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4,669 results for “Environment;”
Environment and genotype influence on Populus tremuloides condensed tannin composition
<p>This dataset contains concentration and molecular structural information (mean degree of polymerization, procyanidin:prodelphinidin ratios, stereochemistry) describing condensed tannins in <em>Populus tremuloides</em> (aspen) tree foliage in different genotypes and in response to altered environmental conditions (warming, freeze damage, ozone exposure, elevated carbon dioxide, elevated soil nutrients, altered soil microbiome, mammal browsing, and insect herbivory).</p>
Supporting data for: Immersive information seeking - a scoping review of information seeking in virtual reality environments
<p>Dataset that contains of all reviewed research items obtained for the Scoping Literature Review <em>Immersive information seeking - a scoping review of information seeking in virtual reality environments</em>.</p>
Figures and Data Set of "The Effelsberg survey of FU Orionis and EX Lupi objects I. - Host environments of FUors/EXors traced by NH3"
<p>This is the full version of Figure 1 and the fits files for the NH<sub>3</sub> detections for the paper "The Effelsberg survey of FU Orionis and EX Lupi objects I. - Host environments of FUors/EXors traced by NH<sub>3</sub>".</p> <p>The paper is published in Astronomy & Astrophysics, and can be found at: <a href="https://doi.org/10.1051/0004-6361/202244911">https://doi.org/10.1051/0004-6361/202244911</a></p> <p> </p>
Carryover effects in a sea star: Juvenile resource availability does not compensate for a poor larval environment
<p><span>Carryover effects are widespread in nature and can link early-life experiences to the regulation of populations. However, for organisms with complex life cycles, it is unclear whether offspring can overcome negative early-life experiences when provided with abundant post-metamorphic resources. We tested this by rearing larvae of the keystone sea star </span><em>Asterias forbesi</em><span>, under high or low food conditions, and then reared the juveniles for 2–3 weeks under one of four food treatments. Larvae reared under low food conditions took longer to reach metamorphosis and settled as smaller juveniles with fewer spines. For early settlers (mean age at settlement = 24.0 d), carryover effects of low larval food significantly reduced post-metamorphic size, mussel consumption and growth. However for late settlers (mean age at settlement = 29.3 d), there were no carryover effects of larval food availability detected post-metamorphosis. The differences between early and late settlers may indicate a trade-off between larval duration and the presence of carryover effects. Our data suggest that carryover effects mediated by body size at settlement could determine post-metamorphic survival, growth, and performance, ultimately impacting the recruitment of this keystone predator.</span></p>
Does competitive asymmetry confer polyploid advantage under changing environments?
<p>Competitive interactions drive critical ecological processes in plant communities. Yet how competitive interactions are influenced by polyploidy which has a widespread incidence in plants remains largely unknown.</p> <p>To evaluate the hypothesis of competitive asymmetry between polyploids and diploids, we set up competing tetraploid and diploid plants of perennial herbaceous <em>Chrysanthemum indicum</em> L. (Asteraceae) at different relative frequencies under contrasting soil water contents. We quantified the interaction intensity between competing plants of the same (intraploidy) and different (interploidy) ploidy levels, and measured functional traits related to gas exchange and plant water use to understand the underlying mechanisms.</p> <p>The stronger competitive effect of tetraploids on diploids than that of diploids on tetraploids provided evidence for the competitive asymmetry. As a stronger competitor, tetraploids were limited more by individuals of their own than by diploids. Such competitive asymmetry was not only maintained under reduced soil water content, but also translated into higher aboveground biomass of tetraploids. Tetraploids showed more resource-acquisitive traits than diploids under high soil water content and more resource-conservative traits under reduced soil water content. As such, the higher trait plasticity in tetraploids than diploids likely explained the competitive asymmetry.</p> <p><em>Synthesis</em>. These results elucidate the nature and magnitude of species interactions between polyploid and diploid plants under changing environments and the underlying mechanisms, and provide important insights into the prevalence and persistence of polyploid plants under a changing climate.</p>
# Blocks? Graphs? Why Not Both? Designing and Evaluating a Hybrid Programming Environment for End-users: Replication Package
<p><strong>Blocks? Graphs? Why Not Both? Designing and Evaluating a Hybrid Programming Environment for End-users: Replication Package</strong></p> <p>This repository contains supplementary materials for the paper "Blocks? Graphs? Why Not Both? Designing and Evaluating a Hybrid Programming Environment for End-users". We provide this data for transparency reasons and to support replications of our experiemnts.</p> <p><em>Note: This package is anonymized for peer review purposes. We will provide contact information for the authors at a later date. We also plan to add interactive versions of our tasks and tutorials in an updated version to allow readers easier exploration/experimentation.</em></p> <p><strong>Summary of files contained in this package</strong></p> <p>This package contains two parts:</p> <ul> <li> <p>The <code>data-analysis/</code> folder contains the raw dataset we collected for our experiment in CSV format, as well as scripts we used for our analyses.</p> <ul> <li>Column <code>ID</code> contains a unique 4-digit identifier for each participant that they were assigned throughout our study.</li> <li>Column <code>Group</code> contains the group (Blocks/Graph) that participants were randomly assigned to.</li> <li>Columns <code>Task1Time</code> and <code>Task2Time</code> contain the time participants spent to complete the two programming tasks of our study in minutes.</li> <li>Columns <code>Task1Success</code> and <code>Task2Success</code> contain a boolean value indicating whether the participants successfully completed the given task. Note that participants had unlimited attempts until they timed out after a strict time limit of 30 minutes, so if a participant was unsuccessful the corresponding time value is 30.</li> <li>Columns <code>Task1Tests</code> and <code>Task2Tests</code> contain the number of times a participant executed their code throughout a task, including their final submission if they were successful.</li> <li>Columns <code>LearnTask</code>, <code>ReadTask</code> and <code>WriteTask</code> contain the scores that participants gave to the task editor component of their assigned programming environment. There are 3 scores for the categories "learnability", "readability" and "writability". Scores are on a 5-point scale from 1 (worst) to 5 (best).</li> <li>Columns <code>LearnTrig</code>, <code>ReadTrig</code> and <code>WriteTrig</code> contain the scores that participants gave to the trigger editor component of their assigned programming environment. There are 3 scores for the categories "learnability", "readability" and "writability". Scores are on a 5-point scale from 1 (worst) to 5 (best).</li> <li>Columns <code>LearnComp</code>, <code>ReadComp</code> and <code>WriteComp</code> contain the scores that participants gave to their assigned assigned programming environment in direct comparison to the other alternative. There are 3 scores for the categories "learnability", "readability" and "writability". Unlike in the paper, where scores are on a scale from -2 to 2, the raw scores here are on a 5-point scale from 1 (strong preference for other environment) to 5 (strong preference for own environment).</li> <li>The script <code>survival.py</code> was used to perform the survival analysis presented in the paper and generate the related figure.</li> <li>The script <code>batplot.py</code> was used to generate the 3x3 grid of ratings used in a figure in the paper.</li> </ul> </li> <li> <p>The <code>materials/</code> folder contains the tutorials and task descriptions we presented to study participants. It also contains the exact wording of pre-screening and post-experiemental survey questions.</p> <ul> <li>The image <code>pre-screening.png</code> shows the three pre-screening questions we used to determine whether our participants could be included in our study.</li> <li>The images <code>tutorial1_instructions.png</code> and <code>tutorial1_sim.png</code> contain the instructions and initial simulator state we provided to participants for the first programming tutorial. This tutorial did not provide starter code and was identical for both participant groups.</li> <li>The images <code>tutorial2_instructions.png</code> and <code>tutorial2_sim.png</code> contain the instructions and initial simulator state we provided to participants for the second programming tutorial. This tutorial was identical for both participant groups and provided participants with starter code, which is shown in the images: <ul> <li><code>tutorial2_code_main.png</code> for the main program in the left canvas</li> <li><code>tutorial2_code_move.png</code> for the definition of "Move box to the right".</li> </ul> </li> <li>The images <code>tutorial3_instructions_blocks.png</code>/<code>tutorial3_instructions_graph.png</code> and <code>tutorial3_sim.png</code> contain the instructions and initial simulator state we provided to participants for the third programming tutorial. This tutorial also provided participants with starter code, which is shown in the images: <ul> <li><code>tutorial3_code_main.png</code> for the main program in the left canvas</li> <li><code>tutorial3_code_pick.png</code> for the definition of "Pick up box"</li> <li><code>tutorial3_code_place.png</code> for the definition of "Place box"</li> </ul> </li> <li>The images <code>task1_instructions.png</code> and <code>task1_sim.png</code> contain the instructions and initial simulator state we provided to participants for the first programming task. The task did not provide starter code and the instructions were identical for both participant groups.</li> <li>The images <code>task2_instructions.png</code> and <code>task2_sim.png</code> contain the instructions and initial simulator state we provided to participants for the second programming task. The instructions were identical for both groups. This task also provided participants with starter code, which is shown in the images: <ul> <li><code>task2_code_main.png</code> for the main program in the left canvas</li> <li><code>task2_code_pick_prog.png</code> for the definition of "Pick up block"</li> <li><code>task2_code_load_trig_blocks.png</code>/<code>task2_code_load_trig_graph.png</code> for the definition of the trigger "Ready to load machine"</li> <li><code>task2_code_load_prog.png</code> for the definition of "Load and activate machine"</li> <li><code>task2_code_finished_trig_blocks.png</code>/<code>task2_code_finished_trig_graph.png</code> for the definition of the trigger "Machine finished"</li> <li><code>task2_code_finished_prog1.png</code> for the definition of "Get block from machine"</li> <li><code>task2_code_finished_prog2.png</code> for the definition of "Place block in bin"</li> </ul> </li> <li>The image <code>usability.png</code> shows the usability questions we used to determine a participant's rating of their assigned programming environment. The questions were identical for both participant groups.</li> <li>The images <code>comprehension_blocks_1.png</code> and <code>comprehension_blocks_2.png</code> show the program comprehension questions we used to determine whether participants in the Blocks group could understand more complex triggers.</li> <li>The images <code>comprehension_graph_1.png</code> and <code>comprehension_graph_2.png</code> show the program comprehension questions we used to determine whether participants in the Graph group could understand more complex triggers.</li> <li>The images <code>comparison_blocks.png</code> and <code>comparison_graph.png</code> show the images of triggers in the alternative environment that we showed to our participants before choosing their preferred environment. The questions were identical for both participant groups.</li> <li>The image <code>comparison.png</code> shows the questions we used to determine a participant's preference between the two programming environment alternatives.</li> </ul> </li> </ul>
Interview guide from the paper "Act Against the Aggression A Preliminary Model of a Digital Platform Aimed at Cyberaggressions in the Portuguese University Environment"
<p>Interview guide used in the study "Act Against the Aggression A Preliminary Model of a Digital Platform Aimed at Cyberaggressions in the Portuguese University Environment".</p>
Data and codes for: Experimental evolution of evolutionary potential in fluctuating environments
<p>This supplementary data contains raw data for a publication: "Experimental evolution of evolutionary potential in fluctuating environments." 1) Raw data of optical density measurements (10 .csv files), 2) R-code for obtaining maximal growth rate and maximum biomass yield from measurements. 3) resulting data file 4) R-code for Bayesian analysis of the data.</p>
Wide-Area Geolocalization with a Limited Field of View Camera in Challenging Urban Environments Dataset
<p>Rectified imagery with latitude and longitude tags for paths driven throughout Cambridge and Boston, MA in November 2022. Faces and license plates have been blurred for anonymity. Dataset created for “Wide-Area Geolocalization with a Limited Field of View Camera in Challenging Urban Environments” paper, currently under review in IEEE Transactions on Robotics. Lena M. Downes is a Draper Scholar at MIT.</p>
DeepREM: Deep-Learning-Based Radio Environment Map Estimation from Sparse Measurements
<p><strong>DeepREM: Deep-Learning-Based Radio Environment Map Estimation from Sparse Measurements</strong></p> <p>DeepREM combines two deep-learning models (U-Net and CGAN) that estimate Radio Environment Maps (REMs) from sparse measurements. In this repository, we present the dataset and the interactive app developed to use the resulting models derived from the research. </p> <p><strong>Urban REMs dataset: </strong>We present a (REM) dataset of urban scenarios. Each map provides coverage information in areas from 2290 x 3670 m<sup>2</sup> to 3810 x 5160 m<sup>2</sup> with a resolution of 10 m. Coverage areas are sampled from Colombian cities (Armenia, Bogota, Cali, Ibague, Manizales, Medellin, and Pasto) and U.S. cities (Columbus and Washington). The simulations include topographic and building vector database information and Intelligent Ray-Tracing as a propagation model.</p> <p>In our <strong>second version</strong>, 400 new REMs were added to the dataset, including 4 new city areas with different topographic and building features (100 REMs for each area). The new cities are Barranquilla, Bucaramanga, Popayan, and North Pasto, all in Colombia. In addition, we also present an interactive application developed in the Streamlit framework to test CGAN and UNET performance in RSRP and BS coverage predictions either with REMs from our dataset or with completely new user-supplied REMs.The repository of the app can be downloaded at the following link: <a href="https://gitlab.com/andreajohanacv/deeprem">DeepREMapp</a></p>
Dataset from Nature Materials paper: Amorphous nickel hydroxide shell tailors local chemical environment on platinum surface for alkaline hydrogen evolution reaction
<p>Dataset of the paper "Amorphous nickel hydroxide shell tailors local chemical environment on platinum surface for alkaline hydrogen evolution reaction" accepted in Nature Materials.</p> <p>- GCGA_inputs.zip: A zip file containing all needed input files to run a grand canonical genetic algorithm (GCGA) global optimization structure search. Note that the script would need modifications to be compatible with later version of the GOCIA package, please following the most updated instructions at https://github.com/zishengz/gocia</p> <p>- GCGA_Ni12OxHy_all_samples.db: An ASE database file containing all unique structures from the GCGA search of Ni12OxHy on a Pt(111) surface. </p> <p>- GM_Ni12O25H13.vasp: The structure of the global minimum structure from GCGA search, which is also the surface structure we focused on in this study, in VASP structure format.</p> <p>- rxn_structures.zip: A zip file containing the structures of reaction intermediates investigated in this work, in VASP structure format</p> <p> </p>
AVLEN: Audio-Visual-Language Embodied Navigation in 3D Environments - Supplementary Data
<p><strong>Introduction</strong></p> <p>In this zip, we release the auxiliary data that is beneficial to execute the implementation of AVLEN described in our paper AVLEN: Audio-Visual-Language Embodied Navigation in 3D Environments by Sudipta Paul, Amit K Roy-Chowdhury, and Anoop Cherian, NeurIPS, 2022.</p> <p><strong>At a Glance</strong></p> <ul> <li>The size of the unzipped data is 4.6G</li> <li>The unzipped folder contains: (i) a README.md file and (ii) ./AVLEN-data folder. The latter contains the following zip files. Please see the AVLEN code to see how to unzip these files into their respective folders. <ul> <li>ckpt.119.pth -- 61M </li> <li>connectivity.zip -- 1.4M </li> <li>pretrained_weights.zip -- 1.7G</li> <li>ResNet-152-imagenet.zip -- 2.9G</li> <li>semantic_audionav_dialog_approx.zip -- 2.7M</li> <li>soundspaces.zip -- 479K</li> <li>speaker_model_weights.zip -- 51M</li> </ul> </li> </ul> <p><strong>Other Resources</strong></p> <p>For the implementation of AVLEN that uses the data shared here, please visit <a href="https://www.merl.com/publications/TR2022-131">MERL TR2022-131</a>.</p> <p><strong>Citation</strong></p> <p>If you use AVLEN in your research, please cite our paper:</p> <pre><code>@InProceedings{paul2022avlen, title={AVLEN: Audio-Visual-Language Embodied Navigation in 3D Environments}, booktitle={Advances in Neural Information Processing Systems}, author={Paul, Sudipta and Roy-Chowdhury, Amit and Cherian, Anoop}, volume={35}, pages={6236--6249}, year={2022} }</code></pre> <p><strong>Copyright and License</strong></p> <p>The AVLEN dataset is released under CC-BY-SA-4.0 license.</p> <p>All data:</p> <pre><code>Created by Mitsubishi Electric Research Laboratories (MERL), 2023 SPDX-License-Identifier: CC-BY-SA-4.0</code></pre> <p> </p>
Developmental environment has lasting effects on amphibian behavior and thermal physiology
<p>Environmental challenges early in development can result in complex phenotypic trade-offs and long-term effects on individual physiology, performance, and behavior, with implications for disease and predation risk. We examined the effects of simulated pond-drying and elevated water temperatures on development, growth, thermal physiology, and behavior in a widespread North American amphibian, the Southern leopard frog, <em>Rana sphenocephala</em>. Tadpoles were raised in outdoor mesocosms under warming and drying regimes based on projected climatic conditions in 2070. We predicted that amphibians experiencing the rapid pond drying and elevated pond temperatures associated with climate change would accelerate development, be smaller at metamorphosis and demonstrate long-term differences in physiology and exploratory behavior post-metamorphosis. While both drying and warming accelerated development and reduced survival to metamorphosis, only drying resulted in smaller animals at metamorphosis. At approximately one month post-metamorphosis, animals from the control (ambient no-drying) treatment jumped relatively farther at high temperatures in jumping trials. In addition, across all treatments, frogs with shorter larval periods had lower critical thermal minima and maxima. We also found evidence that developing under warming and drying resulted in a less exploratory behavioral phenotype, and that drying, but not warming, resulted in warmer thermal preferences. Furthermore, behavior predicted thermal preference, with less exploratory animals selecting higher temperatures. Our results underscore the multi-faceted effects of early developmental environments on behavioral and physiological phenotypes later in life. For example, thermal preferences can influence disease risk through behavioral thermoregulation, and exploratory behavior may increase risk of predation or pathogen encounter. By impacting thermal physiology, behavior, and various physiological traits, climatic stressors during development may mediate amphibian exposure and susceptibility to predators and pathogens into adulthood.</p>
Datasets for Russell & Jones, Transport and eruption of mantle xenoliths creates a lagging problem, Communications Earth and Environment
<p>Example datasets for Russell & Jones, Transport and eruption of mantle xenoliths creates a lagging problem, Communications Earth and Environment </p>
Increased eye size is favoured in Trinidadian killifish experimentally transplanted into low light, high competition environments
<p>Intraspecific <span>variation in vertebrate eye size is well known. Ecological factors such as light availability are often correlated with shifts in relative eye size. However, experimental tests of selection on eye size are lacking. Trinidadian killifish (<em>Anablepsoides hartii</em>) are found in sites that differ in predation intensity. Sites that lack predators are characterized by lower light, high killifish densities, low resource availability, and intense competition for food. We previously found that killifish in sites that lack predators have evolved a larger relative eye size than fish from sites with predators. Here we used transplant experiments to test how selection operates on eye size when fish that are adapted to sites with predators are translocated into sites where predators are absent. We observed a significant 'population x relative eye size' interaction; the relationship between relative eye size and a proxy for fitness (rates of individual growth) was positive in the transplanted fish. The trend was opposite for resident fish. Such results provide experimental support that larger eyes enhance fitness and are favoured in environments characterized by low light and high competition.</span></p>
Multi-Environment Audio Dataset using RPi based Sound Logger
<p>The proposed dataset is a compilation of 10-12 audios from diverse environments. These audio sets are recorded using a portable sound logger. The audios(.wav audio file format) range from 30-60 mins with sampling frequency of 44.1KHz. Comprehensive literature illustrating the details of the system under test as well as the acoustic conditions around it can be found in the attached paper. The primary aim of releasing this database is to foster research in the field of medicine, especially otology along with other areas such as speech recognition, event detection, anomaly detection, etc.</p>
Raw data for: Sex and population differences underlie variation in reproductive success in a warming environment
<p>Current rising temperatures are threatening biodiversity. It is therefore crucial to understand how climate change impacts male and female fertility and whether evolutionary responses can help in coping with heat stress. We use experimental evolution to study male and female fertility during real-time evolution of two historically differentiated populations of <em>Drosophila</em> <em>subobscura</em> under different thermal selection regimes for 23 generations. We aim to (1) tease apart sex-specific differences in fertility after exposure to warming conditions during development, (2) test whether thermal selection can enhance fertility under thermal stress, and (3) address the role of historically distinct genetic backgrounds. Contrary to expectations, heat stress during development had a higher negative impact on female fertility than on male fertility. We did not find clear evidence for enhanced fertility in males or females evolving under warming conditions. Population history had a clear impact on fertility response under thermal stress, particularly in males with those from lower latitudes presenting better performance than their higher latitude counterparts. We show that the impact of thermal stress on fertility varies between traits, sexes and genetic backgrounds. Incorporating these several levels of variation is crucial for a deeper understanding of how fertility evolves under climate change.</p>
Data for: Environments and hosts structure the bacterial microbiomes of fungus-gardening ants and their symbiotic fungus gardens
<p>The fungus gardening-ant system is considered a complex, multi-tiered symbiosis between the ants, their fungus, and microorganisms associated with either ants or fungus. We examine the bacterial microbiome of <em>Trachymyrmex septentrionalis</em> and <em>Mycetomoellerius turrifex</em> ants and their symbiotic fungus garden, using 16S rRNA Illumina sequencing, over a large geographical region. Typically microorganisms can be acquired from a parent colony (vertical transmission) or from the environment (horizontal transmission). Because the symbiosis is characterized by co-dispersal of the ants and fungus, elements of both ant and fungus garden microbiome could be characterized by vertical transmission, for example. The goals of this study were to explore how both the ant and fungus garden bacterial microbiome were acquired. The main findings were that different mechanisms appear to explain the structure the microbiomes of ants and their symbiotic fungus gardens. Ant associated microbiomes had a strong host ant signature, which suggests vertical inheritance of the ant associated bacterial microbiome. On the other hand, the bacterial microbiome of the fungus garden was more complex in that some components appear to be structured by the ant host species whereas other by fungal lineage or region. Thus bacteria in fungus gardens appear to be acquired both horizontally and vertically. </p>
Geography, environment, and colonization history interact with morph type to shape genomic variation in an Arctic fish
<p><span>Polymorphic species are useful models for investigating the evolutionary processes driving diversification. Such processes include colonization history as well as contemporary selection, gene flow, and genetic drift, which can vary between intraspecific morphs as a function of their distinct life histories. The interactive and relative influence of such evolutionary processes on morph differentiation critically informs morph-specific management decisions and our understanding of incipient speciation. We therefore investigated how geographic distance, environmental conditions, and colonization history interacted with morph migratory capacity in the highly polymorphic fish species, Arctic Charr (<em>Salvelinus</em> <em>alpinus</em>).</span> <span>Using an</span><span> 87k SNP chip we genetically characterized recently evolved anadromous, resident, and landlocked charr collected from 45 locations across a secondary contact zone of three charr glacial lineages in eastern Canada. A strong pattern of isolation by distance across all populations suggested geographic distance principally shaped genetic structure. Landlocked populations had lower genetic diversities and higher genetic differentiation than anadromous populations. However, genetic diversity was generally temporally stable in landlocked populations in comparison to recent decreases in anadromous populations. Genetic diversity positively correlated with latitude, potentially indicating southern anadromous populations' vulnerability to climate change and greater introgression between the Arctic and Atlantic glacial lineages in northern Labrador. Local adaptation was suggested by the observation of several environmental variables strongly associating with functionally relevant outlier genes including a region on chromosome AC21 potentially associated with anadromy. Our results demonstrate that gene flow, colonization history, and local adaptation uniquely interact to influence the genetic variation and evolutionary trajectory of populations.</span></p>
Frontopolar cortex represents complex features and decision value during choice between environments
<p><span>Important decisions often involve choosing between complex environments that define future item encounters. Despite its importance for adaptive behaviour and distinct computational challenges</span><span>, decision-making</span><span> research primarily focuses on item choice ignoring environment choice altogether. Here we contrast previously studied item choice in ventromedial prefrontal cortex with lateral frontopolar cortex (FPl) linked to environment choice. Furthermore, we propose a mechanism for how FPl decomposes and represents complex environments during decision-making. Specifically, we trained a choice-optimized, brain-naive convolutional neural network (CNN) and compared predicted CNN activation with actual FPl activity. We showed the high dimensional FPl activity decomposes environment features to represent the complexity of an environment to make such choice possible. Moreover, FPl functionally connects with posterior cingulate cortex for guiding environment choice. Further probing FPl's computation revealed a parallel processing mechanism in extracting multiple environment features.</span></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.