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Data from: How diverse is Mitopus morio? Integrative taxonomy detects cryptic species in a small-scale sample of a widespread harvestman
Mitopus morio is a widespread harvestman species occurring in most of Europe and in moderate and cold-moderate zones of Asia and North America. The species is characterized by extreme variability in body size and leg length. As leg length is correlated with habitat temperature, M. morio has been considered as an example of Allen's rule. Recently, observations for a single location in Tyrol, Austria, indicated the absence of mating between short- and long-legged individuals. This study examines for signs of putative cryptic species in M. morio using an integrative approach that combines mating trials, amplified fragment length polymorphism whole-genome scans, mitochondrial sequences and morphometrics. The mating trials did not corroborate the initial hypothesis of a reproductive barrier associated with leg size. Both types of genetic data revealed the existence of three distinct groups, in line with the mating results but largely unrelated to leg morphology and geographical origin of specimens. Morphometric characters supporting the findings of the other disciplines were identified using a supervised approach. We infer from all data together the existence of strongly diverged cryptic lineages among the analysed individuals, cautiously interpret them as three sympatric species and conclude that in these harvestmen Allen's rule applies at different levels. Due to the unexpected amount of differentiation found within a geographical scale very small compared with the distribution of M. morio, we suggest a thorough revision of the genus prior to formal taxonomic changes. Our case study underlines the general applicability of the integrative taxonomic protocol used and highlights the relevance of several rationales implemented in the protocol.
Data from: A refined modelling approach to assess the influence of sampling on palaeobiodiversity curves: new support for declining Cretaceous dinosaur richness
Modelling has been underdeveloped with respect to constructing palaeobiodiversity curves, but it offers an additional tool for removing sampling from their estimation. Here an alternative to subsampling approaches, which often require large sample sizes, is explored by the extension and refinement of a pre-existing modelling technique that uses a geological proxy for sampling. Application of the model to the three main clades of dinosaurs suggests that much of their diversity fluctuations cannot be explained by sampling alone. Furthermore, there is new support for a long-term decline in their diversity leading up to the K/Pg extinction event. At present use of this method with data that includes either lagerstätten or 'Pull of the Recent' biases is inappropriate, although partial solutions are offered.
Data from: Evaluating the interaction of faecal pellet deposition rates and DNA degradation rates to optimize sampling design for DNA-based mark-recapture analysis of Sonoran pronghorn
Knowledge of population demographics is important for species management but can be challenging in low-density, wide-ranging species. Population monitoring of the endangered Sonoran pronghorn (Antilocapra americana sonoriensis) is critical for assessing the success of recovery efforts, and noninvasive DNA sampling (NDS) could be more cost-effective and less intrusive than traditional methods. We evaluated faecal pellet deposition rates and faecal DNA degradation rates to maximize sampling efficiency for DNA-based mark–recapture analyses. Deposition data were collected at five watering holes using sampling intervals of 1–7 days and averaged one pellet pile per pronghorn per day. To evaluate nuclear DNA (nDNA) degradation, 20 faecal samples were exposed to local environmental conditions and sampled at eight time points from one to 124 days. Average amplification success rates for six nDNA microsatellite loci were 81% for samples on day one, 63% by day seven, 2% by day 14 and 0% by day 60. We evaluated the efficiency of different sampling intervals (1–10 days) by estimating the number of successful samples, success rate of individual identification and laboratory costs per successful sample. Cost per successful sample increased and success and efficiency declined as the sampling interval increased. Results indicate NDS of faecal pellets is a feasible method for individual identification, population estimation and demographic monitoring of Sonoran pronghorn. We recommend collecting samples >7 days old and estimate that a sampling interval of 4–7 days in summer conditions (i.e. extreme heat and exposure to UV light) will achieve desired sample sizes for mark–recapture analysis while also maximizing efficiency.
Data from: Sensitivity of functional diversity metrics to sampling intensity
1. Functional diversity (FD) metrics are increasingly used in ecological research, particularly in studies of community assembly and ecosystem functioning. However, studies using FD metrics vary greatly in the intensity by which ecological communities were sampled and it is largely unknown how sensitive these metrics are to low sampling intensity (undersampling). 2. Here, we used a combination of simulations with theoretically assembled communities and three comprehensive, independent, empirical datasets on plant, ground beetle and bird communities to investigate the sensitivity of nine commonly used FD metrics to undersampling. 3. Simulations with both theoretical communities and empirical data showed that in a wide range of contexts, the measurement of various FD metrics requires a much higher sampling effort to reach an 'adequate' precision (defined as an r2 of at least 0.7 between different subsets of the same population), than that required for commonly used taxonomic diversity metrics (e.g. species richness), although the 'accuracy' (their deviation from the diversity value of a completely sampled community) of their measurements is not more sensitive to undersampling than species richness. We also found that some FD metrics (e.g. Functional Dispersion) are consistently less sensitive to undersampling than others (e.g. nearest neighbour distance-metrics). Problems of undersampling were generally most severe in datasets with high overall species richness and low overall abundances. 4. We found that the precision of many FD metrics is highly sensitive to undersampling, and more so than commonly used taxonomic diversity metrics. Therefore, to ensure reproducible results in functional biodiversity research, we recommend that thorough sampling designs are used to sample communities and that datasets originally collected for studying taxonomic diversity should only be used for FD when it can be shown that undersampling is not a major issue. In cases where undersampling is suspected or logistically unavoidable, FD metrics that are relatively insensitive to its effects (e.g. Functional Dispersion) should be prioritized.
Sample data for PyMINEr
<p>Sample data for the tutorial of PyMINEr, downloaded from https://www.sciencescott.com/pyminer</p>
Data from: The program STRUCTURE does not reliably recover the correct population structure when sampling is uneven: sub-sampling and new estimators alleviate the problem
Inferences of population structure and more precisely the identification of genetically homogeneous groups of individuals are essential to the fields of ecology, evolutionary biology, and conservation biology. Such population structure inferences are routinely investigated via the program STRUCTURE implementing a Bayesian algorithm to identify groups of individuals at Hardy-Weinberg and linkage equilibrium. While the method is performing relatively well under various population models with even sampling between subpopulations, the robustness of the method to uneven sample size between subpopulations and/or hierarchical levels of population structure has not yet been tested despite being commonly encountered in empirical datasets. In this study, I used simulated and empirical microsatellite datasets to investigate the impact of uneven sample size between subpopulations and/or hierarchical levels of population structure on the detected population structure. The results demonstrated that uneven sampling often leads to wrong inferences on hierarchical structure and downward biased estimates of the true number of subpopulations. Distinct subpopulations with reduced sampling tended to be merged together, whilst at the same time, individuals from extensively sampled subpopulations were generally split, despite belonging to the same panmictic population. Four new supervised methods to detect the number of clusters were developed and tested as part of this study and were found to outperform the existing methods using both evenly and unevenly sampled datasets. Additionally, a sub-sampling strategy aiming to reduce sampling unevenness between subpopulations is presented and tested. These results altogether demonstrate that when sampling evenness is accounted for, the detection of the correct population structure is greatly improved.
Data from: The effects of inference method, population sampling and gene sampling on species tree inferences: an empirical study in slender salamanders (Plethodontidae: Batrachoseps)
Species tree methods are now widely used to infer the relationships among species from multi-locus datasets. Many methods have been developed, which differ in whether gene and species trees are estimated simultaneously or sequentially, and in how gene trees are used to infer the species tree. While these methods perform well on simulated data, less is known about what impacts their performance on empirical data. We used a dataset including five nuclear genes and one mitochondrial gene for 22 species of Batrachoseps to compare the effects of method of analysis, within-species sampling and gene sampling on species tree inferences. For this dataset, the choice of inference method had the largest effect on the species tree topology. Exclusion of individual loci had large effects in *BEAST and STEM, but not in MP-EST. Different loci carried the greatest leverage in these different methods, showing that the causes of their disproportionate effects differ. Even though substantial information was present in the nuclear loci, the mitochondrial gene dominated the *BEAST species tree. This leverage is inherent to the mtDNA locus and results from its high variation and lower assumed ploidy. This mtDNA leverage may be problematic when mtDNA has undergone introgression, as is likely in this dataset. By contrast, the leverage of RAG1 in STEM analyses does not reflect properties inherent to the locus, but rather results from a gene tree that is strongly discordant with all others, and is best explained by introgression between distantly related species. Within-species sampling was also important, especially in *BEAST analyses, as shown by differences in tree topology across 100 subsampled datasets. Despite the sensitivity of the species tree methods to multiple factors, five species groups, the relationships among these, and some relationships within them, are generally consistently resolved for Batrachoseps.
Data from: Disparity in preemptive end-of-life conversation experience caused by subjective economic status among general Japanese elderly people: a cross-sectional study with stratified random sampling
Objectives: Preemptive conversations (PCs) about end-of-life (EOL) preferences are beneficial for both elderly people and their families to understand and share the preferences. However, the factors which promote/inhibit PCs have yet to be clarified. We therefore aimed to determine the factors related to having PCs with hypothesis that age, subjective economic status and subjective health status are associated with having PC experience. Design: A cross-sectional study administering a questionnaire and using stratified random sampling by gender and region. Setting: Residents aged 65 years or older who were not receiving nursing care as of November 1, 2016, were extracted from the Japanese long-term care insurance system registry in Koriyama City, Fukushima Prefecture, Japan. Participants: 1,575 participants (717 males and 858 females). Outcome: Presence or absence of PC experience with family or friends (yes/no). Results: The mean age of the participants was 74.0 years. A multivariable logistic-regression analysis revealed that having PC experience was significantly associated with gender (OR = 1.907; 95% CI = 1.556, 2.337; p < 0.001), subjective economic status (OR = 0.832; 95% CI = 0.716, 0.966; p=0.016), and subjective happiness (OR = 0.926; 95% CI = 0.880, 0.973; p=0.003). Conclusions: Poor subjective economic status of elderly people may result in absence of EOL conversation experience with their families and friends, hindering the elderly from sharing and understanding the EOL preferences. To promote PCs about EOL, gerontology and public health professionals should give special consideration to the subjective economic status of elderly people.
Data from: Phylogenomic incongruence, hypothesis testing, and taxonomic sampling: the monophyly of characiform fishes
Phylogenomic studies using genome‐wide datasets are quickly becoming the state of the art for systematics and comparative studies, but in many cases, they result in strongly supported incongruent results. The extent to which this conflict is real depends on different sources of error potentially affecting big datasets (assembly, stochastic, and systematic error). Here, we apply a recently developed methodology (GGI or gene genealogy interrogation) and data curation to new and published datasets with more than 1000 exons, 500 ultraconserved element (UCE) loci, and transcriptomic sequences that support incongruent hypotheses. The contentious non‐monophyly of the order Characiformes proposed by two studies is shown to be a spurious outcome induced by sample contamination in the transcriptomic dataset and an ambiguous result due to poor taxonomic sampling in the UCE dataset. By exploring the effects of number of taxa and loci used for analysis, we show that the power of GGI to discriminate among competing hypotheses is diminished by limited taxonomic sampling, but not equally sensitive to gene sampling. Taken together, our results reinforce the notion that merely increasing the number of genetic loci for a few representative taxa is not a robust strategy to advance phylogenetic knowledge of recalcitrant groups. We leverage the expanded exon capture dataset generated here for Characiformes (206 species in 23 out of 24 families) to produce a comprehensive phylogeny and a revised classification of the order.
Data from: Fine-scale landscape genetics of the American badger (Taxidea taxus): disentangling landscape effects and sampling artifacts in a poorly understood species
Landscape genetics is a powerful tool for conservation because it identifies landscape features that are important for maintaining genetic connectivity between populations within heterogeneous landscapes. However, using landscape genetics in poorly understood species presents a number of challenges, namely, limited life history information for the focal population and spatially biased sampling. Both obstacles can reduce power in statistics, particularly in individual-based studies. In this study, we genotyped 233 American badgers in Wisconsin at 12 microsatellite loci to identify alternative statistical approaches that can be applied to poorly understood species in an individual-based framework. Badgers are protected in Wisconsin owing to an overall lack in life history information, so our study utilized partial redundancy analysis (RDA) and spatially lagged regressions to quantify how three landscape factors (Wisconsin River, Ecoregions and land cover) impacted gene flow. We also performed simulations to quantify errors created by spatially biased sampling. Statistical analyses first found that geographic distance was an important influence on gene flow, mainly driven by fine-scale positive spatial autocorrelations. After controlling for geographic distance, both RDA and regressions found that Wisconsin River and Agriculture were correlated with genetic differentiation. However, only Agriculture had an acceptable type I error rate (3–5%) to be considered biologically relevant. Collectively, this study highlights the benefits of combining robust statistics and error assessment via simulations and provides a method for hypothesis testing in individual-based landscape genetics.
Data from: Multiple continental radiations and correlates of diversification in Lupinus (Leguminosae): testing for key innovation with incomplete taxon sampling
Replicate radiations provide powerful comparative systems to address questions about the interplay between opportunity and innovation in driving episodes of diversification and the factors limiting their subsequent progression. However, such systems have been rarely documented at intercontinental scales. Here, we evaluate the hypothesis of multiple radiations in the genus Lupinus (Leguminosae), which exhibits some of the highest known rates of net diversification in plants. Given that incomplete taxon sampling, background extinction, and lineage-specific variation in diversification rates can confound macroevolutionary inferences regarding the timing and mechanisms of cladogenesis, we used Bayesian relaxed clock phylogenetic analyses as well as MEDUSA and BiSSE birth–death likelihood models of diversification, to evaluate the evolutionary patterns of lineage accumulation in Lupinus. We identified 3 significant shifts to increased rates of net diversification (r) relative to background levels in the genus (r = 0.18–0.48 lineages/myr). The primary shift occurred approximately 4.6 Ma (r = 0.48–1.76) in the montane regions of western North America, followed by a secondary shift approximately 2.7 Ma (r = 0.89–3.33) associated with range expansion and diversification of allopatrically distributed sister clades in the Mexican highlands and Andes. We also recovered evidence for a third independent shift approximately 6.5 Ma at the base of a lower elevation eastern South American grassland and campo rupestre clade (r = 0.36–1.33). Bayesian ancestral state reconstructions and BiSSE likelihood analyses of correlated diversification indicated that increased rates of speciation are strongly associated with the derived evolution of perennial life history and invasion of montane ecosystems. Although we currently lack hard evidence for "replicate adaptive radiations" in the sense of convergent morphological and ecological trajectories among species in different clades, these results are consistent with the hypothesis that iteroparity functioned as an adaptive key innovation, providing a mechanism for range expansion and rapid divergence in upper elevation regions across much of the New World.
Data from: Taxonomic survey of Agaricomycetes (Fungi: Basidiomycota) in Ontario tallgrass prairies determined by fruiting body and soil rDNA sampling
The fungal composition of North America's grasslands is poorly known, but an important area of study due to grassland conservation concerns and their close relation to agricultural lands. This study is a survey of Agaricomcyetes from fifteen diverse tallgrass prairies across southwestern Ontario, determined through fruiting body surveys (above-ground) and next-generation sequencing of soil ribosomal DNA (below-ground), and makes comparisons between the results of these two techniques. The most species rich taxa were the Clavariaceae, Hygrophoraceae, and Entolomataceae, each detected by both techniques, with the addition of the Sebacinaceae and Polyporaceae sensu lato below-ground, and Hymenogastraceae (Hebeloma spp.) and Mycenaceae above-ground. Many of the most abundant species belonged to these species-rich taxa and were highly abundant by either technique. The above-ground surveys found at least 73 species and the below-ground technique 238 operatonal taxonomic units. Although many fine-scale taxa (species and approximate families) were unique to one technique or the other (only eight genetic species were shared between both), the below-ground technique uncovered a greater breadth of higher taxa (mostly equivalent to orders), including ones undetected by the above-ground technique. A review of grassland fungi surveys around the world shows many similarities and the potential for grassland fungal conservation in North America. Given current technological advancements and grassland conservation concerns, it is prudent to further study North America's grassland fungi.
Data from: Next-generation sampling: pairing genomics with herbarium specimens provides species-level signal in Solidago (Asteraceae)
Premise of the study: The ability to conduct species delimitation and phylogeny reconstruction with genomic data sets obtained exclusively from herbarium specimens would rapidly enhance our knowledge of large, taxonomically contentious plant genera. In this study, the utility of genotyping by sequencing is assessed in the notoriously difficult genus Solidago (Asteraceae) by attempting to obtain an informative single-nucleotide polymorphism data set from a set of specimens collected between 1970 and 2010. Methods: Reduced representation libraries were prepared and Illumina-sequenced from 95 Solidago herbarium specimen DNAs, and resulting reads were processed with the nonreference Universal Network-Enabled Analysis Kit (UNEAK) pipeline. Multidimensional clustering was used to assess the correspondence between genetic groups and morphologically defined species. Results: Library construction and sequencing were successful in 93 of 95 samples. The UNEAK pipeline identified 8470 single-nucleotide polymorphisms, and a filtered data set was analyzed for each of three Solidago subsections. Although results varied, clustering identified genomic groups that often corresponded to currently recognized species or groups of closely related species. Discussion: These results suggest that genotyping by sequencing is broadly applicable to DNAs obtained from herbarium specimens. The data obtained and their biological signal suggest that pairing genomics with large-scale herbarium sampling is a promising strategy in species-rich plant groups.
Data from: Detection of invasive mosquito vectors using environmental DNA (eDNA) from water samples
Repeated introductions and spread of invasive mosquito species (IMS) have been recorded on a large scale these last decades worldwide. In this context, members of the mosquito genus Aedes can present serious risks to public health as they have or may develop vector competence for various viral diseases. While the Tiger mosquito (Aedes albopictus) is a well-known vector for e.g. dengue and chikungunya viruses, the Asian bush mosquito (Ae. j. japonicus) and Ae. koreicus have shown vector competence in the field and the laboratory for a number of viruses including dengue, West Nile fever and Japanese encephalitis. Early detection and identification is therefore crucial for successful eradication or control strategies. Traditional specific identification and monitoring of different and/or cryptic life stages of the invasive Aedes species based on morphological grounds may lead to misidentifications, and are problematic when extensive surveillance is needed. In this study, we developed, tested and applied an environmental DNA (eDNA) approach for the detection of three IMS, based on water samples collected in the field in several European countries. We compared real-time quantitative PCR (qPCR) assays specific for these three species and an eDNA metabarcoding approach with traditional sampling, and discussed the advantages and limitations of these methods. Detection probabilities for eDNA-based approaches were in most of the specific comparisons higher than for traditional survey and the results were congruent between both molecular methods, confirming the reliability and efficiency of alternative eDNA-based techniques for the early and unambiguous detection and surveillance of invasive mosquito vectors. The ease of water sampling procedures in the eDNA approach tested here allows the development of large-scale monitoring and surveillance programs of IMS, especially using citizen science projects.
Data from: Examining temporal sample scale and model choice with spatial capture-recapture models in the common leopard Panthera pardus
Many large carnivores occupy a wide geographic distribution, and face threats from habitat loss and fragmentation, poaching, prey depletion, and human wildlife-conflicts. Conservation requires robust techniques for estimating population densities and trends, but the elusive nature and low densities of many large carnivores make them difficult to detect. Spatial capture-recapture (SCR) models provide a means for handling imperfect detectability, while linking population estimates to individual movement patterns to provide more accurate estimates than standard approaches. Within this framework, we investigate the effect of different sample interval lengths on density estimates, using simulations and a common leopard (Panthera pardus) model system. We apply Bayesian SCR methods to 89 simulated datasets and camera-trapping data from 22 leopards captured 82 times during winter 2010–2011 in Royal Manas National Park, Bhutan. We show that sample interval length from daily, weekly, monthly or quarterly periods did not appreciably affect median abundance or density, but did influence precision. We observed the largest gains in precision when moving from quarterly to shorter intervals. We therefore recommend daily sampling intervals for monitoring rare or elusive species where practicable, but note that monthly or quarterly sample periods can have similar informative value. We further develop a novel application of Bayes factors to select models where multiple ecological factors are integrated into density estimation. Our simulations demonstrate that these methods can help identify the "true" explanatory mechanisms underlying the data. Using this method, we found strong evidence for sex-specific movement distributions in leopards, suggesting that sexual patterns of space-use influence density. This model estimated a density of 10.0 leopards/100 km2 (95% credibility interval: 6.25–15.93), comparable to contemporary estimates in Asia. These SCR methods provide a guide to monitor and observe the effect of management interventions on leopards and other species of conservation interest.
Data from: DNA barcoding and metabarcoding of standardized samples reveal patterns of marine benthic diversity
Documenting the diversity of marine life is challenging because many species are cryptic, small, and rare, and belong to poorly known groups. New sequencing technologies, especially when combined with standardized sampling, promise to make comprehensive biodiversity assessments and monitoring feasible on a large scale. We used this approach to characterize patterns of diversity on oyster reefs across a range of geographic scales comprising a temperate location [Virginia (VA)] and a subtropical location [Florida (FL)]. Eukaryotic organisms that colonized multilayered settlement surfaces (autonomous reef monitoring structures) over a 6-mo period were identified by cytochrome c oxidase subunit I barcoding (>2-mm mobile organisms) and metabarcoding (sessile and smaller mobile organisms). In a total area of ∼15.64 m2 and volume of ∼0.09 m3, 2,179 operational taxonomic units (OTUs) were recorded from 983,056 sequences. However, only 10.9% could be matched to reference barcodes in public databases, with only 8.2% matching barcodes with both genus and species names. Taxonomic coverage was broad, particularly for animals (22 phyla recorded), but 35.6% of OTUs detected via metabarcoding could not be confidently assigned to a taxonomic group. The smallest size fraction (500 to 106 μm) was the most diverse (more than two-thirds of OTUs). There was little taxonomic overlap between VA and FL, and samples separated by ∼2 m were significantly more similar than samples separated by ∼100 m. Ground-truthing with independent assessments of taxonomic composition indicated that both presence–absence information and relative abundance information are captured by metabarcoding data, suggesting considerable potential for ecological studies and environmental monitoring.
Data for "Advanced momentum sampling and Maslov phases for a precise semiclassical model of strong-field ionization"
<p>Data and plot scripts used to produce the figures in "Advanced momentum sampling and Maslov phases for a precise semiclassical model of strong-field ionization", available in preprint on arXiv <a href="https://doi.org/10.48550/arXiv.2311.01845">https://doi.org/10.48550/arXiv.2311.01845.</a></p><p>Abstract: Recollision processes are fundamental to strong-field physics and attoscience, thus models connecting recolliding trajectories to quantum amplitudes are a crucial part in furthering understanding of these processes. We report developments in the semiclassical path-integral-based Coulomb quantum-orbit strong-field approximation model for strong-field ionization by including an additional phase known as Maslov's phase and implementing a new solution strategy via Monte-Carlo-style sampling of the initial momenta. In doing so, we obtain exceptional agreement with solutions to the time-dependent Schrödinger equation for hydrogen, helium, and argon. We provide an in-depth analysis of the resulting photoelectron momentum distributions for these targets, facilitated by the quantum-orbits arising from the solutions to the saddle-point equations. The analysis yields a new class of rescattered trajectories that includes the well-known laser-driven long and short trajectories, along with novel Coulomb-driven rescattered trajectories. By virtue of the precision of the model, it opens the door to detailed investigations of a plethora of strong-field phenomena such as photoelectron holography, laser-induced electron diffraction and high-order above threshold ionization.</p><p>For more information on the files and their content, see the README file.</p>
Denoising Autoencoders for Phenotype Stratification (DAPS) Sample Simulated Patient Data
<p>Generated with https://github.com/greenelab/DAPS/</p>
Informative data about the biological sample studied in the article "Nineteenth century French rose (Rosa sp.) germplasm shows a shift over time from a European to an Asian genetic background"
<p>Informative data about the biological sample studied in the article "Nineteenth century French rose (<em>Rosa </em>sp.) germplasm shows a shift over time from a European to an Asian genetic background" published in Journal of Experimental Botany (https://doi.org/10.1093/jxb/erw269)</p>
Sampling data accompanying "An aerosol activation metamodel of v1.2.0 of the pyrcel cloud parcel model: Development and offline assessment for use in an aerosol-climate model"
<p>Datasets recording sampling results, accompanying the manuscript <em>An aerosol activation metamodel of v1.2.0 of the pyrcel cloud parcel model: Development and offline assessment for use in an aerosol-climate model, </em>Rothenberg, D. and Wang, C., submitted, GMD. Please see the included README for more details.</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.