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12,393 results for “Material”
Material Particulado de 10 estación Barrancas Guajira, Colombia
<p>Estación Barrancas, datos recopilados en SISAIRE IDEAM, para material particulado de 10 micras.</p>
Material Particulado de 2.5 estación Barrancas Guajira, Colombia
<p>Estación Barrancas, datos recopilados en SISAIRE IDEAM, para material particulado de 2.5 micras.</p>
Learning Dynamics of Electrophysiological Brain Signals During Human Fear Conditioning (Open Data and Open Materials)
<p><strong>Open Data and Open Materials of: Sperl, M. F. J., Wroblewski, A., Mueller, M., Straube, B., & Mueller, E. M. (2021). Learning Dynamics of Electrophysiological Brain Signals During Human Fear Conditioning. <em>NeuroImage</em>, <em>226</em>, 117569.</strong></p> <p>Electrophysiological studies in rodents allow recording neural activity during threats with high temporal and spatial precision. Although fMRI has helped translate insights about the anatomy of underlying brain circuits to humans, the temporal dynamics of neural fear processes remain opaque and require EEG. To date, studies on electrophysiological brain signals in humans have helped to elucidate underlying perceptual and attentional processes, but have widely ignored how fear memory traces <em>evolve</em> over time. The low signal-to-noise ratio of EEG demands aggregations across high numbers of trials, which will wash out transient neurobiological processes that are induced by learning and prone to habituation. Here, our goal was to unravel the plasticity and temporal emergence of EEG responses during fear conditioning. To this end, we developed a new sequential-set fear conditioning paradigm that comprises three successive acquisition and extinction phases, each with a novel CS+/CS- set. Each set consists of two different neutral faces on different background colors which serve as CS+ and CS-, respectively. Thereby, this design provides sufficient trials for EEG analyses while tripling the relative amount of trials that tap into more transient neurobiological processes. Consistent with prior studies on ERP components, data-driven topographic EEG analyses revealed that ERP amplitudes were potentiated during time periods from 33–60 ms, 108–200 ms, and 468–820 ms indicating that fear conditioning prioritizes early sensory processing in the brain, but also facilitates neural responding during later attentional and evaluative stages. Importantly, averaging across the three CS+/CS- sets allowed us to probe the temporal evolution of neural processes: Responses during each of the three time windows gradually increased from early to late fear conditioning, while long-latency (460–730 ms) electrocortical responses diminished throughout fear extinction. Our novel paradigm demonstrates how short-, mid-, and long-latency EEG responses change during fear conditioning and extinction, findings that enlighten the learning curve of neurophysiological responses to threat in humans.</p>
Code, data and scripts to study wave dynamics in asymmetric material
<p>Supplementary data for [1] Vladislav A. Yastrebov. "Wave propagation through an elastically-asymmetric architected material", 2021, https://arxiv.org/abs/1712.06294v2</p> <p>See "Readme.md" and indivual "Readme.md" files in folders: "data", "src", "fig"</p>
Supplementary Materials: A primer on gathering and analysing multi-level quantitative evidence for differential student outcomes in higher education
<p>Example data sets, syntax files and macros for the tutorials in: Balloo, K., & Winstone, N. E. (2021). A primer on gathering and analysing multi-level quantitative evidence for differential student outcomes in higher education.<em> Frontline Learning Research</em>. <a href="https://eur02.safelinks.protection.outlook.com/?url=https%3A%2F%2Fdoi.org%2F10.14786%2Fflr.v9i2.675&data=04%7C01%7Ck.balloo%40surrey.ac.uk%7C50bb47bb433744dc8da208d8c2116202%7C6b902693107440aa9e21d89446a2ebb5%7C0%7C0%7C637472728228002863%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C1000&sdata=fyA0y2hUkHESUJ7sVJ3s42Re4Yqa5XbgwW7AvEyGDdk%3D&reserved=0">https://doi.org/10.14786/flr.v9i2</a><a href="https://eur02.safelinks.protection.outlook.com/?url=https%3A%2F%2Fdoi.org%2F10.14786%2Fflr.v9i2.675&data=04%7C01%7Ck.balloo%40surrey.ac.uk%7C50bb47bb433744dc8da208d8c2116202%7C6b902693107440aa9e21d89446a2ebb5%7C0%7C0%7C637472728228002863%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C1000&sdata=fyA0y2hUkHESUJ7sVJ3s42Re4Yqa5XbgwW7AvEyGDdk%3D&reserved=0">.675</a> </p> <p><strong>The data for all examples are fictional, and have only been designed to simulate the possible behaviour of institutional data for the purposes of demonstrating the analytical approaches in the primer. No inferences or conclusions should be drawn from the findings of these examples, because the results are not real. </strong></p> <p>We anticipate that readers can use the example data sets as templates and substitute in their own data.</p>
Supplementary Materials for "On the Scalability of Data Reduction Techniques in Current and Upcoming HPC Systems from an Application Perspective"
<p>Supplementary materials with all used benchmark scripts, plot scripts, benchmark results and PIConGPU example data for the submission to "The 1st International Workshop on Data Reduction for Big Scientific Data (DRBSD-1)" held in conjunction with ISC 2017 in Frankfurt, Germany.</p>
The Neanderthal Niche Space of Western Eurasia - Supplemental Material
<p>The data provided here are the supplemental information accompanying the journal article <strong>The Neanderthal Niche Space of Western Eurasia 145ka to 30ka ago</strong> by Yaworsky, Nielsen, & Nielsen. All analyses were performed in R v4.5.0 and are documented in the HTML document, <strong>Supplemental 9</strong>.</p> <p>List of Supplemental Files:</p> <ol> <li><strong>ROCEEH Archaeological Observations - File name: </strong><em><strong>FaunalData_52923_NOANIMALS.csv</strong></em> <ol> <li>Retrieved from <em>Role of Culture in Early Expansions of Humans Out-of Africa Database (</em>http://www.roceeh.net)</li> <li>Original PHP query is found in Supplemental 9. The zooarchaeological observations have been removed from the original PHP query.</li> </ol> </li> <li><strong>ROCEEH Dates Data - File name: </strong><em><strong>Dates_Geog.csv</strong></em> <ol> <li>Retrieved from <em>Role of Culture in Early Expansions of Humans Out-of Africa Database (</em>http://www.roceeh.net)</li> <li>Original PHP query is found in Supplemental 9. These are the Geolayer dates.</li> </ol> </li> <li><strong>ROCEEH Dates Data - File name: </strong><em><strong>Dates_Assem.csv</strong></em> <ol> <li>Retrieved from <em>Role of Culture in Early Expansions of Humans Out-of Africa Database (</em>http://www.roceeh.net)</li> <li>Original PHP query is found in Supplemental 9. These are the ArchLayer dates.</li> </ol> </li> <li><strong>ROCEEH Dates Data - File name: </strong><em><strong>Dates_ArchLayer.csv</strong></em> <ol> <li>Retrieved from <em>Role of Culture in Early Expansions of Humans Out-of Africa Database (</em>http://www.roceeh.net)</li> <li>Original PHP query is found in Supplemental 9. These are the Assemblage dates.</li> </ol> </li> <li><strong>Spatiotemporal Archaeological Observations - File name: </strong><em><strong>ArchaeologicalData_V1.csv</strong></em> <ol> <li>Derived from Supplemental 1 after removing observations that dated outside of the 145ka to 50ka year range, all NA values, and observations duplicated in time and space (1000-year range).</li> </ol> </li> <li><strong>Spatiotemporal Background Points - File name: </strong><em><strong>AbsencePointData.csv</strong></em> <ol> <li>Randomly generated background points. 100 random points were generated in each millennium.</li> </ol> </li> <li><strong>High-Resolution Spatiotemporal Predictions - File name: </strong><em><strong>SDM_MainGIF.mp4</strong></em> <ol> <li>High-resolution mp4 file showing the predictions of the Neanderthal niche space from 145ka to 30ka ago.</li> </ol> </li> <li><strong>Neanderthal Niche Space 145ka to 30ka ago- File name: </strong><em><strong>Human_Niche_Size.csv</strong></em> <ol> <li>Quantification of the Neanderthal niche space for each millennium.</li> </ol> </li> <li><strong>Analysis Markdown Document - File Name: </strong><em><strong>NeanderEdgeMD_v5.html</strong></em> <ol> <li>Markdown illustrating step-by-step the methods used to organize and analyze the data.</li> </ol> </li> <li><strong>Delta O18 Record - File name: </strong><em><strong>LisieckiRaymod18O.csv</strong></em> <ol> <li>Delta O18 Record from Lisiecki & Raymo, 2005.</li> <li>Used in Figure 1 of the publication to illustrate the relationship between Neanderthal niche size and Delta O18 values.</li> </ol> </li> <li><strong>Neanderthal Niche Space 350ka ago to Present - File name: </strong><em><strong>Human_Niche_Size_350k.csv</strong></em> <ol> <li>Neanderthal niche space estimates from 350ka to the present based on the model constructed around the 145ka to 50ka ago archaeological observations.</li> <li>Not discussed in the main publication.</li> </ol> </li> </ol> <p>The NeanderEDGE Project is funded by the Independent Research Fund Denmark (Danmarks Frie Forskningsfond) case number 9062-00027B.</p>
The Human Niche Space of Post-LGM Late Upper Paleolithic Europe - Supplemental Material
<p>The data provided here are the supplemental information accompanying the journal article <strong>The Human Niche Space of Post-LGM Late Upper Paleolithic Europe: The Effects of Climate and Population Growth on Human Land Use</strong> by Yaworsky, Hussain, & Riede. All analyses were performed in R v4.5.0 and are documented in the HTML document, <strong>Supplemental 4</strong>.</p> <p>Version 1.2 of the Analysis Markdown Document incoporates changes made to functions within the package ENMeval.</p> <p>List of Supplemental Files:</p> <ol> <li><strong>Spatiotemporal Archaeological Observations - File name: <em>Archaeologicaldata_v1.csv</em></strong> <ol> <li>Archaeological observations derived from Kretschmer (2015) and supplemented with additional observations (see main paper for details).</li> </ol> </li> <li><strong>Summed Probability Estimate for Population Estimation - File name: <em>Population_SPD2.csv</em></strong><br> <ol> <li>Summed probability distribution estimating changes in relative population size across Europe from 22ka ago to 9.1ka ago using data from the P3K14C database (Bird et al, 2022; see <strong>Supplemental 4</strong> for details).</li> </ol> </li> <li><strong>Spatiotemporal Background Points - File name: </strong><em><strong>AbsencePointData.csv</strong></em><br> <ol> <li>Randomly generated background points. 100 random points were generated in each millennium.</li> </ol> </li> <li><strong>Analysis Markdown Document - File Name: </strong><em><strong>CLIOARCH_MD_v1.2.html</strong></em><br> <ol> <li>Markdown illustrating step-by-step the methods used to organize and analyze the data.</li> </ol> </li> <li><strong>High-Resolution Spatiotemporal Predictions - File name: </strong><em><strong>SDM_MainGIF.mp4</strong></em><br> <ol> <li>High-resolution mp4 file showing the predictions of the potential climate niche space for humans from 22ka to 9.1ka ago.</li> </ol> </li> <li><strong>Potential Niche Space 22ka to 9.1ka ago- File name: </strong><em><strong>Human_Niche_Size.csv</strong></em> <ol> <li>Quantification of the potential climate niche space for each century.</li> </ol> </li> </ol> <p>The Climate data are not provided due to their size but are sourced from Karger et al (2023) and are accessible <a href="https://chelsa-climate.org/">here (https://chelsa-climate.org/)</a>.</p> <p> </p>
Frontiere della Transizione Energetica. Un database cartografico sui permessi di ricerca per materie prime critiche in Italia.
<p>La principale strategia istituzionale per limitare il riscaldamento globale e realizzare un futuro a bassa intensità di carbonio si risolve, ad oggi, nella transizione a forme di energia "pulite". Le tecnologie di base di questa transizione come batterie ricaricabili, pannelli solari e turbine eoliche sono tuttavia caratterizzate da un'alta intensità minerale, ossia dalla necessità di reperire alcune materie prime in nuove e ben più ingenti quantità rispetto a precedenti cicli di accumulazione. All'interno dell'Eurozona, la sostanziale dipendenza dalle importazioni di CRM ha prodotto un forte stimolo all'esplorazione di risorse minerarie indigene tramite, per esempio, il Raw Materials Act (2023) ed altre iniziative comunitarie. All'interno di questo scenario europeo, già si assiste ad una significativa espansione delle concessioni per permessi di ricerca mineraria in diversi territori della penisola italiana. Al di là dei casi isolati è però complicato tracciare un quadro d'insieme di questa espansione. Almeno due fattori concorrono a rendere difficoltosa questa informazione: da un lato, la scarsa consapevolezza rispetto alla reale intensità minerale della transizione energetica e quindi la sostanziale mancanza di un dibattito tanto pubblico quanto accademico, dall'altro dalla straordinaria frammentazione istituzionale che caratterizza la gestione delle risorse minerarie in Italia, la cui autorizzazione spetta alle Regioni. Questo dataset sopperisce a questa mancanza. Sono qui raccolti e progressivamente aggiornati i dati cartografici relativi ai permessi di ricerca mineraria per materie prime critiche (CRM) ad oggi attivi in Italia, con l'obiettivo di rendere unitari, leggibili e accessibili i dati geografici relativi a queste concessioni. I dati raccolti sono di pubblico dominio e reperiti nelle diverse banche dati regionali. Ad ogni poligono sono associati alcuni indicatori di tipo qualitativo e quantitativo. In conclusione, questo dataset risponde alla necessità di tracciare le dimensioni geografiche di un fenomeno emergente che, data la sua fase iniziale di sviluppo, è ancora poco leggibile dal punto di vista materiale pur promettendo trasformazioni di ampio raggio su ecosistemi e società locali.</p>
Supplementary Materials for "Accelerating data sharing and re-use in volume electron microscopy"
<p>The deposition contains supporting materials for "Accelerating data sharing and re-use in volume electron microscopy" Comment</p> <ul> <li>Sample preparation protocol for cell monolayers optimized for serial block face scanning electron microscopy</li> <li>Supporting movies showing models of biological specimens imaged using volume electron microscopy</li> </ul>
Dataset for "Fertilizer value of dairy processing waste materials and contributions of soil microorganisms towards phosphorus uptake in grasses."
<p>This file includes the dataset used for the analysis of the fertilizer value from dairy processing waste materials and the contribution of soil microorganisms towards P uptake. More information in the linked future publication</p>
Supplementary Material for "Using Unstructured Crowd-sourced Data to Evaluate Urban Tolerance of Terrestrial Native Animal Species within a California Mega-City"
<p>This data repository is for the publication "Using Unstructured Crowd-sourced Data to Evaluate Urban Tolerance of Terrestrial Native Animal Species within a California Mega-City" and contains all R scripts and data files to reproduce results as well as all supplementary tables and figures.</p>
Organic Matter, Geochemical, Visible Spectrocolorimetric Properties, Radiocesium Properties, and Grain Size of Potential Source Material, Target Sediment Core Layers and Laboratory Mixtures for Conducting Sediment Fingerprinting Approaches in the Mano Dam Reservoir (Hayama Lake) Catchment, Fukushima Prefecture, Japan
<p>The current dataset was compiled to study sediment fingerprintings practices, i.e tracer selection and contribution modelling. Organic matter, elemental geochemistry, visible difuse spectrocolorimetric properties, radiocesium properties, and grain size were analysed were analysed in potential source material that may supply sediment to coastal rivers, here the upper part of the Mano river, draining the main Fukushima radioactive pollution plume (Japan). Four potential soil source materials (<em>n</em> = 68) were considered: undecontaminated cropland (<em>n</em> = 24), as non-decontaminated soil before the application of local decontamination policies, remediated cropland (<em>n</em> = 10), as decontaminated soil after the application of local decontamination policies, forest soils (n = 24) and subsurface material originating from channel bank collapse or landslides (<em>n</em> = 10; referred to as subsoil). A sediment core was collected in the Mano Dam lake (Hayama lake) on the 6th June 2021 and was sectionned into 1-cm layers (<em>n</em> = 38). Laboratory mixtures (<em>n</em> = 27) were made to assess different contribution levels from the sources.</p> <p>The current dataset comprises four .csv files including data and metadata information and their respective descriptions of variables. The data set is composed of soil samples, sediment core layer and laboratory mixtures. Laboratory mixtures were prepared to provide a dataset to calibrate/validate un-mixing models implemented to address this research question and analysed in the same conditions and using the same equipment as the source/target material.</p> <p>Recommended encoding format: <strong>latin1</strong></p>
Supplementary material to: Long-term (bio)deterioration of Fe-containing and Fe-depleted sandstones: An experimental insight into biotic and abiotic interactions.
<p>This dataset includes: micorphotographs, scanning electron microscope images and related EDS spectra, thermal analysis (DSC-TG), grain size distribution. Abbreviations used in the supplementary file names refer to: GMB (growth medium inoculated with the bacteria, Pseudomonas fluorescens), GM (sterile growth medium), ARE (artificial root exudates), H2O (water), NR (Sample Nowa Ruda), Z (Sample Żerkowice ŻR).</p>
Application and characterization of poly(vinyl alcohol) reinforced with cellulose nanofibrils as a coating for wood – Supplementary material
<p>Supplementary material to the article "Application and characterization of poly(vinyl alcohol) reinforced with cellulose nanofibrils as a coating for wood"</p>
Data from 'Tracability of Forest Reproductive Material with the quality label 'Plant van Hier': A DNA database with genetic profiles of native autochthonous tree and shrub species of Flanders, Belgium'
<h2>Background</h2> <p>Indigenous trees and shrubs play an important role in multifunctional forest management. They form a significant part of the biodiversity in our forests. Forest reproductive material (FRM) of autochthonous Flemish origin is sold under the quality label ‘Plant van Hier’, a certification mark of the Agency for Nature and Forests. To ensure the provenance of the seedlings, we developed a DNA-database of genetic profiles of potential parent trees, using species-specific genetic markers. This database enables the traceability of FRM of the ‘Plant van Hier’ label throughout the entire production chain; from seed harvesting and cultivation to planting by the end user.</p> <p>This database contains the genetic profiles of almost all possible parent trees present within 27 Flemish autochthonous seed orchards of eight ecologically important tree and shrub species: <em>Carpinus betulus</em>, <em>Corylus avellana</em>, <em>Frangula alnus</em>, <em>Populus tremula</em>, <em>Sorbus aucuparia</em>, <em>Tilia cordata</em>, <em>Tilia platyphyllos,</em> and <em>Ulmus laevis</em>. The profiles were established using microsatellite markers (11 to 24 markers per species). New genetic markers were developed for <em>Carpinus betulus</em> and <em>Ulmus laevis</em>. PCR products were run on an ABI 3500 Genetic Analyser (Thermo Fisher Scientific).</p> <h2>Files</h2> <p>The files will be updated when new genotypes are added to the seed orchards. The current data files contain data from genotypes collected in the period 2018-2023. </p> <h3>Species_genotypes</h3> <p>These files contain the genetic fingerprints of the parent trees of autochthonous Flemish seed orchards. Missing data is indicated as ‘MD’. For <em>Carpinus betulus</em>, an octoploid species, the allelic phenotype is given instead of the genotype as the number of times that an allele occurs on a specific locus is not known.</p> <p>The next metadata is additionally given:<br>- Species: the Latin name of the species<br>- Seed_orchard: the name of the seed orchard in which the genotypes are located<br>- Code_seed_orchard: the code of the seed orchard in which the genotypes are located as given in the Register of Flemish Forest Reproductive Material (‘Register bosbouwkundig uitgangsmateriaal’; inbo.be)<br>- Genotype: the fieldname given to the genotype<br>- Origin: the location where the genotype was collected in Flanders, Belgium. Genotypes were collected from natural stands which are assumed to have an autochthonous origin. When the specific location is unknown, the location ‘Flanders’ is given. <br>- Year_sampled: the year in which the genotypes were sampled in the respective seed orchard for genetic analysis.</p> <h3>Species_binsets</h3> <p>These files contain the binsets and allele names that are used to score the alleles of the genotypes in the programme Geneious Prime 2019.3.2 (<a href="https://www.geneious.com">https://www.geneious.com</a>). For <em>Tilia platyphyllos </em>and <em>Tilia cordata</em>, the same binsets were used.</p>
Supplementary material to: Bioweathering of Egyptian Nubian sandstone and Theban limestone: three months insight by experimental incubation
<p>This dataset includes: microscope images, scanning electron microscope images and related EDS spectra, thermal analysis (DSC-TG), grain size parameters, XRD data. Abbreviations used in the supplementary file names refer to: S3: Nubian sandstone sample S3, S6: Nubian sandstone sample S6, TL: Theban limestone sample, SEM afterEXP: scanning electron microscope observations made after termination of the experiment, SEM: scanning electron microscope, XRD: X-ray powder diffraction.</p>
HTSinfer: Supplementary materials
<p>This repository contains data used for the testing of <a href="https://github.com/zavolanlab/htsinfer">HTSinfer</a>, a Python-based tool to infer metadata directly from bulk RNA-sequencing data, generated on Illumina platforms. </p> <p>The repository includes the sample tables containing metadata from the 72 self-generated and publicly shared RNA-Seq samples, the 720 samples collected from the SRA database, and the aggregated tables, describing the results of the inference. </p> <p>For testing purposes, HTSinfer was installed from <a href="https://anaconda.org/bioconda/htsinfer">Bioconda</a> and executed with default settings, except for the <code>--records</code> parameter, which was adjusted in the case of the 720 RNA-Seq samples set. HTSinfer was tested with the <code>--records</code> argument set to different values (10 thousand, 100 thousand, 1 million, 10 million, and 0 – indicating all records) to evaluate performance and runtimes.</p> <p>A supplementary table comparing the functionality of HTSinfer with other available metadata inference tools is also available in the repository.</p>
Dataset of "Mn-doped WSe2 as an efficient electrocatalyst for hydrogen production and as anode material for lithium-ion batteries"
<p>The ongoing energy crisis has made it imperative to develop low-cost, easily fabricated, yet efficient materials. It is highly desirable for these nanomaterials to function effectively in multiple applications. Among transition metal dichalcogenides, tungsten diselenide (WSe2) shows great promise but remains understudied. In this work, we doped WSe2 with Mn using a simple hydrothermal method. The resulting material exhibited excellent electrocatalytic activity for the hydrogen evolution reaction, achieving a low overpotential of –0.28 V vs RHE at -10 mA/cm2, enhanced conductivity, and high stability and durability. Moreover, as an anode material in in lithium-ion batteries, the Mn-doped WSe2 outperformed pristine WSe2, reaching discharge and charge capacities of 1223 and 922 mAh g−1, respectively. Additionally, the Mn-doped material maintained a significantly higher discharge capacity of 201 mAh g−1 compared to intact WSe2, which had 68 mAh g−1 after 150 cycles. This work offers novel insights into designing efficient bifunctional nanomaterials using transition metal dichalcogenides.</p>
Supplementary Materials for 'Measuring and assessing indeterminacy and variation in the morphology-syntax distinction'
<p><strong>Supplementary materials for the article 'Measuring and assessing indeterminacy and variation in the morphology-syntax distinction' in <em>Linguistic Typology </em>(Vol. and No. TBD).</strong></p> <p>Abstract:</p> <p>We provide a discussion of some of the challenges in using statistical methods to investigate the morphology-syntax distinction cross-linguistically. The paper is structured around three problems related to the morphology-syntax distinction; (i) the boundary strength problem; (ii) the composition problem; (iii) the architectural problem.<br> The boundary strength problem refers to the possibility that languages vary in terms of how distinct morphology and syntax are or the degree to which morphology is autonomous. The composition problem refers to the possibility that languages vary in terms of how they distinguish morphology and syntax: what types of properties distinguish the two systems. The architecture problem refers to the possibility that languages vary in terms of whether a global distinction between morphology and syntax is motivated at all and the possibility that languages might partition phenomena in different ways.<br> This paper is concerned with providing an overarching review of the methodological problems involved in addressing these three issues. We illustrate the problems using three statistical methods: correlation matrices, random forests with different choices for the dependent variable, and hierarchical clustering with validation techniques.</p> <p> </p> <p>Overview of materials:</p> <ul> <li>SM1: csv with the data</li> <li>SM2: code and pdf for generating the correlation matrices</li> <li>SM3: code and pdf for the random forest analyses</li> <li>SM4: code and pdf for the clustering and cluster validation analyses</li> </ul>
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.