and inflammation. Taken together, we show that disruptions to the tightly regulated immune processes may tip the balance between exacerbated immune responses and allergy, or increased risk of infection and impaired resolution of inflammation. </p> <p>-------------------------------------------------------------------------------------</p> <p>This dataset contains GWAS summary statistics for infection, inflammation, and allergy related traits in 487,297 individuals</p>
A common NFKB1 variant detected through antibody analysis in UK Biobank predicts risk of infection and allergy: Summary statistics - Serology
<p>Infectious agents contribute significantly to the global burden of diseases, through both acute infection and their chronic sequelae. We leveraged the UK Biobank to identify genetic loci that influence humoral immune response to multiple infections. From 45 genome-wide association studies in 9,611 participants from UK Biobank, we identified NFKB1 as a locus associated with quantitative antibody responses to multiple pathogens including those from the herpes, retro- and polyoma-virus families. An insertion-deletion variant thought to affect NFKB1 expression (rs28362491), was mapped as the likely causal variant. This variant has persisted throughout hominid evolution and could play a key role in regulation of the immune response. Using 121 infection and inflammation related traits in 487,297 UK Biobank participants, we show that the deletion allele was associated with an increased risk of infection from diverse pathogens but had a protective effect against allergic disease. We propose that altered expression of NFKB1, as a result of the deletion, modulates haematopoietic pathways, and likely impacts cell survival, antibody production, and inflammation. Taken together, we show that disruptions to the tightly regulated immune processes may tip the balance between exacerbated immune responses and allergy, or increased risk of infection and impaired resolution of inflammation. </p> <p>-------------------------------------------------------------------------------------</p> <p>This dataset contains GWAS summary statistics for quantitative antibody responses in 9611 individuals and results for a meta-analysis of UK Biobank and CoLaus/PsyCoLaus antibody responses.</p> <p> </p>
A Tool for Uncertainty Quantification in Reconstructing Sparse Water Quality Time Series Data to Assess Risk Metrics for Watershed Health and TMDL Analysis
<p>The uploaded file contains the input and output data which can be used to reproduce the results in the research article 'Uncertainty Quantification in Reconstruction of Sparse Water Quality Time Series: Implications for Watershed Health and Risk-Based TMDL Assessment'. Please refer to the file '<a href="https://zenodo.org/api/files/31b59cce-8eb2-4ee7-93aa-61474c6f6359/dst_2019_SJRW_TP_TDS.zip?versionId=2af2b54d-d5fb-4720-919d-de2e827595e2">dst_2019_SJRW_TP_TDS.zip'</a> for updated files..</p>
Simulated data used in "The importance of censoring in competing risks analysis of the subdistribution hazard"
<p>The simulated data used for analysis in "The importance of censoring in competing risks analysis of the subdistribution hazard". Simulated using the method described in Additional file 1.<br> <br> <strong>Warning: Large file.</strong> Contains 1000 datasets of 300 observations each, for each of 105 parameter combinations (31,500,000 rows). Some programs (e.g. Excel) will not be able to open it in full.</p> <p>csv file with columns:</p> <p><strong>p.comp:</strong> risk of the competing event in exposure group A for this scenario [0 to 0.30 in increments of 0.05]<br> <strong>lnb.cens:</strong> log(hazard ratio) for loss to follow-up in old versus young individuals for this scenario [0 to 1 in increments of 0.25]<br> <strong>lnb.evt:</strong> log(subdistribution hazard ratio) for the event of interest in exposure group B vs group A for this scenario [0, 0.5, 1]<br> <strong>sim:</strong> ID of the simulated dataset for this scenario [1-1000]<br> <strong>exposure:</strong> exposure group (0 = A, 1 = B) of this individual<br> <strong>age:</strong> age group (0 = young, 1 = old) of this individual<br> <strong>time:</strong> time-to-event or censoring for this individual<br> <strong>evtcode:</strong> event type (0 = censoring, 1 = event of interest, 2 = competing event)<br> <strong>censcode:</strong> type of censoring (1 = end-of-study, 2 = loss to follow-up)</p>
A meta-analysis on global change drivers and the risk of infectious disease database and code
<p>Data and code associated with the manuscript "A Meta-analysis on Global change drivers and the risk of infectious disease".</p>
Algae-Bacteria Community Analysis for Drinking Water Taste and Odour Risk Management
<p>The datasets and accompanying R script included in this upload are provided to complement the manuscript titled <em>"Algae-Bacteria Community Analysis for Drinking Water Taste and Odour Risk Management."</em> These resources are intended to facilitate the replication and verification of the analyses presented in the paper.</p> <p> </p> <p> </p>
Assessment of risk and vulnerability to disasters by field protocols and classification trees: an analysis of the Municipal Risk Reduction Plans (MRRP) of São Bernardo do Campo and Franco da Rocha (2020-2021), in Brazil
<p><span>Most disaster risk assessment methodologies were developed by natural science professionals. The UN Sendai Framework confirms the need to include these methods as interweaving complex networks of socially vulnerable financial processes, especially in developing countries. This work aimed to analyze the experience of including social vulnerability information in field protocols of the Municipal Risk Reduction Plans (MRRP) of São Bernardo do Campo and Franco da Rocha (2020-2021). A georeferenced database was structured with data from field protocols on risk sectors and then the relationship between vulnerability and risk was analyzed using the classification tree method. The results show that the geotechnical and social vulnerability variables relevant to risk attribution are largely overlapping over the sectors, but that the integrated analysis of the two dimensions allows a better interpretation of the risk level. However, the models with information from field protocols cannot replace a broader holistic assessment by the specialist in the field. Finally, qualitative reflections are made on the limitations and potential of including aspects of vulnerability in the specific case study.</span></p>
A Factor Analysis Model for Dimension Reduction of Outcome Factors in Neonatal Seizure Context-Figure 2. Identified risk factors hierarchy
<p>AED - antiepileptic drug, CP - cerebral palsy, GDD - global developmental delay, GA - gestational age, BW- birth weight, RS - repeated/recurrent seizure, MD - type/mode of delivery, AS1 - Apgar score at 1 minute, AS5 - Apgar score at 5 minute, AS10 - Apgar score at 10 minute, SO - seizure onset, ST_EPI - status epilepticus, UBS - ultrasound brain scan, MSU- maternal substance used, MIS – maternal inflammatory state, PRM- prolonged rupture of membranes, PNN – postnatal neuroimaging, PNS – postnatal seizure. The most frequently identified risk factors were the EEG findings (abnormal / severe electroencephalogram results), seizure characteristics (type, onset, duration, semiology), etiology, birth weight, Apgar score, cerebral ultrasound scan findings (abnormal) (Figure 2).</p>
Fig. 1 in Applying a modified streamlined disease risk analysis framework to a platypus conservation translocation, with special consideration for the conservation of ecto- and endoparasites
Fig. 1. An outline of how parasite conservation can be considered in translocation planning, reproduced from Carlson et al. (2020).
Deep Learning and Procrustes Analysis for Early Dysgraphia Risk Detection with a Tablet Application - DATASET
<p>Data to support the findings reported in the journal paper</p> <p>Lomurno, E., Dui, L. G., Gatto, M., Bollettino, M., Matteucci, M., & Ferrante, S. (2023). Deep Learning and Procrustes Analysis for Early Dysgraphia Risk Detection with a Tablet Application. <em>Life</em>, <em>13</em>(3), 598.</p> <ul> <li>Caratterizzazione_y3b_pulito.xls: <ul> <li>Subject ID</li> <li>Age at the beginning of the study</li> <li>Handedness</li> <li>Sex</li> </ul> </li> <li>Score_BVSCO_pulito.xls: <ul> <li>Subject ID</li> <li>columns B-D: graphemes in the three tests of the BVSCO-2</li> <li>columns E-G: z-score computed on normative data for the three tests of the BVSCO-2</li> <li>median z-score: computed on columns E-G</li> <li>at risk: if median z-score is under the -2 threshold (0=not at risk, 1=at risk)</li> </ul> </li> <li>executions.mat: a matrix for each time point (y1, y2a, y2b, y3a, y3b) and game (copa_q = copy square, copia_seq = copy sequence, tunnel_q = tunnel square, tunnel_ele = tunnel word). <ul> <li>first column of all the cell arrays: subject ID</li> <li>second column for the copy games: three sub-matrices with an execution for each level (spontaneous, big, small)</li> <li>columns 2:N for the tunnel games: an average execution for each index of difficulty</li> <li>for each execution, the columns of the sub-matrices are normalized time, normalized x, normalized y and pressure</li> </ul> </li> </ul> <p> </p> <p>Copy games</p> <ul> <li>A matrix for each game and each time point with a number of rows equal to the number of children and a number of columns equal to 2: <ul> <li>First column: array with school and child code</li> <li>Second column: executions</li> </ul> </li> <li>For the two copy games, the data has a dimension of 3 x 1, where 3 are the modalities (spontaneous, big, small) and 1 is the data matrix.</li> <li>By accessing the data matrix we have four variables, i.e., normalized time, normalized x, normalized y and pressure.</li> </ul> <p> </p> <p>Tunnel games</p> <ul> <li>A matrix for each game and each time point with a number of rows equal to the number of children and a number of columns equal to index of difficulty number +1: <ul> <li>First column: array with school and child code</li> <li>From the second column onwards: executions, each column corresponds to the "typical" execution (the average) of an ID (5 for square tunnel and 8 for ele tunnel). Sub-matrices contain the data matrix with its four variables. i.e., normalized time, normalized x, normalized y and pressure.</li> </ul> </li> </ul>
Occupational exposure to silica and risk of heart disease: a systematic review with meta-analysis
<p><b><span>Objective</span></b> To search for evidence of the relationship between occupational silica exposure and heart disease.</p> <p><b><span>Design</span></b> A systematic review and meta-analysis.</p> <p><b><span>Background</span></b> Growing evidences suggest a connection between occupational silica exposure and heart disease; however, the link between them is less clear.</p> <p><b><span>Data sources </span></b>PubMed, ScienceDirect, Springer and EMBASE were searched for articles published between 1 January 1995 and 20 June 2019. Articles that investigated the effects of occupational silica exposure on heart disease risk were considered.</p> <p><b><span>Study selection </span></b><span>We included c</span><span>ohort stud</span><span>ies</span>, including prospective, retrospective and retro-prospective studies.</p> <p><b><span>Data extraction and synthesis</span></b> We extracted data by using a piloted data collection form and conducted random-effects meta-analysis and exposure-response analyses. The meta-relative risk (meta-RR), a measure of the average ratio of heart disease rates for those with and without silica exposure, was used as an inverse variance-weighted average of relative risks from the individual studies. The Newcastle-Ottawa Quality assessment Scale about cohort studies was used for study quality assessment.</p> <p><b><span>Outcome measure</span></b> We calculated heart disease risks of pulmonary heart disease, ischaemic heart disease and other heart diseases.</p> <p><span><b><span>Results</span></b> Twenty cohort articles were included. Results suggest a significant increase of overall heart disease risk (meta-RR = 1.08, 95% CI = 1.03, 1.13). Stronger evidences of association with pulmonary heart disease were found through both categories of heart disease risk estimate (meta-RR = 1.24, 95% CI = 1.08, 1.43) and exposure-response analyses (meta-RR = 1.39, 95% CI = 1.19, 1.62). Moreover, our subgroup analyses revealed that the statistical heterogeneity among studies could be attributed mainly to the diversities of reference group, occupation and study quality score.</span></p> <p><b><span>Conclusions</span></b> Silica-exposed workers have increased risk of overall heart disease, especially pulmonary heart disease. While further research is needed to better clarify the relationship between occupational silica exposure and ischaemic heart disease.</p>
Genome-wide meta-analysis of short-tandem repeats for Parkinson's disease risk
<p>Idiopathic Parkinson's disease (PD) is the second most common neurodegenerative disease after Alzheimer's disease and is determined by a combination of genetic and environmental risk factors. The to date largest genome-wide association study (GWAS) on single nucleotide polymorphisms (SNPs) by Nalls at al., 2019, reported 90 SNPs that were independently associated with PD risk. However, common SNPs account only for 16-36% of the total genetic heritability of the disease suggesting that other genetic variants play a role in PD susceptibility. One example of previously understudied genetic variants are short-tandem repeats (STR, also known as microsatellites), i.e., repeating sequence motifs in the human genome of 1-6 nucleotides in length. Thus, in this study, we performed a GWAS on imputed STRs in a large PD case-control dataset (n=4,757), and meta-analyzed these data with those from a previous study of the International PD Genetics Consortium (Bustos et al., 2023) resulting in a total sample size of 43,844 PD cases and controls. Thus, in this study, we performed a GWAS on imputed STRs in a large PD case-control dataset (n=4,757) from the US (the PEG and a GHC-based study) and Denmark (PASIDA).</p>
Replication Package for "Beyond Words: On Large Language Models Actionability in Mission-Critical Risk Analysis"
<h1>Replication Package for the Paper: “Beyond Words: On Large Language Models Actionability in Mission-Critical Risk Analysis”</h1> <p>This replication package includes the raw data, questionnaire answers, and a Python notebook needed for reproducing the results detailed in the paper titled “Beyond Words: On Large Language Models Actionability in Mission-Critical Risk Analysis.”</p> <h2><a></a>Repository Structure</h2> <ol> <li><strong>Scenarios:</strong> Contains an Excel file encompassing all 141 scenarios collected (in Italian).</li> <li><strong>Training and Validation Messages:</strong> Includes the jsonl files necessary for fine-tuning the model.</li> <li><strong>Testing Messages and Ground Truth:</strong> Contains the messages utilized for testing the models.</li> <li><strong>Results:</strong> Contains Excel files with the responses from the 2 human experts and the 5 model as well as the review of the 3 human reviewer.</li> <li><strong>Tables:</strong> Contains the full Wilcoxon Test Results for H01 and H02 as well as the raw RQs results.</li> </ol> <h2><a></a>Replication Process</h2> <p>To replicate the results of our study, open the provided Python Notebook in Google Colab and follow the instructions to seamlessly reproduce the results.</p> <h1><a></a>Instructions for Use</h1> <p>To utilize this replicability package, refer to the steps outlined in the notebook file.</p> <h1><a></a>Remarks</h1> <p>If you encounter any issues or have any questions, please reach out to the authors of the paper. We will be glad to assist you!</p>
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.