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2,911 results for “dispersal”
Data from: Group size and dispersal ploys: An analysis of commuting behaviour of the pond bat (Myotis dasycneme)
<p>This study aimed to provide a description on how Pond bats (<em>Myotis dasycneme</em>) disperse, how to recognize a commuting route, and details about the effort needed to make a complete survey of one commuting route. The study area covered the provinces of Zuid-Holland, Overijssel, Friesland, Noord-Holland, and Utrecht. During 6 years of study between 2002 and 2009, researchers and bat volunteers studied pond bats along several waterways (all waterways wider than 10 m) between known roosts and their hunting areas. All the observations were made between April and September, starting 20 min before sunset. During the entire observation effort, the time (in hours and minutes) and direction of each bat was recorded. The time that each bat passed the observation location was later transformed to minutes after sunset. The number of animals on commuting route was related to the number of animals present in their respective roost.</p> <p> </p> <p>Data are organized in 3 files: <strong>commuting data 10 minutes.csv</strong>, <strong>commuting data.csv</strong> and <strong>observations waddinxveen.csv</strong>. The variables in these data files are explained here:</p> <p>Date: the observation date</p> <p>Location description: description of the location</p> <p>X Y: The coordinates of the location in RD. The RD (Rijks-Driehoek) system is the coordinate system used by the Dutch geographical service.</p> <p>Long Lat: The coordinates of the location in longitude and latitude.</p> <p>Distance over water: commuting distance over water. For each route, the distance (d) over water between roost and observation location was measured from a topographical map and expressed in kilometres.</p> <p>Moon cover: the amount of moon cover, expressed in percentages.</p> <p>Roost location: the assumed location of the roost of the bats passing on their commuting route</p> <p>Max N of bats in roost: the max number of bats observed emerging from a roost.</p> <p>Sum N of bats over 10-minute interval: the sum of all the observed bats passing in one direction within a 10-minute interval</p> <p>Time after sunset in 10 min: the begin time of each interval, measured in minutes after sunset</p> <p>Peak time after sunset: the time of the observed peak in numbers of bats, in minutes after sunset.</p> <p>Area: the municipality near the observation location.</p> <p>Total N of pond bats on route: the total number of pond bats observed on route, in the given observation time. Including foraging and returning bats.</p> <p>Total N of commuting pond bats: the total number of bats observed commuting (excluding all other behaviours).</p> <p>Time of first bat minutes after sunset: the time of the first bat, measured in minutes after sunset.</p> <p>Duration of commuting: the time in hours between the first and the last bat observed commuting.</p> <p>Observation time: the total duration (in minutes) of the observation period.</p> <p>Moon phases: a 1–3 scale, where c1 is the new moon, c2 is the first quarter, c3 half moon, c4 is the last quarter and c5 is the full moon.</p> <p>Cloud cover: estimation of the cover, using the following three categories: c1-0%–25% cover (clear night sky or some isolated clouds), c2-25%–75% cover (several scattered clouds but not covering more than 75% of the night sky), and c3- 75%–100% cover (scattered clouds covering more than 75% of the night sky to a completely overcast night sky</p> <p>Observation type: observation of either emerging bats from a roost (roost) or bats observed on commuting route (commuting).</p> <p> </p> <p>In addition, we also provide 2 pdf’s containing the observation protocols (in Dutch) for counting emerging bats (<strong>Handleiding tellen van een groep meervleermuizen.pdf</strong>) and bats along a commuting route (<strong>Handleiding vliegroute telling.pdf</strong>). The protocols are intended for professionals and citizen scientists.</p>
Dung removal and secondary seed dispersal data
<p>The datasets are described in the following data paper:<br> <br> Tanja Milotić, Christophe Baltzinger, Carsten Eichberg, Amy Eycott, Marco Heurich, Jörg Müller, Jorge Ari Noriega, Rosa Menendez, Jutta Stadler, Réka Ádám, Tessa Bahiga Bargmann, Isabelle Bilger, Jörn Buse, Joaquin Calatayud, Constantin Ciubuc, Gergely Boros, Marie Hauso, Pierre Jay-Robert, Märt Kruus, Enno Merivee, Geoffrey Miessen, Anne Must, Elham Omidzadeh Ardali, Elena Preda, Iraj Rahimi, Dirk Rohwedder, Eleanor M. Slade, László Somay, Pejman Tahmasebi, Stefano Ziani, Maurice Hoffmann (2018) Dung beetle assemblages and associated dung removal and secondary seed dispersal: data from a large-scaled multi-site experiment in the Western Palaearctic. Frontiers of Biogeography, Volume 10, Issue 1-2.</p>
Larval dispersal histogram data used for ATLAS deliverable D1.6: Biologically realistic Lagrangian dispersal and connectivity
<p>Larval dispersal histogram data for ATLAS deliverable D1.6 "Biologically realistic Lagrangian connectivity" (https://www.eu-atlas.org/resources/atlas-partners-document-area/atlas-deliverables/455-d1-6-biologically-realistic-lagrangian-connectivity/file). Tar archive files are ordered by ATLAS case study source region and with folders by larval behaviour type. The numbered behaviour types are described in deliverable D1.6. Each netcdf histogram file, e.g. hists_age_21.nc, contains the histogram for larvae of a single age in 5-day steps, from 00 (0 days) to 37 (185 days).</p> <p>Within each file histogram file, particle counts in each Viking20 model grid-cell are contained in a 4-d array with dimensions (launch month, lauch year, model gridsquare y index, model gridsquare x index). The Viking20 grid in the North Atlantic is the ORCA tripolar grid. Details of the model mesh are in the included file viking20_mesh_mask.tgz</p> <p>Histograms are in netcdf files:</p> <p>============================</p> <p>$ ncdump -h hists_age_00.nc<br> netcdf hists_age_00 {<br> dimensions:<br> coordinate = 4 ;<br> coordinate_1 = 50 ;<br> coordinate_2 = 1719 ;<br> coordinate_3 = 1784 ;<br> variables:<br> int64 coordinate(coordinate) ;<br> coordinate:units = "month" ;<br> coordinate:long_name = "Launch month" ;<br> int64 coordinate_1(coordinate_1) ;<br> coordinate_1:units = "year" ;<br> coordinate_1:long_name = "Launch year" ;<br> int64 coordinate_2(coordinate_2) ;<br> coordinate_2:units = "index" ;<br> coordinate_2:long_name = "J index" ;<br> int64 coordinate_3(coordinate_3) ;<br> coordinate_3:units = "index" ;<br> coordinate_3:long_name = "I index" ;<br> int64 data(coordinate, coordinate_1, coordinate_2, coordinate_3) ;<br> data :long_name = "particle count" ;</p> <p>// global attributes:<br> :Conventions = "CF-1.6" ;<br> }</p> <p>==========================================</p> <p> </p> <p> </p>
Data from: "Imprinted habitat selection varies across dispersal phases in a raptor species"
<p><span><span>Natal Habitat Preference Induction (NHPI) plays a significant role in shaping settlement decisions in dispersive animals. Despite its importance, limited research has explored how NHPI varies during natal dispersal phases and across different types of natal habitats. In this study, we examined NHPI in 77 GPS-tagged juvenile red kites <em>(Milvus milvus</em>) originating from different natal habitats along an elevational gradient in Switzerland. We applied individual-based step selection analysis to investigate habitat selection from independence to settlement. We found that during the prospecting phase, individuals predominantly selected habitats similar to their natal environments. However, this pattern changed in the settlement phase: individuals fledged from habitats at higher elevations or closer to urban areas mostly avoided similar habitats (negative NHPI), while those from areas with more farmlands or pastures (combined with forests) showed a preference for similar habitats (positive NHPI). Moreover, the magnitude and individual variation in NHPI differed depending on the natal habitat types from which individuals originated. These findings highlight that strength, direction, and individual variation in NHPI differ between natal habitat types and dispersal phases. Natal habitats therefore can have pervasive legacy effects on subsequent habitat selection, likely affecting population and range dynamics.</span></span></p>
Resolution Enhancement of UWB Time-Reversal Microwave Imaging in Dispersive Environments (dataset)
<p>These files are the simulation data used to create the figures illustrated in the journal paper with the same title which has been accepted for publication as a regular paper in IEEE Transactions on Computational Imaging. Each filename indicates the figure number associated with the file. These files are text files. The column structure of each file is described in the README file.</p>
Supporting data for "Dispersive sensing of charge states in a bilayer graphene quantum dot"
<p>Supporting data and analysis scripts for all figures in the article "Dispersive sensing of charge states in a bilayer graphene quantum dot", Appl. Phys. Lett. <strong>118</strong>, 093104 (2021); <a href="https://doi.org/10.1063/5.0040234">https://doi.org/10.1063/5.0040234</a></p> <p>The files are sorted according to the figures/panels in the publication with a "0-README.txt" file including further information. </p> <p>The following versions of Pyhton and the packages have been used:<br> python: 3.6.10<br> numpy: 1.18.1<br> matplotlib: 3.1.3<br> scipy: 1.4.1</p>
Dispersal of alien species in relation to the historic development of hydropower generation and navigation
<p>Dataset on dispersal of alien species in relation to the historic development of hydropower generation and Navigation along the River Danube.</p>
Micheluz et al energy dispersive X-ray-spectroscopy data
<p><strong># Micheluz et al energy dispersive X-ray-spectroscopy data</strong></p> <p><strong>## paper: https://doi.org/10.3390/pathogens11121462</strong></p> <p><strong>### Dataset: </strong></p> <p>Dataset1_Micheluz-et-al.csv</p> <p>This is a CSV file with 206 lines and 12 columns.</p> <p>Data are energy-dispersive X-ray spectroscopy data as weight%</p> <p>Explanation of the heading: Site, the Italian city where the samples of Eurotium halophilicum were collected;</p> <p>Structure, the features analysed (EPS, conidia, background); presence of crystal (TRUE/FALSE) indicates if in the areas/samples were detected biogenic crystals;</p> <p>C, carbon; O, oxygen; Na, sodium; P, phosphorus; S, sulphur; Cl, chlorine, K, potassium; Ca, calcium; Au, gold; Total, the sum of all the elements.</p> <p> </p> <p>Dataset1_Micheluz-et-al.csv</p> <p>This is a CSV file with 24 lines and 8 columns.</p> <p>Data are energy-dispersive X-ray spectroscopy data as atomic%</p> <p>Explanation of the heading: ID, is the biogenic crystal analysed; </p> <p>C, carbon; O, oxygen; Na, sodium; S, sulphur; Cl, chlorine, Ca, calcium; Total, the sum of all the elements.</p> <p><strong>### Sampling</strong></p> <p>The mycelium samples analysed with Energy-dispersive X-ray spectroscopy were obtained by pressing a carbon-based, impurity-free adhesive tape (FungiTapeTM, Scientific Device Lab., Inc Glenview, IL, USA) onto the fungal colonies found on the spines of books in five Italian libraries in Turin, Venice, Genova and Rome (2 libraries in Rome).</p> <p><strong>### Methods</strong></p> <p>Energy-dispersive X-ray spectroscopy was performed with an INCA Oxford 250 system, maintaining the electron beam at 20 keV, with a mean working distance to the sample of 12.5 mm. The electron beam could be focused on very small areas, in the order of nm2, allowing a surface resolution that readily resolves objects that are a few tens of nm in dimension. This way, a database was obtained with repeated observations of the composition of conidia and other fungus structures carried out on samples from the covers of different books. Some samples were analysed with energy-dispersive X-ray spectroscopy also after metallisation in order to be able to focus on peculiar structures like the (apparently biogenic) crystals. When this was the case, the spectra obtained contained gold, also present in the background.</p> <p>The calibration of the apparatus was based on the standards CaCO3, SiO2, albite, MgO, Al2O3, GaP, FeS2, wollastonite, feldspar MAD-10, Ti and Fe, supplied by Agar Scientific Ltd. (Stansted, UK) and the conventional ZAF correction (atomic number Z, absorption A, fluorescence F) from the Oxford INCA 250 software was applied to the measurements to convert apparent concentrations (raw peak intensity) into (semi-quantitative) concentrations corrected for inter-element matrix effects.</p> <p><strong>### Labels Used</strong></p> <p>Conidia = part of the fungal mycelium analysed</p> <p>EPS = Extracellular polymeric material present in the mycelium</p> <p>Background = the adhesive tape (made of carbon) used to collect the mycelium and prepare the samples for observation with scanning electron microscopy</p>
IMMERSE Horizon 2020 Project Downstream User Toolbox – data for tutorial on impact of wave coupling on surface particle dispersion simulations
<p>Exemplary data for tutorial on impact of wave coupling on surface particle dispersal simulations<br> <a href="https://github.com/immerse-project/Downstream-Users-Toolbox/tree/main/T8.3_WaveCoupling_ParticleTransport_UniU">https://github.com/immerse-project/Downstream-Users-Toolbox/tree/main/T8.3_WaveCoupling_ParticleTransport_UniU</a><br> created as part of the downstream user toolbox of the IMMERSE Horizon 2020 project (<a href="https://immerse-ocean.eu/">https://immerse-ocean.eu/</a>).</p> <p>In the tutorial the impact of new options for the representation of wave-current interactions in the NEMO ocean model (<a href="https://www.nemo-ocean.eu/">https://www.nemo-ocean.eu/</a>) on surface particle simulations are tested in a case study for the Mediterranean Sea. The tutorial consists of two jupyter notebooks: Parcels_CalcTraj.ipynb and CompTraj_uncoupledVScoupled.ipynb. Parcels_CalcTraj.ipynb calculates Lagrangian particle trajectories based on velocity output from ocean only as well as coupled ocean-wave model simulation by making use of the OceanParcels software (<a href="https://oceanparcels.org/">https://oceanparcels.org/</a>). CompTraj_uncoupledVScoupled.ipynb compares dispersal statistics of Lagrangian particle trajectories calculated from ocean-only vs coupled ocean-wave model simulations.</p> <p>This repository contains the surface velocity and ocean model grid data needed to run Parcels_CalcTraj.ipynb, as well as the trajectory data produced by Parcels_CalcTraj.ipynb, which is needed to run CompTraj_uncoupledVScoupled.ipynb. The surface velocity data stems from two simulations with a regional high-resolution (1/24° horizontal resolution) model configuration for the Mediterranean Sea: a coupled ocean-wave model simulation and a complimentary ocean-only simulation. These model simulations make use of the NEMO v4.2-RC ocean model, the Wave Watch 3 v.6.07 wave model, the OASIS3-MCT coupler, and ECMWF atmospheric fields; they are described in detail in IMMERSE deliverable D5.7 “Assessment of wave-current effects on the circulation in theMed-MFC system”<strong>.</strong></p>
Datasets used for the manuscript: "Sibling competition, dispersal and fitness outcomes in humans"
<p>Datasets used for the manuscript: “Sibling competition, dispersal and fitness outcomes in humans”, 10.1038/s41598-023-33700-3</p>
Morphological cladogenesis and terminal dwarfing in extinct Late Miocene through Pliocene menardiform globorotalids: New complementary data to «Evolutionary prospection in the Neogene planktic foraminifer Globorotalia menardii and related forms from ODP Hole 925B (Céara Rise, western tropical Atlantic): evidence for gradual evolution superimposed by long distance dispersal ?, Swiss J. Palaeontology, 135:205-248»
<p>A complementary morphometric data set is provided to the study of Knappertsbusch (2016) about the shell evolution of menardiform globorotalids (Neogene planktic foraminifera) at ODP Hole 925B from Céara Rise in the the western tropical Atlantic. The new measurements confirm splitting of extinct <em>Globorotalia multicamerata</em> from the <em>G. menardii</em> stock via the intermediate form <em>G. limbata</em> between about 6 Ma to 5 Ma ago. After splitting both <em>G. limbata</em> and <em>G. multicamerata</em> show gradual divergence from <em>G. menardii</em> in several shell parameters illustrating morphological cladogenesis. Between 2.88 Ma and 2.59 Ma the same parameters show a concerted trend towards reduced values indicating pre-extinction dwarfing. A comparison with published literature data of Delta<sup>18</sup>O trends between species, that populated the mixed layer (<em>Globigerinoides sacculifer</em>) and the thermocline layer (<em>Neogloboquadrina dutertrei</em>) at this location during those times suggests, that both divergence and subsequent dwarfing trends were probably the results of changes in upper watermass stratification.</p> <p>The complementary data set is provided in six zipped archives APPENDIX A, B, C, D, E and F (zipped with free software 7-Zip 22.00 (x64), 2022-06-15 from 1999-2022 Igor Pawlow), together with a description of the data in file Report_925B_suppl_1.pdf.</p>
Spin wave dispersion of ultra-low damping hematite (α-Fe2O3) at GHz frequencies
<p>Raw data associated to the manuscript ‘’Spin wave dispersion of ultra-low damping hematite (α-Fe<sub>2</sub>O<sub>3</sub>) at GHz frequencies‘’,</p> <p>Physical Review Materials 7, 054407(2023); doi: 10.1103/PhysRevMaterials.7.054407<br> Information about file formats and measurement parameters are described in text files in the specific folders.</p> <p>Paper abstract:<br> Low magnetic damping and high group velocity of spin waves (SWs) or magnons are two crucial parameters for functional magnonic devices. Magnonics research on signal processing and wave-based computation at GHz frequencies focused on the artificial ferrimagnetic garnet Y<sub>3</sub>Fe<sub>5</sub>O<sub>12</sub> (YIG) so far. We report on spin-wave spectroscopy studies performed on the natural mineral hematite (α-Fe<sub>2</sub>O<sub>3</sub>) which is a canted antiferromagnet. By means of broadband GHz spectroscopy and inelastic light scattering, we determine a damping coefficient of 1.1×10<sup>−5</sup> and magnon group velocities of a few 10 km/s, respectively, at room temperature. Covering a large regime of wave vectors up to k≈24 rad/μm, we find the exchange stiffness length to be relatively short and only about 1 Å. In a small magnetic field of 30 mT, the decay length of SWs is estimated to be 1.1 cm similar to the best YIG. Still, inelastic light scattering provides surprisingly broad and partly asymmetric resonance peaks. Their characteristic shape is induced by the large group velocities, low damping and distribution of incident angles inside the laser beam. Our results promote hematite as an alternative and sustainable basis for magnonic devices with fast speeds and low losses based on a stable natural mineral.</p>
Seed dispersal data for Warneke et al "Habitat fragmentation alters the distance of abiotic seed dispersal through edge effects and direction of dispersal"
This csv file contains seed dispersal data for five species (Carphephorus bellidifolius, Aristida beyrichiana, Liatris squarrulosa, Sorghastrum secundum, and Anthenantia villosa). Data were collected at the Savannah River Site, near Aiken, South Carolina, United States. Data were collected between November 17, 2009, to January 22, 2010 and were collected using the methods outlined in this document.
Nest-mediated seed dispersal study from mixed habitats in North Georgia and Western North Carolina
Many plant seeds travel on the wind and through animal ingestion or adhesion; however, an overlooked dispersal mode may lurk within those dispersal modes. Viable seeds may remain attached or embedded within materials birds gather for nest building. Our objective was to determine if birds inadvertently transport seeds when they forage for plant materials to build, insulate, and line nests. We also hypothesized that nest-mediated dispersal might be particularly useful for plants that use mating systems with self-fertilized seeds embedded in their stems. We gathered bird nests in temperate forests and fields in eastern North America and germinated the plant material. We also employed experimental nest boxes and performed nest dissections to rule out airborne and fecal contamination. We found that birds collect plant stem material and mud for nest construction and inadvertently transport the seeds contained within. Experimental nest boxes indicated that bird nests were not passive recipients of seeds (e.g., carried on wind), but arrived in the materials used to construct nests. We germinated 144 plant species from the nests of 23 bird species. A large proportion of the nest germinants were graminoids containing self-fertilized seeds inside stems—suggesting that nest dispersal may be an adaptive benefit of closed mating systems. Avian nest building appears as a dispersal pathway for hundreds of plant species, including many non-native species, at distances of at least 100–200 m. We propose a new plant dispersal guild to describe this phenomenon, caliochory (calio = Greek for nest).
Annual and monthly time series of estimated kelp spore dispersal times among ROMS cells in southern California, 1996 – 2006
These data describe the estimated dispersal duration of spores of giant kelp, Macrocystis pyrifera, among connectivity cells in a high-resolution, three-dimensional, spatiotemporally-explicit ocean circulation model (Regional Oceanic Modeling System, ROMS) in southern California, USA, for an 11-year period from the beginning of 1996 to the end of 2006. Asymmetrical and dynamic estimates of giant kelp spore dispersal durations connecting source and destination ROMS cells were estimated on monthly and annual timescales using minimum mean transit times.
Simulation data and scripts for CFD-DEM simulation of saturated bi-disperse granular flows
<ul> <li>Data set 1 - contains the raw data required to replicate and validate all plots in the main article. </li> <li>Sample case - a .zip file which includes codes which are needed to simulate a CFD-DEM case of a steady granular flow in water with cyclic boundaries in the stream wise direction. Also enclosed is a ReadMe.txt file detailing the implementation instructions for both Esys particle and OpenFOAM codes. Download links for Esys particle and OpenFOAM are also included</li> <li>Geo file generator - a .zip file which includes Esys particle codes that can be used to generate a .geo file specifying the initial position of the particles used in the test simulations. A ReadMe.txt file is enclosed with more detailed implementation instructions.</li> </ul>
Fig. 29 in Systematics of the enigmatic South American Streblopus Van Lansberge, 1874 dung beetles and their transatlantic origin: a case study on the role of dispersal events in the biogeographical history of the Scarabaeinae (Coleoptera: Scarabaeidae)
Fig. 29. Current distribution of Streblopus van Lansberge, 1874 and the Old World groups with which it is believed to be more closely related plotted on an Upper Cretaceous palaeomap (~ 80 million years ago). Based particularly on the hypothesis in Tarasov & Génier (2015) that Streblopus is part of a clade otherwise composed uniquely of dung beetle lineages either exclusively distributed in Africa (Circellium, Chalconotus and Gyronotus) or with a distribution largely centred on that continent (Scarabaeini), and on the dating of the origin of the Scarabaeini as 71 million years ago (Gunter et al. 2016), we propose that the lineage that would eventually lead to Streblopus branched off from those groups in Africa some time between 95 and 71 million years ago, and that one of its descendent lineages (the only one living today) dispersed from its original continent to South America during the late Upper Cretaceous or the early Cenozoic. Since Africa and South America have not been connected by land since the Lower Cretaceous, the only way the ancestor of Streblopus could have reached South America was through transoceanic dispersal across the early South Atlantic. That dispersal probably happened by rafting on floating pieces of plants or other debris, as probably occurred with a large number of other organisms. Palaeomap modified from Scotese (2016); distribution area based on Balthasar (1963), Scholtz & Howden (1987), Davis et al. (2008) and our own results.
Fig. 14. Profemora. A‒B. Streblopus opatroides van Lansberge, 1874. A in Systematics of the enigmatic South American Streblopus Van Lansberge, 1874 dung beetles and their transatlantic origin: a case study on the role of dispersal events in the biogeographical history of the Scarabaeinae (Coleoptera: Scarabaeidae)
Fig. 14. Profemora. A‒B. Streblopus opatroides van Lansberge, 1874. A. ♂. B. ♀. C‒D. S. punctatus (Balthasar, 1938). C. ♂. D. ♀. Note the differences between the species and sexes in relation to the overall shape of the profemora and the presence of spurs on the anterior edge in males.
Fig. 12. Pronotum. A. Streblopus opatroides van Lansberge, 1874. B. S in Systematics of the enigmatic South American Streblopus Van Lansberge, 1874 dung beetles and their transatlantic origin: a case study on the role of dispersal events in the biogeographical history of the Scarabaeinae (Coleoptera: Scarabaeidae)
Fig. 12. Pronotum. A. Streblopus opatroides van Lansberge, 1874. B. S. punctatus (Balthasar, 1938). Note the differences in the umbilicate punctation and colour between the species.
Fig. 1. Streblopus opatroides van Lansberge, 1874. A‒B. Ordinary specimens, dorsal view. A in Systematics of the enigmatic South American Streblopus Van Lansberge, 1874 dung beetles and their transatlantic origin: a case study on the role of dispersal events in the biogeographical history of the Scarabaeinae (Coleoptera: Scarabaeidae)
Fig. 1. Streblopus opatroides van Lansberge, 1874. A‒B. Ordinary specimens, dorsal view. A. ♂. B. ♀. C‒D. Lectotype, ♂. C. Dorsal view. D. Attached labels.
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.