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Complete set of raw and processed datasets, as well as associated Jupyter notebooks for analysis, associated with manuscript entitled: "The MOUSE project: a practical approach for obtaining traceable, wide-range X-ray scattering information"
<p>This dataset is a complete set of raw, processed and analyzed data, complete with Jupiter notebooks, associated with the manuscript mentioned in the title. </p> <p>In the manuscript, we provide a ``systems architecture''-like overview and detailed discussions of the methodological and instrumental components that, together, comprise the "MOUSE" project (<strong>M</strong>ethodology <strong>O</strong>ptimization for <strong>U</strong>ltrafine <strong>S</strong>tructure <strong>E</strong>xploration). Through this project, we aim to provide a comprehensive methodology for obtaining the highest quality X-ray scattering information (at small and wide angles) from measurements on materials science samples. </p>
Projecte ATENC!Ó Results
<p>This dataset contains the results of the ATENC!Ó randomized controlled trial assessing whether air pollution in high schools can affect the attention processes of adolescents. </p>
Monochromatic opacity data from the Opacity Project (OP) for use with MESA.
<p>Monochromatic opacity data from the Opacity Project (OP) for use with MESA.</p> <p>The OP_mono opacities use data and code from the OP website as modified by Haili Hu. Since the file is large, it is not included in the standard mesa download.</p> <p>If you use these opacities, you should cite Seaton (2005): https://ui.adsabs.harvard.edu/#abs/2005MNRAS.362L…1S</p>
Greenland ice sheet surface melt projections using artifical neural networks
<p>Surface melt projections for the Greenland ice sheet using artificial neural networks.</p> <p>Organized as follows:</p> <p><scenario>/<variable>/<model>/<ensemble_number>.nc</p>
Projected effects of climate change on boreal bird community accentuated by anthropogenic disturbances in western boreal forest, Canada
<p><b>Aim</b></p> <p>Climate change<b> </b>is expected to influence boreal bird communities significantly, notably through changes in forest habitat (composition and age structure),<b> </b>in the coming decades. How these changes will accumulate and interact with anthropogenic disturbances remains an open question for most species.</p> <p><b>Location</b></p> <p>Northeastern Alberta, Canada.</p> <p><b>Methods </b></p> <p>We used the LANDIS-II forest landscape model to project changes in forest landscapes, and associated bird populations (72 passerine species), according to three climatic scenarios (baseline, RCP 4.5, RCP 8.5) and three forest harvesting scenarios of differing intensity.</p> <p><b>Results</b></p> <p>Both forest harvesting and climate-related drivers were projected to have large impacts on bird communities in this region. As a result of climate-induced increases in fire activity as well as decreased conifer productivity, our simulations projected that an important proportion of Alberta's boreal forests would transition to treeless habitat (i.e. grass-, or shrub-dominated vegetation) while many conifer-dominated stands would likely be replaced by broadleaf tree cover. Consequently, the abundance of bird species associated with open and deciduous habitats were projected to increase. With a strong anthropogenic climate forcing scenario (RCP 8.5), sharp declines in abundance of coniferous trees were also projected, particularly in mature and old forest stands, triggering major declines for bird species associated with coniferous and mixedwood forest types.</p> <p><b>Main Conclusions</b></p> <p><a>As the most comprehensive simulation of climate change and harvesting impacts on avian habitats in the North American boreal region to date</a>, our study <a>reveals</a> the importance of considering key habitat characteristics like forest age structure and composition through forest landscape modeling, and identifies 18 bird species particularly sensitive to climate change. Our simulations suggest that a change in forest management practices could play an important role in the conservation of boreal bird species vulnerable to climate change. The intensive forest harvesting simulated accelerated declines in bird abundance compared to a "no harvesting" scenario.</p> <div> <div> <div class="msocomtxt"> </div> </div> </div>
Communication Challenges in adopting scrum methodology in research-based projects
<p>The folder contains three other folders, one has the questionnaire question, the second one has participants' answers to the questionnaire, and the last one has data analysis files for the questionnaire. </p>
Data from: Projected changes in prevailing winds for transatlantic migratory birds under global warming
A number of terrestrial bird species that breed in North America cross the Atlantic Ocean during autumn migration when travelling to their non-breeding grounds in the Caribbean or South America. When conducting oceanic crossings, migratory birds tend to associate with mild or supportive winds, whose speed and direction may change under global warming. The implications of these changes for transoceanic migratory bird populations have not been addressed. We used occurrence information from eBird (1950–2015) to estimate the geographical location of population centres at a daily temporal resolution across the annual cycle for 10 transatlantic migratory bird species. We used this information to estimate the location and timing of autumn migration within the transatlantic flyway. We estimated how prevailing winds are projected to change within the transatlantic flyway during this time using daily wind speed anomalies (1996–2005 and 2091–2100) from 29 Atmosphere-Ocean General Circulation Models implemented under CMIP5. Autumn transatlantic migrants have the potential to encounter strong westerly crosswinds early in their transatlantic journey at intermediate and especially high migration altitudes, strong headwinds at low and intermediate migration altitudes within the Caribbean that increase in strength as the season progresses, and weak tailwinds at intermediate and high migration altitudes east of the Caribbean. The CMIP5 simulations suggest that, during this century, the likelihood of autumn transatlantic migrants encountering strong westerly crosswinds will diminish. As global warming progresses, the need for species to compensate or drift under the influence of strong westerly crosswinds during the initial phase of their autumn transatlantic journey may be diminished. Existing strategies that promote headwind avoidance and tailwind assistance will likely remain valid. Thus, climate change may reduce time and energy requirements and the chance of mortality or vagrancy during a specific but likely critical portion of these species' autumn migration journey.
Data from: Covariation in abscission force and terminal velocity of wind-borne sibling seeds alters long distance dispersal projections
1. Despite the fact that seeds are unlikely to be identical—even among siblings within a maternal individual—dispersal models typically use one mean trait value to represent the ability of an entire species to disperse. Previous work has shown that the environmental conditions under which individuals leave the maternal site strongly affect how far seeds will travel. However, less is known about how trait variation within individuals contributes to dispersal or how such variation might interact with abiotic factors. 2. Here, we develop the use of an ergometer in a novel application to investigate variation in seed traits, specifically the force required for seed abscission and seed terminal velocity, exhibited by seeds from different locations within maternal capitula of the invasive species Carduus nutans (Asteraceae). 3. We find that seeds from the center of capitula are significantly easier to liberate and have slower falling velocities than siblings found near the edge of capitula. When abscission force is positively correlated with terminal velocity, slowly falling, easily abscised seeds are projected to travel much further than the average seed on slow winds. 4. Our experimental and theoretical results, which together show that within-individual variation can strongly affect model projections of species dispersal, have important implications for our broader understanding of population spread rates, the spatial structure of populations, metapopulation connectivity, and gene flow in the landscape.
Data from: Evaluating the reintroduction project of Przewalski's horse in China using genetic and pedigree data
Przewalski's horse went extinct in the wild in the mid 1960's. Starting in 1985, individuals were brought from western zoos to two centers in China and breeding programs were initiated. With the increasing size of captive populations, two reintroduction projects were launched in the northwestern China in 2001 and 2010. Knowledge on genetic diversity in China's horse populations is limited, but would help improve the genetic management and assess the success of the reintroduction. Accordingly, one reintroduced and two captive populations were examined with 10 microsatellite loci together with pedigree data. The results showed higher level of diversity within the captive populations than the reintroduced population, indicating some alleles may have been lost during reintroduction. Genetic differentiation was detected among populations (FST=0.09±0.05, RhoST=0.05±0.02) and Bayesian clustering supported the presence of three subpopulations. The highest genetic differentiation was observed between the captive and reintroduced populations, and inbreeding coefficients were generally higher in the reintroduced population. Temporal estimates of both pedigree and microsatellite data showed a high, but decreasing level inbreeding. Through simulations, we estimated that the reintroduced population needs more than 100 individuals to retain approximately 90% of its current, already depauperate, genetic diversity. We have provided recommendations for the management program concerning introgressed genes from domestic horse and the number and origin of individuals for future reintroductions.
Community science validates climate suitability projections from ecological niche modeling
<p><span>Climate change poses an intensifying threat to many bird species, and projections of future climate suitability provide insight into how species may shift their distributions in response. Climate suitability is characterized using ecological niche models (ENMs), which correlate species occurrence data with current environmental covariates and project future distributions using the modeled relationships together with climate predictions. Despite their widespread adoption, ENMs rely on several assumptions that are rarely validated <i>in situ </i>and can be highly sensitive to modeling decisions, precluding their reliability in conservation decision-making. Using data from a novel, large-scale community science program, we developed dynamic occupancy models to validate near-term climate suitability projections for bluebirds and nuthatches in summer and winter. We estimated occupancy, colonization, and extinction dynamics across species' ranges in the United States in relation to projected climate suitability in the 2020s, and used a Gibbs variable selection approach to quantify evidence of species-climate relationships. We also included a Bird Conservation Region strata-level random effect to examine among-strata variation in occupancy that may be attributable to land-use and ecoregional differences. Across species and seasons, we found strong evidence that initial occupancy and colonization were positively related to 2020 climate suitability, illustrating an independent validation of projections from ENMs across a large geographic area. </span><span>Random strata effects revealed that occupancy probabilities were generally higher than average in core areas and lower than average in peripheral areas of species' ranges, and served as a first step in identifying spatial patterns of occupancy from these community science data. </span><span>Our findings lend much-needed support to the use of ENM projections for addressing questions about potential climate-induced changes in species' occupancy dynamics. More broadly, </span>our work highlights the value of community scientist observations for ground-truthing projections from statistical models and for refining our understanding of the processes shaping species' distributions under a changing climate.</p>
Afognak Lake sockeye salmon stock monitoring project (2017–2019)
<p>The Afognak River (Litnik) has historically supported one of the largest sockeye salmon subsistence fisheries for Kodiak Archipelago residents. In the 2000s, the number of sockeye salmon returning to Afognak River had diminished substantially resulting in closures to commercial, sport, and subsistence fishing in Afognak Bay. Local subsistence users, represented by the Kodiak-Aleutians Regional Advisory Council, Kodiak Fish and Game Advisory Committee, and Kodiak Tribal Council, stressed the importance of the Afognak River system to local subsistence users and contended that continued closures would make it more difficult for local residents to meet their sockeye salmon needs and shift fishing efforts to small nearby sockeye salmon runs. The Afognak Lake Sockeye Salmon Stock Monitoring Project enumerates adult sockeye salmon into Afognak Lake through a weir located on the Afognak River, describes run-timing, or proportional daily passage, of sockeye salmon through the weir, estimates the age and sex composition of adult sockeye salmon returns, and estimates the average length (mm) by age and sex of sockeye salmon passing through the weir. Data collected from this project provide salmon management biologists the ability to make in-season decisions to execute commercial and sport fisheries. In addition, the information that is gathered from these projects refine the escapement goals and improve preseason run forecasts to allow for maximum sustainable yield and prevent unnecessary restrictions of federal and state subsistence fisheries.</p>
ATN-classification and clinical progression in subjective cognitive decline: the SCIENCe project
<p>Objective: To investigate the relationship between the ATN-model and risk of dementia and cognitive decline in individuals with subjective cognitive decline (SCD).</p> <p>Methods: We classified 693 participants with SCD (60±9yr, 41%F, MMSE 28±2) from the Amsterdam Dementia Cohort and SCIENCe project according to the ATN-model, as determined by amyloid PET or CSF Abeta (A), CSF p-tau (T) and MRI-based medial temporal lobe atrophy (N). All underwent extensive neuropsychological assessment. For 342 participants follow-up was available (3±2yr). As a control population, we included 124 participants without SCD.</p> <p>Results: 56% (n=385) participants had <i>normal AD biomarkers </i>(A-T-N-), 27% (n=186) had <i>non-AD pathologic change</i> (A-T-N+, A-T+N-, A-T+N+), 18% (n=122) fell within the <i>Alzheimer's continuum </i>(A+T-N-, A+T-N+, A+T+N-, A+T+N+). ATN profiles were unevenly distributed, with A-T+N+, A+T-N+ and A+T+N+ containing very few participants. Cox regression showed that compared to A-T-N-, participants in A+ profiles had a higher risk of dementia with a dose-response pattern for number of biomarkers affected. Linear mixed models showed participants in A+ profiles showed a steeper decline on tests addressing memory, attention, language, and executive functions. In the control group, there was no association between ATN and cognition.</p> <p>Conclusions: Among individuals presenting with SCD at a memory clinic, those with a biomarker profile A-T+N+, A+T-N-, A+T+N- and A+T+N+ were at increased risk of dementia, and showed steeper cognitive decline compared to A-T-N- individuals. These results suggest a future where biomarker results could be used for individualized risk profiling in cognitively normal individuals presenting at a memory clinic.</p>
Data from: Evidence of genomic adaptation to climate in Eucalyptus microcarpa: implications for adaptive potential to projected climate change
Understanding whether populations can adapt in situ or whether interventions are required is of key importance for biodiversity management under climate change. Landscape genomics is becoming an increasingly important and powerful tool for rapid assessments of climate adaptation, especially in long-lived species such as trees. We investigated climate adaptation in Eucalyptus microcarpa using the DArTseq genomic approach. A combination of FST outlier and environmental association analyses were performed using > 4,200 genome-wide single nucleotide polymorphisms (SNPs) from 26 populations spanning climate gradients in south-eastern Australia. Eighty-one SNPs were identified as putatively adaptive, based on significance in FST outlier tests and significant associations with one or more climate variables related to temperature (70 / 81), aridity (37 / 81) or precipitation (35 / 81). Adaptive SNPs were located on all 11 chromosomes, with no particular region associated with individual climate variables. Climate adaptation appeared to be characterized by subtle shifts in allele frequencies, with no consistent fixed differences identified. Based on these associations, we predict adaptation under projected changes in climate will include a suite of shifts in allele frequencies. Whether this can occur sufficiently rapidly through natural selection within populations, or would benefit from assisted gene migration, requires further evaluation. In some populations, the absence, or predicted increases to near fixation of particular adaptive alleles hint at potential limits to adaptive capacity. Together, these results reinforce the importance of standing genetic variation at the geographical level for maintaining species' evolutionary potential.
Data from: Quantifying demographic uncertainty: Bayesian methods for integral projection models (IPMs)
Integral projection models (IPMs) are a powerful and popular approach to modeling population dynamics. Generalized linear models form the statistical backbone of an IPM. These models are typically fit using a frequentist approach. We suggest that hierarchical Bayesian statistical approaches offer important advantages over frequentist methods for building and interpreting IPMs, especially given the hierarchical nature of most demographic studies. Using a stochastic IPM for a desert cactus based on a 10-year study as a worked example, we highlight the application of a Bayesian approach for translating uncertainty in the vital rates (e.g., growth, survival, fertility) to uncertainty in population-level quantities derived from them (e.g., population growth rate). The best-fit demographic model, which would have been difficult to fit under a frequentist framework, allowed for spatial and temporal variation in vital rates and correlated responses to temporal variation across vital rates. The corresponding posterior probability distribution for the stochastic population growth rate (λS) indicated that, if current vital rates continue, the study population will decline with nearly 100% probability. Interestingly, less-supported candidate models that did not include spatial variance and vital rate correlations gave similar estimates of λS. This occurred because the best-fitting model did a much better job of fitting vital rates to which the population growth rate was weakly sensitive. The cactus case study highlights several advantages of Bayesian approaches to IPM modeling, including that they: (1) provide a natural fit to demographic data, which are often collected in a hierarchical fashion (e.g., with random variance corresponding to temporal and spatial heterogeneity); (2) seamlessly combine multiple data sets or experiments; (3) readily incorporate covariance between vital rates; and, (4) easily integrate prior information, which may be particularly important for species of conservation concern where data availability may be limited. However, constructing a Bayesian IPM will often require the custom development of a statistical model tailored to the peculiarities of the sampling design and species considered; there may be circumstances under which simpler methods are adequate. Overall, Bayesian approaches provide a statistically sound way to get more information out of hard-won data, the goal of most demographic research endeavors.
Data from: Current and projected future risks of freshwater fish invasions in China
Biological invasions are a primary threat to global biodiversity, supporting mounting calls for the development of early-warning systems to manage existing and emerging invaders. Here, we evaluated the geographical pattern of invasion risks of currently established and potentially emerging nonnative freshwater fishes in China by jointly considering the threats of introduction and establishment under climate change. Introduction threats were estimated according to proxies of human activities and propagule pressure for two primary pathways (aquaculture or ornamental). Establishment threats for 51 current and 64 potential invaders (based on whether having established or not self-sustaining populations) were assessed using an ensemble of species distribution models under current (1960-1990) and future [2041-2060 (2050s) and 2061-2080 (2070s)] climate scenarios. Geographical patterns of invasion risk were then assessed by overlaying the threats of introduction and establishment for each species group both in present-day and in the future. We found that eastern China displayed the highest threat of introduction. In contrast, southeastern and northwestern regions were identified as the most suitable for the establishment of both current and potential future invaders. Under a changing climate, 83 out of 115 species displayed an increase in habitat suitability, resulting in an overall increase of 4.8% by 2050s and 7.1% by 2070s in the extent of suitable habitat for nonnative freshwater fishes. Taken together, invasion risk was found to be highest in southeastern China and lowest in the Tibet Plateau. Our research highlights the importance of assessing invasion risk by integrating the threats associated with the introduction and establishment stages. In particular, our findings revealed convergent patterns of invasion risk between current and potential nonnative freshwater fishes under climate change. Geographic patterns in hotspots of existing and emerging invasions provide critical insights to guide the allocation of resources to monitor and control existing and emerging invasions in China.
Data from: Current and projected global distribution of Phytophthora cinnamomi, one of the world's worst plant pathogens
Globally, Phytophthora cinnamomi is listed as one of the 100 worst invasive alien species and active management is required to reduce impact and prevent spread in both horticulture and natural ecosystems. Conversely, there are regions thought to be suitable for the pathogen where no disease is observed. We developed a CLIMEX model for the global distribution of P. cinnamomi based on the pathogen's response to temperature and moisture and by incorporating extensive empirical evidence on the presence and absence of the pathogen. The CLIMEX model captured areas of climatic suitability where P. cinnamomi occurs that is congruent with all available records. The model was validated by the collection of soil samples from asymptomatic vegetation in areas projected to be suitable by the model for which there were few records. DNA was extracted and the presence or absence of P. cinnamomi determined by high throughput sequencing (HTS). While not detected using traditional isolation methods, HTS detected P. cinnamomi at higher elevations in eastern Australia and central Tasmania as projected by the CLIMEX model. Further support for the CLIMEX model was obtained by using the large dataset from southwest Australia where the proportion of positive records in an area is related to the Ecoclimatic Index value for the same area. We provide for the first time a comprehensive global map of the current P. cinnamomi distribution, an improved CLIMEX model of the distribution, and a projection to 2080 of the distribution with predicted climate change. This information provides the basis for more detailed regional scale modelling and supports risk assessment for governments to plan management of this important soil-borne plant pathogen.
Data from: Current and projected cumulative impacts of fire, drought and insects on timber volumes across Canada
Canada's forests are shaped by disturbances such as fire, insect outbreaks and droughts that often overlap in time and space. The resulting cumulative disturbance risks and potential impacts on forests are generally not well accounted for by models used to predict future impacts of disturbances on forest. This study aims at projecting future cumulative effects of four main natural disturbances – fire, mountain pine beetle, spruce budworm and drought - on timber volumes across Canada's forests using an approach that accounts for potential overlap among disturbances. Available predictive models for the four natural disturbances were used to project timber volumes at risk under aggressive climate forcing up to 2100. Projections applied to the current vegetation suggest increases of volumes at risk related to fire, mountain pine beetle and drought over time in many regions of Canada, but a decrease of the volume at risk related to spruce budworm. When disturbance effects are cumulated, important changes in volumes at risk are projected to occur as early as 2011-2041, particularly in central and eastern Canada. In our last simulation period covering 2071 to 2100, nearly all timber volumes in most of Canada's forest regions could be at risk of being affected by at least one of the four natural disturbances considered in our analysis, a six-fold increase relative to the baseline period (1981-2010). Tree species particularly vulnerable to specific disturbances (e.g., trembling aspen to drought) could suffer disproportionate increases in their volume at risk with potential impacts on forest composition. By 2100, estimated wood volumes not considered to be at risk could be lower than current annual timber harvests in central and eastern Canada. Current level of harvesting could thus be difficult to maintain without the implementation of adaptation measures to cope with these disturbances.
Data from: Incorporating interspecific competition into species-distribution mapping by upward scaling of small-scale model projections to the landscape
There are a number of overarching questions and debate in the scientific community concerning the importance of biotic interactions in species distribution models at large spatial scales. In this paper, we present a framework for revising the potential distribution of tree species native to the Western Ecoregion of Nova Scotia, Canada, by integrating the long-term effects of interspecific competition into an existing abiotic-factor-based definition of potential species distribution (PSD). The PSD model is developed by combining spatially explicit data of individualistic species' response to normalized incident photosynthetically active radiation, soil water content, and growing degree days. A revised PSD model adds biomass output simulated over a 100-year timeframe with a robust forest gap model and scaled up to the landscape using a forestland classification technique. To demonstrate the method, we applied the calculation to the natural range of 16 target tree species as found in 1,240 provincial forest-inventory plots. The revised PSD model, with the long-term effects of interspecific competition accounted for, predicted that eastern hemlock (Tsuga canadensis), American beech (Fagus grandifolia), white birch (Betula papyrifera), red oak (Quercus rubra), sugar maple (Acer saccharum), and trembling aspen (Populus tremuloides) would experience a significant decline in their original distribution compared with balsam fir (Abies balsamea), black spruce (Picea mariana), red spruce (Picea rubens), red maple (Acer rubrum L.), and yellow birch (Betula alleghaniensis). True model accuracy improved from 64.2% with original PSD evaluations to 81.7% with revised PSD. Kappa statistics slightly increased from 0.26 (fair) to 0.41 (moderate) for original and revised PSDs, respectively.
Data from: Projected population proximity indices (30km) for 2005, 2030 & 2050
This data package includes nine population proximity index layers for 2005, 2030 and 2050, for rural, urban and total populations. The layers are distributed as 1km GeoTIFFs and GeoJPGss at 1km. The aim of these layers is to describe the population which may be likely to visit a specific locality where access is determined by Euclidean distance. By using the layers alongside other geographic datasets relating to disease risk it may help identify where people may come into contact with a disease. Human population layers are often used in models to identify risk areas where humans and viruses interact, however most pathogens are not restricted to areas of human habitation: many are found in lesser populated areas such as forests. This dataset will help identify less populated areas that may well still receive high visitor numbers. The layers have been projected to 2030 and 2050 to enable projections of human/disease interfaces in the medium-term which are required to inform policy makers at country and continental level. Urban and rural populations have been separated into individual layers as in some cases it is useful to distinguish between the behaviour and associated risks attributed to the different population segments. There may be a different risk of contacting diseases in rural habitats for rural workers than for than urban visitors.
Data from: Demography of Euterpe precatoria and Mauritia flexuosa in the Amazon: application of integral projection models for their harvest
Non-Timber Forest Products like palm fruits are fundamental in the livelihood of Amerindian groups. For the last 10 years the fruits of wild palm species, like Euterpe precatoria and Mauritia flexuosa, have been entering into global markets. These species are mostly harvested felling the adults, a practice that may have a disproportionate impact in the conservation of the populations. We studied the demography of E. precatoria and M. flexuosa, two important palms of the Amazon, using integral projection models, to characterize the population dynamics and project impact of different fruit harvest methods: adult felling and direct fruit harvest. We followed over 1400 individuals from populations with low harvest intensities in the Tikuna community of Amacayacu, Amazonas, Colombia from 2011 to 2013, establishing four plots for E. precatoria in seasonally inundated forests and two for M. flexuosa in swamps. The population growth in E. precatoria was slightly declining, whereas M. flexuosa was stable. As expected, the simulations of adult felling diminished λ and the number of available adults under any scenario for either species. On the contrary, the simulations support existing information that climbing and other non-destructive harvest methods would probably allow a sustainable management, satisfying the demand and preserving wild populations.
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.