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1,102 results for “human use”
Data of: Imputation-free reconstructions of three-dimensional chromosome architectures in human diploid single-cells using allele-specified contacts
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Data from: Blockade of dengue virus transmission from viremic blood to Aedes aegypti mosquitoes using human monoclonal antibodies
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Large-scale neural recordings with single neuron resolution using Neuropixels probes in human cortex
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Congruence among multiple indices of habitat preference for species facing human-induced rapid environmental change: A case study using the Brewer’s sparrow
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Computationally-informed point of departure evaluation for proarrhythmic cardiotoxicity assessment using 3D engineered cardiac microtissues from human iPSC-derived cardiomyocytes
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Historical Human Causes and Uses of Fire in Alaska
Although wildfire has been central to the ecological dynamics of interior Alaska for 5000 years, the role of humans in this dynamic is not well known. As a multidisciplinary research team, together with Native community partners, we analyzed patterns of human-fire interaction in two contiguous areas of Interior Alaska occupied by different Athabaskan groups. The Koyukon Athabascans in the western Interior considered fire a destructive force and had no oral history or stories suggesting use of fire for landscape management. Low lightning strike density and moist climate constrained occurrence of lightning fires, and a subsistence dependence on a predictable resource (salmon) resulted in a relatively sedentary settlement pattern. In this environment wildfire near communities might have negatively impacted hunting opportunities. In contrast, the Gwich'in Athabascans of the eastern Interior actively used fires to manage the landscape. Lightning fires occurred more frequently here because of greater lightning strike density and warmer summer temperatures. The Gwich'in showed greater mobility in hunting their less spatially predictable subsistence base (moose and caribou), which enabled them to move when wildfires altered local habitat. These striking contrasts between two neighboring Athabaskan groups sharing a contiguous boundary indicated different use and views of fire that were consistent with cultural adaptation to local biophysical and ecological settings. This contrasts with the commonly held view that Native peoples of North America pervasively modified landscapes through use of fire.
Using psychophysical performance to predict short-term ocular dominance plasticity in human adults
<p>This is the dataset reported in the manuscript "Using psychophysical performance to predict short-term ocular dominance plasticity in human adults" published in the Journal of Vision 2020;20(7):6. doi: <a href="https://doi.org/10.1167/jov.20.7.6">https://doi.org/10.1167/jov.20.7.6</a></p> <p> </p>
Upper-body movements: precise tracking of human motion using inertial sensors
<p>The <em>Upper-body movements: precise tracking of human motion using inertial sensors</em> is a dataset composed of 11 participants' IMU data (5 women + 6 men). This collection is divided into 6 motion sets containing different motions for the upper-body.</p> <p><strong>Folder Structure</strong></p> <p>subject -> set -> IMU position -> file</p> <p>e.g. subject01 -> set6 -> forearm -> Accelerometer.txt</p> <p><strong>IMU placement </strong></p> <p>For data collection participants wore 4 IMUs:</p> <ul> <li>1 on the chest</li> <li>1 on the right arm</li> <li>1 on the right forearm</li> <li>1 on the right hand.</li> </ul> <p><strong>Sets</strong></p> <p>Each set includes:</p> <ul> <li> set1 - flexion/extension of the forearm; abduction/adduction of the arm; anatomical position</li> <li> set2 - flexion/extension of the wrist; radial/ulnar deviation of the wrist; anatomical position</li> <li> set3 - flexion/extension and lateral flexion of the torso; anatomical position</li> <li> set4 - flexion/extension of the arm; flexion/extension of the torso; anatomical position</li> <li> set5 - flexion/extension of the arm; anatomical position; anatomical position</li> <li> set6 - flexion/extension of the torso; flexion/extension of the arm; anatomical position</li> </ul> <p><strong>Annotations</strong></p> <p>This dataset is accompanied by the<em> annotations.csv</em> file.<br> Each file row present "Set,Subject,Category,Segment,Type,Init,End":</p> <ul> <li>Set - sets 1-6</li> <li>Subject - participant ID</li> <li>Category - relative or absolute. Refers to the joint angle.</li> <li>Absolute if the angle is obtained considering an anatomical plane as reference.</li> <li>Relative if the angle is obtained from one segment in relation to another.</li> <li>Type - segment at action (torso; right_arm_forearm; wrist; right_arm_sagittal)</li> <li>Init/End - time in seconds, describing the begin and end of the motion, respectively.</li> </ul> <p> </p>
Dataset and code accompanying publication: "Revealing the Physiological Origin of Event-Related Potentials using Electrocorticography in Humans"
<p>Electrocorticographic (ECoG) activity from eight human subjects; Electroencephalographic (EEG) activity from seven human subjects; recorded during a simple reaction-time task. </p> <p>For questions, contact Peter Brunner, PhD (brunner@neurotechcenter.org)</p> <p>Code written by Hohyun Cho, PhD (cho@neurotechcenter.org)</p> <p>This repository contains the MATLAB scripts (*.m) used to create the figures of this publication. </p> <p>All non-MATLAB dependencies are included in ./functions.</p> <p>MATLAB versions tested: R2017b to R2020a</p> <p>Before running the scripts, please run "add_path.m" first.</p> <p> </p> <p><strong>[MATLAB scripts reproducing the figures shown in this publication]</strong></p> <p>Figure 2: figure2A.m<br> Figure 2: figure2B_and_C.m</p> <p>Figure 2 - Figure supplement 1: figure2_supplement_1.m</p> <p>Figure 2 - Figure supplement 2: figure2_supplement_2.m</p> <p>Figure 2 - Figure supplement 3: figure2_supplement_3.m</p> <p>Figure 2 - Figure supplement 4: figure2_supplement_4.m</p> <p>Figure 3: figure3_erp_analysis.m</p> <p>Figure 3 - Figure supplement 1: figure3_supplement_1_auditory.m<br> Figure 3 - Figure supplement 1: figure3_supplement_1_motor.m</p> <p>Figure 3 - Figure supplement 2: figure3_supplement_2.m</p> <p>Figure 5: figure5.m</p> <p>Figure 5 - Figure supplement 1: figure5_supplement_1.m</p> <p>Figure 5 - Figure supplement 2: figure5_supplement_2A.m<br> Figure 5 - Figure supplement 2: figure5_supplement_2B_auditory.m<br> Figure 5 - Figure supplement 2: figure5_supplement_2B_motor.m</p> <p> </p> <p><strong>[MATLAB scripts implementing the methods presented in this publication]</strong></p> <p>removing_addivity_under_3Hz.m <br> - a script for removing effect of additivity from the evoked potentials across all subjects</p> <p>removing_phase_reset_of_ongoing_osillation.m <br> - a script for removing effect of phase resetting within ongoing oscillation from the evoked potentials across all subjects</p> <p>removing_asymmetry_of_ongoing_oscillation.m <br> - a script for removing effect of asymmetry within ongoing oscillation from the evoked potentials across all subjects</p> <p>removing_additive_power.m <br> - a script for removing additive power from the evoked potentials across all subjects</p> <p>removing_addivity_and_phase_reset.m <br> - a script for removing effect of additivity and phase resetting from the evoked potentials across all subjects</p>
African sunbirds predominantly pollinate plants useful to humans
<p>Birds provide multiple ecological services that benefit humans including pollination. In Africa, sunbirds are the <span>domi- </span>nant vertebrate pollinator. Here we present a species-level assessment for African sunbirds of the number and relative frequency of their food plants that have useful properties to humans. <span>We </span>conducted this analysis by compiling and integrating known sunbird food plants with useful tropical plant and tropical cultivated plant databases. Across Africa, 68% of the 329 genera and 44% of the 468 species of sunbirds' known food plants are used by humans for medicine, food, building materials, or other uses. <span>Yet </span>most genera and species of useful plants are visited by a small number of sunbird species. The median number of sunbird species that visit a useful genus and species of plant is two and one, re- spectively. Of the 409 genera and 308 species of useful plants that are sunbird pollinated across one or more of the <span>six </span>predominant habitats for sunbirds, 67% of genera and 71% of species are pollinated by sunbird species that are forest or woodland dependent. Additionally, 58% of all genera and 83% of all species of useful plants pollinated by sunbirds are non-cultivated. In Africa, non-cultivated sunbird-pollinated useful plants are almost entirely collected, used, and traded locally rather than regionally or internationally. Our results indicate that African sunbirds provide important ecological services as pollinators that benefit humans, and these services are provided largely at a local scale. Given the decline of invertebrate and vertebrate pollinators both globally and in Africa, sunbirds are important to the long-term conservation of many useful plants in Africa and hence human well-being.</p>
Data and software associated with PHENOstruct: Prediction of human phenotype ontology terms using heterogeneous data sources
<p>Data and software associated with the paper:</p> <p>PHENOstruct: Prediction of human phenotype ontology terms using heterogeneous data sources</p>
Parallel reverse genetic screening in mutant human cells using transcriptomics - Data and analyses
<p>This dataset contains data files and analysis code associated with manuscript entitled "Parallel reverse genetic screening in mutant human cells using transcriptomics".</p> <p>Data files include expression profiles for over 1800 RNA-seq samples and annotations.</p> <p>Analysis files include R scripts to generate summary figures.</p>
The FORTH-TRACE dataset for human activity recognition of simple activities and postural transitions using a Body Area Network
<p>The dataset is collected from 15 participants wearing 5 Shimmer wearable sensor nodes on the locations listed in Table 1. The participants performed a series of 16 activities (7 basic and 9 postural transitions), listed in Table 2.</p> <p>The captured signals are the following:</p> <ul> <li>3-axis accelerometer</li> <li>3-axis gyroscope</li> <li>3-axis magnetometer</li> </ul> <p>The sampling rate of the devices is set to 51.2 Hz.</p> <p>DATASET FILES</p> <p>The dataset contains the following files:</p> <ul> <li>partX/partXdev1.csv</li> <li>partX/partXdev2.csv</li> <li>partX/partXdev3.csv</li> <li>partX/partXdev4.csv</li> <li>partX/partXdev5.csv</li> </ul> <p>Where X corresponds to the participant ID, and numbers 1-5 to the device IDs indicated in Table 1.</p> <p>Each .csv file has the following format:</p> <ul> <li>Column1: Device ID</li> <li>Column2: accelerometer x</li> <li>Column3: accelerometer y</li> <li>Column4: accelerometer z</li> <li>Column5: gyroscope x</li> <li>Column6: gyroscope y</li> <li>Column7: gyroscope z</li> <li>Column8: magnetometer x</li> <li>Column9: magnetometer y</li> <li>Column10: magnetometer z</li> <li>Column11: Timestamp</li> <li>Column12: Activity Label</li> </ul> <p>Table 1: LOCATIONS</p> <ol> <li>Left Wrist</li> <li>Right Wrist</li> <li>Torso</li> <li>Right Thigh</li> <li>Left Ankle</li> </ol> <p>Table 2: ACTIVITY LABELS</p> <p>(Arrows (->) indicate transitions between activities)</p> <ol> <li>stand</li> <li>sit</li> <li>sit and talk</li> <li>walk</li> <li>walk and talk</li> <li>climb stairs (up/down)</li> <li>climb stairs (up/down) and talk</li> <li>stand -> sit</li> <li>sit -> stand</li> <li>stand -> sit and talk</li> <li>sit and talk -> stand</li> <li>stand -> walk</li> <li>walk -> stand</li> <li>stand -> climb stairs (up/down), stand -> climb stairs (up/down) and talk</li> <li>climb stairs (up/down) -> walk</li> <li>climb stairs (up/down) and talk -> walk and talk</li> </ol>
mRI: multi-modal 3d human pose estimation dataset using mmwave, rgb-d, and inertial sensors
<p>The ability to estimate 3D human body pose and movement, also known as human pose estimation~(HPE), enables many applications for home-based health monitoring, such as remote rehabilitation training. Several possible solutions have emerged using sensors ranging from RGB cameras, depth sensors, millimeter-Wave (mmWave) radars, and wearable inertial sensors. Despite previous efforts on datasets and benchmarks for HPE, few datasets exploit multiple modalities and focus on home-based health monitoring.</p> <p>To bridge this gap, we present <em>mRI</em>, a multi-modal 3D human pose estimation dataset with mmWave, RGB-D, and Inertial Sensors. Our dataset consists of over 5 million frames from 20 subjects performing rehabilitation exercises and supports the benchmarks of HPE and action detection. We perform extensive experiments using our dataset and delineate the strength of each modality.</p> <p>We hope that the release of <em>mRI</em> can catalyze the research in pose estimation, multi-modal learning, and action understanding, and more importantly, facilitate the applications of home-based health monitoring.</p>
Antibody panel used for multiplexed antibody-based imaging of Human Pancreas Analysis Program (HPAP) samples by CODEX
<p>This data file details antibodies applied to human pancreas tissue samples from the Human Pancreas Analysis Program (HPAP; RRID:SCR_016202) of the <a href="https://hirnetwork.org/">Human Islet Research Network</a> (HIRN; RRID:SCR_014393). Images will be uploaded for interactive analysis on <a href="https://pancreatlas.org/datasets">Pancreatlas</a> (RRID:SCR_018567) and made available for download via <a href="https://hpap.pmacs.upenn.edu/">PANC-DB</a>. Workflow is documented on protocols.io: <a href="https://dx.doi.org/10.17504/protocols.io.36wgq7dryvk5/v1">dx.doi.org/10.17504/protocols.io.36wgq7dryvk5/v1</a>.</p><p>Table format adapted from Radtke AJ, Quardokus EM, Saunders DC (2022), <a href="https://doi.org/10.5281/zenodo.7386417">SOP: Construction of Organ Mapping Antibody Panels for Multiplexed Antibody-Based Imaging of Human Tissues</a>. See also: Saunders D; Reihsmann R. <a href="https://doi.org/10.48539/HBM754.BHVR.258">OMAP-13: Organ Mapping Antibody Panel (OMAP) for Multiplexed Antibody-Based Imaging of Human Pancreas with CODEX, v1.0</a>.</p>
Use of artificial intelligence techniques for the recognition of human emotions: a bibliometric analysis
<p>Human emotion recognition with AI uses physiological, audiovisual, and linguistic signals. Despite its importance and great progress in emotion recognition, several challenges remain in generalization and evaluation through standards and shared data, as well as other research gaps. Therefore, the objective is to analyze the scientific production on the use of artificial intelligence techniques for the recognition of human emotions. This study uses bibliometric analysis following the guidelines of the PRISMA-2020 statement for literature reviews. Based on the results of the bibliometrics on the use of artificial intelligence techniques in for the recognition of human emotions, significant conclusions are obtained that improve the understanding of the current panorama in this field of research. A growing interest in the subject is observed during the years 2023, 2022, 2021 and 2020, which demonstrates the relevance and potential of artificial intelligence in the recognition of human emotions. A cubic polynomial growth in the number of scientific articles is observed, demonstrating a constant expansion of knowledge and support for future trends. Leading authors and journals are identified, highlighting global collaboration in China and India. The thematic evolution shows maturity and progressive specialization, with emerging concepts that promise future research and innovative applications.</p>
The global distribution of plants used by humans datasets: list of utilised species, occurrence data and model outputs at 10 arc-minutes spatial resolution
<p>Datasets and model outputs used to map the global distribution of utilised plants by humans. The folder is composed of two subfolders <em>raw_data</em> and <em>processed_data</em> containing respectively the list of utilised plant species modelled -<em>utilised_plants_species_list.csv</em>-, and their occurrence data -<em>occurrence_data.zip-</em> and predicted distribution -<em>species_proba_per_cell.rds-.</em></p> <p> </p> <ul> <li>The file <em>utilised_plants_species_list.csv</em> in the <em>raw_data</em> folder contains a<strong> </strong>list of 35687 plant species (and hybrids) used by humans and 10 plant use categories with the following 14 fields:</li> </ul> <p><strong>plant_ID:<em> </em></strong>plant identifier number ranging from between 1-35687</p> <p><strong>binomial_acc_name:</strong> binomial accepted name of the plant species</p> <p><strong>author_acc_name</strong>: name of the author(s)</p> <p><strong>is_hybrid:</strong> logical TRUE or FALSE indicating whether the species is an hybrid or not.</p> <p><strong>AnimalFood:</strong> forage and fodder for vertebrate animals only.</p> <p><strong>EnvironmentalUses:</strong> examples include intercrops and nurse crops, ornamentals, barrier hedges, shade plants, windbreaks, soil improvers, plants for revegetation and erosion control, wastewater purifiers, indicators of the presence of metals, pollution, or underground water.</p> <p><strong>Fuels:</strong> charcoal, petroleum substitutes, fuel alcohols, etc. Given the importance of energy plants for people, those were distinguished from Materials.</p> <p><strong>GeneSources:</strong> wild relatives of major crops which may possess traits associated with biotic or abiotic resistance and may be valuable for breeding programs.</p> <p><strong>HumanFood:</strong> food for humans only, including beverages and food additives.</p> <p><strong>InvertebrateFood:</strong> plants consumed by invertebrates used by humans, such as bees, silkworms, lac insects and edible grubs.</p> <p><strong>Materials:</strong> woods, fibers, cork, cane, tannins, latex, resins, gums, waxes, oils, lipids, etc. and their derived products.</p> <p><strong>Medicines:</strong> both human and veterinary.</p> <p><strong>Poisons:</strong> plants which are poisonous to both vertebrates and invertebrates, both accidentally and intentionally, e.g., for hunting and fishing, molluscicides, herbicides, insecticides.</p> <p><strong>SocialsUses:</strong> plants used for social purposes, which cannot be defined as food or medicine, for instance, masticatories, smoking materials, narcotics, hallucinogens and psychoactive drugs, and plants with ritual or religious significance.</p> <p><strong>Totals:</strong> total number of uses recorded for a species</p> <p> </p> <ul> <li>The zipfile <em>occurrence_data.zip</em> in the <em>processed_data</em> folder contains 35687 Comma Separated Values (CSV) files, one for each species, containing curated geographic occurrence records used to build species distribution models with the following 14 fields:</li> </ul> <p><strong>Species:</strong> the binomial accepted name of the species</p> <p><strong>Fullname:</strong> same as species</p> <p><strong>decimalLongitude:</strong> the geographic longitude of the occurrence records of the species in decimal degrees</p> <p><strong>decimalLatitude:</strong> the geographic latitude of the occurrence records of the species in decimal degrees</p> <p><strong>countryCode:</strong> a three-letter standard abbreviation for the country of the occurrence locality</p> <p><strong>coordinateUncertaintyinMeters</strong>: indicator for the accuracy of the coordinate location, described as the radius of a circle around the stated point location</p> <p><strong>year:</strong> year of the observation of the occurrence record of the species</p> <p><strong>individualCount:</strong> the number of individuals present at the time of the observation</p> <p><strong>gbifID:</strong> unique identifier number for the occurrence from the original database</p> <p><strong>basisOfRecords:</strong> the type of the individual record, e.g. observation, physical specimen, fossil, living ex-situ, culture collection specimen</p> <p><strong>institutionCode</strong>: the name of the institution or organization listed as the data publisher on GBIF</p> <p><strong>establishmentMeans:</strong> statement about whether an organism has been introduced to a given place and time through the direct or indirect activity of modern humans</p> <p><strong>is_cultivated_observation:</strong> whether or not an organism is cultivated</p> <p><strong>sourceID:</strong> name of the source database</p> <p> </p> <ul> <li>The file <em>species_proba_per_cell.rds</em> in the <em>processed_data</em> folder is<em> a R Data Serialization </em>(RDS) file containing a data.table object with the following 3 fields:</li> </ul> <p><strong>plant_ID:</strong><em> </em>plant identifier number ranging from between 1-35687</p> <p><strong>proba:</strong> species occurrence probability</p> <p><strong>cell:</strong><em> </em>raster grid cell number between 1-2251762</p> <p>This object can be used in combination with a raster layer to reconstruct the modelled distribution of each species or retrieve species richness and endemism.</p>
Native forest and proximity to humans are stronger drivers of Brazilian cottontail habitat use than invasive European hare
<p>Human activities and biological invasions have caused unprecedented biodiversity loss over the past 500 years. Proximity to humans drives the spatial distribution of species toward less disturbed habitats. Invasive species can competitively exclude native species, but species may coexist due to different habitat preferences. Here, we investigated how proximity to farms and the presence of the non-native European hare (<em>Lepus europaeus</em>) influence the habitat use by the Brazilian cottontail (<em>Sylvilagus minensis</em>) in southeastern Brazil. We found that the probability of cottontail site use increased with native forest cover and decreased with farmhouse proximity, ranging from 0.05 (<em>SE</em> = 0.02) at sites close to farmhouses (≅ 900 m) with no native forest to 0.70 (<em>SE</em> = 0.15) at sites far from farmhouses (≅ 2500 m) dominated by native forest. Higher risk of harassment and predation by free-roaming dogs and cats may explain the negative effect of farmhouse proximity on cottontail habitat use. We found little evidence for competitive exclusion by the European hare. Instead, our results suggest that the two species spatially segregate due to different habitat preferences. While the European hare more likely uses farmland in its native and non-native range, our results suggest that the Brazilian cottontail is a forest dweller. Although we found only weak evidence of competitive exclusion, we advise caution because invasive species may delay the onset of detrimental effects due to initial low population densities in newly invaded areas as is the case of the European hare in southeastern Brazil.</p>
Data from: Northern pikas experience reduced occupancy due to surrounding human land use despite the occurrence of suitable microclimates
<p>Aim: Despite warming temperatures, some species are found persisting at the trailing edge of their distribution. Microclimates provided by complex topography are considered a key factor in these cases of range stationarity, buffering stress from exposure to warming and enabling persistence. However, for species with trailing-edges located in human-modified landscapes, refugial conditions provided by microclimates could be disrupted by human activities. Here, we aimed to understand the determinants of trailing-edge occupancy for a small lagomorph found in rocky patches harboring cool microclimates.</p> <p>Location: Hokkaido Island, Japan</p> <p>Taxon: Northern pika (<em>Ochotona hyperborea</em>)</p> <p>Methods: We surveyed the occupancy of northern pikas across a wide elevational gradient (350–2200 m) for two consecutive summers. Ambient air and microhabitat (i.e., rock interstices) thermal conditions were measured to assess their relationship. We then analyzed their effects on occupancy at two nested spatial scales: (1) whole-distribution, and (2) at identified trailing-edge sites where we explored the effects of microclimates and surrounding human activities (i,e., distance to nearest road and area of human land use such as plantation forests or agricultural fields).</p> <p>Results: Overall, rock interstices exhibited cooler conditions than ambient air with temperature differences of 1–2 ºC. The overall distribution of northern pikas was affected by both mean ambient temperature and microhabitat availability, with warmer (lower elevation) sites with less microhabitats corresponding to the trailing edge of its distribution. Interestingly, trailing edge occupancy patterns were best explained by the negative effect of surrounding human land despite the existence of suitable microclimates in the rocky patches.</p> <p>Main conclusions: Our findings suggest that the local refugial conditions supported by cool microclimates are likely to be disrupted by the effects of human land at the larger landscape scale. This result highlights the importance of considering the effects of human activities and landscape alteration for effective microrefugia conservation. --</p>
Data from: Exploring the multi-level impacts of a youth-led comprehensive sexuality education model in Madagascar using human-centered design methods
<p>Comprehensive sexuality education (CSE) is recognized as a critical tool for addressing sexuality and reproductive health challenges among adolescents. However, little is known about the broader impacts of CSE on populations beyond adolescents, such as schools, families, and communities. This study explores multi-level impacts of an innovative CSE program in Madagascar, which employs young adult CSE educators to teach a three-year curriculum in government middle schools across the country. The two-phased study embraced a participatory approach and qualitative Human-centered Design (HCD) methods. In phase 1, 90 school principals and administrators representing 45 schools participated in HCD workshops, which were held in six regional cities. Phase 2 took place one year later, which included 50 principals from partner schools, and focused on expanding and validating findings from phase 1. From the perspective of school principals and administrators, the results indicate several areas in which CSE programming is having spill-over effects, beyond direct adolescent student sexuality knowledge and behaviors. In the case of this youth-led model in Madagascar, the program has impacted the lives of students (e.g., increased academic motivation and confidence), their parents (e.g., strengthened family relationships and increased parental involvement in schools), their<br>schools (e.g., increased perceived value of schools and teacher effectiveness), their communities (e.g., increased community connections), and impacted broader structural issues (e.g., improved equity and access to resources such as menstrual pads). While not all impacts of the CSE program were perceived as positive (e.g., students start experimenting with sex and love), the findings uncovered opportunities for targeting investments and refining CSE programming to maximize positive impacts at family, school, and community levels.</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.