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638 results for “oscillations”
Raw data for the article: A Cryptochrome adopts distinct moon- and sunlight states and functions as sun- versus moonlight interpreter in monthly oscillator entrainment
<p>The moon's monthly cycle synchronizes reproduction in countless marine organisms. The mass-spawning bristle worm Platynereis dumerilii uses an endogenous monthly oscillator to phase reproduction to specific days. Classical work showed that this oscillator is set by full moon. But how do organisms recognize such a specific moon phase? We uncover that the light receptor L-Cryptochrome (L-Cry) is able to discriminate between different moonlight durations, as well as between sun- and moonlight. Consistent with L-Cry's function as light valence interpreter, its genetic loss leads to a faster re-entrainment under artificially strong nocturnal light. This suggests that L-Cry blocks "wrong" light from impacting on the monthly oscillator. A biochemical characterization of purified L-Cry protein, exposed to naturalistic sun- or moonlight, reveals the formation of distinct sun- and moonlight states characterized by different photoreduction- and recovery kinetics of L-Cry's co-factor Flavin Adenine Dinucleotide. In vivo, L-Cry's sun- versus moonlight states correlate with distinct sub-cellular localizations, indicating different signalling. In contrast, r-Opsin1, the most abundant ocular opsin, is not required for monthly oscillator entrainment. Our work reveals a new concept for correct moonlight interpretation involving a "valence interpreter" that provides entraining photoreceptor(s) with light source and moon phase information. These findings advance our mechanistic understanding of a fundamental biological phenomenon: moon-controlled monthly timing. Such level of understanding is also an essential prerequisite to tackle anthropogenic threats on marine ecology.</p>
Active Power Control from Wind Farms for Damping Very Low-Frequency Oscillations
<p>Dataset used for results in paper "Active Power Control from Wind Farms for Damping Very Low-Frequency Oscillations"</p>
Data from: Manipulation of Miniature and Microminiature Bodies on a Harmonically Oscillating Platform by Controlling Dry Friction
<p>Data from the paper "Manipulation of Miniature and Microminiature Bodies on a Harmonically Oscillating Platform by Controlling Dry Friction" <a href="https://doi.org/10.3390/mi12091087">https://doi.org/10.3390/mi12091087</a></p> <p>Currently used nonprehensile manipulation systems that are based on vibrational techniques employ temporal (vibrational) asymmetry, spatial asymmetry, or force asymmetry to provide and control a directional motion of a body. This paper presents a novel method of nonprehensile manipulation of miniature and microminiature bodies on a harmonically oscillating platform by creating a frictional asymmetry through dynamic dry friction control. To theoretically verify the feasibility of the method and to determine the control parameters that define the motion characteristics, a mathematical model was developed, and modeling was carried out. Experimental setups for miniature and microminiature bodies were developed for nonprehensile manipulation by dry friction control, and manipulation experiments were carried out to experimentally verify the feasibility of the proposed method and theoretical findings. By revealing how characteristic control parameters influence the direction and velocity, the modeling results theoretically verified the feasibility of the proposed method. The experimental investigation verified that the proposed method is technically feasible and can be applied in practice, as well as confirmed the theoretical findings that the velocity and direction of the body can be controlled by changing the parameters of the function for dynamic dry friction control. The presented research enriches the classical theories of manipulation methods on vibrating plates and platforms, as well as the presented results, are relevant for industries dealing with feeding, assembling, or manipulation of miniature and microminiature bodies.</p>
Model data for "Surface heating over the Tibetan Plateau associated with the Antarctic Oscillation"
<p>In HYSPLIT.rar, the ????06.backjectory.10day.sh.p.pnum.nc data are the hysplit results.</p> <p>In CESM.rar, the pres_f.inc6hr.????.cam.h0.????-05_06.nc and pres_f.ins6hr.????.cam.h0.????-05_06.nc are the CTL and EXP experiment results of AGCM.</p> <p>resp_Amundv7.t42l20.nc is the response of the LBM model.</p> <p>Detailed description is shown in the paper "Surface heating over the Tibetan Plateau associated with the Antarctic Oscillation". </p>
Brain waves would include equipotential fluctuations in addition to oscillations as sine waves
<p>Raw 1200 LFP data sets of 60s are in /60s_125(250,500,1000)Hz_20h/12XX/eeg1_t0(1-1199) .txt. Results of tau and burst, whose state is identified by existing method (0:awake, 1:NREM, 2:REM), are in /60s_125-1000Hz_20h/12XX_m2 or S1/tau-burst_m2(s1)_thX.XXX.txt. th=threshold. Column 1:trial No., 2:state, 3:Ntau, 4:Mtau, 5:ratio of total tau, 6:number of burst, 7:mean burst, 8:Abst. Those identified by Ntau method are in /60s_125-1000Hz_20h/4state (mean per state), 4state_m2, or 4states _s1/12XX/tauburst-m2_4state_thx.XXX.txt.The state is listed in third column as 2:awake, 10:REM, 20:NREM, 30:light sleep. Data of SEF95 are in /60s_sef_4state/12XX_SEF4state_125(250,500,1000) Hz.txt.</p> <p>Raw EEG data sets of 64s are in /dogEEG/older(younger)_sev/20150XXX/50Hz_nonMovAve/20150XXX_sevX.X_int0(1,2)_cts2.txt. Results of tau and burst are contained in /dogEEG/older(younger)_sev/20150XXX/sratio_peak/non-movave/20150XXX_sratio_peak_tau-burst_thXX.XX.txt. Column 1:sevoflurane concentration, 2:int, 3:Ntau, 4:Mtau, 5:ratio of total tau, 6:number of burst, 7:mean burst, 8:Abst. Results of SEF95 are in /dogEEG/older(younger)_sev/20150XXX/50Hz_nonMovAve/20150XXX_sef95.txt. Data of maximum Ntau, minimum Abst, or Mtau=2.3, 2.5 sample interval are in /dogEEG/THnt_250Hz.</p>
Data for: First Successful Hindcasts of the 2016 Disruption of the Stratospheric Quasibiennial Oscillation
<p>These data were used for making plots in the article entitled "First Successful Hindcasts of the 2016 Disruption of the Stratospheric Quasibiennial Oscillation". Data format is NetCDF3.</p>
Observations of a PT-like phase transition and limit cycle oscillations in non-reciprocally coupled optomechanical oscillators levitated in vacuum
<p>Trajectories of optically levitated particles in vacuum. Trajectories are recorded using quadrant photodiode and ultra-fast CMOS camera. The readme file with more detailed description is added.</p>
The Aliased Complex Oscillator as a Paradigm for Analog Physical Modeling Sound Synthesis --- Audio Samples
<p>Additional material to the paper with the title: "The Aliased Complex Oscillator as a Paradigm for Analog Physical Modeling Sound Synthesis"</p>
2D Array of Pulse Coupled Oscillators Driving Cilia to Demonstrate Metachronal Waves
<p>The video demonstrates metachornal waves from an 2D array of delay locked pulse coupled oscillators, each mapping to a cilia.<br>Within the triangle structure, the oscillators are coupled to their nearest neighbors.</p>
High-power in-phase and anti-phase mode emission from linear arrays of resonant-tunneling-diode oscillators in the 0.4-to-0.8-THz frequency range - data
<p>Experimental and simulation data from the paper "High-power in-phase and anti-phase mode emission from linear arrays of resonant-tunneling-diode oscillators in the 0.4-to-0.8-THz frequency range".</p>
The mechanisms in regulating the quasi-biennial oscillation in E3SM version 2
<p>The data includes time step output of convective parameters horizonal wind in heating depth (U), the depth of the heating (D) and the maximum latent heating tendency within convection (Q0max) on the spectral element grid. Also, it includes zonal wind,total precipitation and zonal wind tendency caused by gravity wave (BUTGW) at longitude-latitude grid at 45.7 hPa and 96 hPa. The time series of EP flux divergence, gravity wave drag and zonal mean zonal wind are restored.</p>
Coupling and de-coupling of the El Niño Southern Oscillation to the supply of larval fishes to benthic populations in the Hawaiian Islands
<p>Several recent high intensity ENSO events have caused strong negative impacts on the adult phases of foundational species in coral reef ecosystems, but comparatively little is known about how climatic variables related to recent ENSOs are impacting the supply of larvae to benthic populations. In marine fishes and invertebrates, reproductive adults and planktonic larvae are generally more sensitive to environmental variability than older, non-reproductive adults. Further, the transport of larvae in ocean currents may also be strongly ENSO dependent. The interactions between the dynamics of larval survivorship and larval transport could lead to population bottlenecks as stronger ENSO events become more common. We tested the predictions of this hypothesis around the Main Hawaiian Islands (MHI) by constructing a correlation matrix of physical and biological time series variables that spanned 11 years (2007 – 2017) and multiple ENSO events. Our correlation matrix included four types of variables: i. published ENSO indices, ii. satellite-derived sea surface temperature (SST) and chlorophyll variables, iii. abundance and diversity of larval fishes sampled during the late winter spawning season off Oahu, and iv. abundance and diversity of coral reef fish recruits sampled on the western shore of the Big Island of Hawaii. We found that the abundance and diversity of larval fishes was negatively correlated with the Multivariate El Niño Index (MEI), and that larval variables were positively correlated with measures of fall recruitment (September & November), but not correlated with spring-summer recruitment (May & July). In the MHI, SST variables were not correlated with the MEI, but two successive El Niño events of 2014-15 and 2015-2016 were characterized by SST maxima approaching 30 °C. Two large pulses of benthic recruitment occurred in the 2009 and 2014 recruitment seasons, with > 8000 recruits observed by divers over the summer and fall months. Both events were characterized by either neutral or negative MEI indices measured during the preceding winter months. These patterns suggest that La Niña and the neutral phases of the ENSO cycle are generally favorable for adult reproduction and larval development in the spring and summer, while El Niño phases may limit recruitment in the late summer and fall. We hypothesize that episodic recruitment during non-El Niño phases is related to favorable survivorship and transport dynamics that are associated with the formation of pairs of anticyclonic and cyclonic eddies on the leeward sides (western shores) of the Main Hawaiian Islands.</p>
The unsteady shock boundary layer interaction in a compressor cascade - Part 3: Mechanisms of shock oscillation - Promotional video 2
<p>Second promotional video with animation of mechanisms of shock oscillation for the ASME Turbo Expo 2024 open access publication with identifier GT2024-128197 and title "The unsteady shock boundary layer interaction in a compressor cascade - Part 3: Mechanisms of shock oscillation."</p>
Atlantic Ocean marlin fishery and climatic oscillations dataset
<p>Climatic oscillations affect fish population dynamics, ecological processes, and fishing operations in maritime habitats. This study examined how climatic oscillations affect catch rates for striped, blue, and silver marlins in the Atlantic Ocean. These oscillations are regarded as the primary factor influencing the abundance and accessibility of specific resources utilized by fishers. Logbook data were obtained from Taiwanese large-scale fishing vessels for climatic oscillations during the period 2005–2016. The results indicated that the effect of the Subtropical Indian Ocean Dipole on marlin catch rates did not have a lag, whereas those of the North Atlantic Oscillation, Atlantic Multidecadal Oscillation, Pacific Decadal Oscillation, and Indian Ocean Dipole had various lags. Pearson's correlation analysis was conducted to examine the correlations between atmospheric oscillation indices and marlin catch rates, and wavelet analysis was employed to describe the influences of the most relevant lags. The results indicated that annual atmospheric fluctuations and their lags affected the abundance and catchability of striped, blue, and silver marlins in the study region. This, in turn, may affect the presence of these species in the market and lead to fluctuations in their prices in accordance with supply and demand. Overall, understanding the effects of climatic oscillations on fish species are essential for policymakers and coastal communities seeking to manage marine resources, predict changes in marine ecosystems, and establish appropriate methods for controlling the effects of climate variability.</p>
Data Release for "First joint oscillation analysis of Super-Kamiokande atmospheric and T2K accelerator neutrino data"
<p>This archive contains the electronic version in ROOT and pdf formats of the measurements of oscillation parameters obtained with the analyses from the paper “First joint oscillation analysis of Super-Kamiokande atmospheric and T2K accelerator neutrino data”.<br><br>It is published in <a href="https://doi.org/10.1103/PhysRevLett.134.011801">Physical Review Letters</a> and is available on the <a href="https://arxiv.org/abs/2405.12488">arXiv:2405.12488 [hep-ex]</a>. </p> <p>**************************************<br>***** Results included in this release<br>**************************************<br>This release includes the results of the measurements of the different oscillation parameters obtained with the four analyses appearing in the paper. This corresponds to various 1D and 2D DeltaChi^2 and posterior probability maps as well as 2D confidence/credible regions for the parameters sin^2(theta13), sin^2(theta23), dm^2_32/|dm^2_31|, delta_cp, J_cp.</p> <p>The results are separated into different files for the four analyses. Additional details on these analyses can be found below, but two of them use a Bayesian approach (producing posterior probabilities and credible intervals/regions) and two of them follow a frequentist approach (producing DeltaChi^2 maps and confidence intervals/regions). A tag in the TGraph and histogram names also allow to differentiate the different types of intervals/regions: "cred" for credible interval from the Bayesian analysis, "conf" for confidence interval from the frequentist analysis. The tag “posterior” indicates that the object corresponds to a posterior probability distribution, while “chi2” indicates a DeltaChi^2 one.</p> <p>Results for each mass ordering hypothesis are provided, denoted "NO" for normal ordering and "IO" for inverted ordering. The Bayesian files also include results marginalised over the mass ordering, denoted by the tag "both" in the object names. The frequentist files include results profiled over the mass ordering, indicated by a tag “profMO” in the object names.<br>The Bayesian and frequentist results use different conventions for the mass splitting in the inverted ordering: the Bayesian results are in term of #Deltam^{2}_{32} for both NO and IO, whereas the frequentist results are plotted versus #Deltam^{2}_{32} for the NO, and |#Deltam^{2}_{31}| for the IO. </p> <p>A constraint on theta13 from reactor experiment measurements is used for all results in this release. It corresponds to the value in the PDG 2019 review: sin^2(2theta_13)=(8.53+-0.27) x 10^{-2}. This is commonly referred to as "the reactor constraint", and a tag “wRC” is included in the name of the different objects as a reminder that it is used for these results.</p> <p>**************************************<br>***** Brief descriptions of the four analyses<br>**************************************<br>Results are provided for the four analyses mentioned in the “Oscillation analysis” part of the paper. They were given names (Bayesian1, Bayesian2, Frequentist1, Frequentist2) based on the statistical approach they follow.</p> <p>The Bayesian analyses are based on the two T2K analyses described in Eur. Phys. J. C 83, 782 (2023), extended to include the Super-Kamiokande atmospheric data, and with modifications to use the model described in the paper to which the present release is attached to. These analyses use Markov Chain Monte Carlo methods to compute marginal likelihoods for the parameter of interests. </p> <p>For the frequentist analyses, Frequentist1 is a modified version of Bayesian1, optimized for speed to be able to address the computational challenges of producing frequentist results from an ensemble of pseudo-experiments. Frequentist2 is based on the Super-Kamiokande atmospheric analysis described in PTEP 2019, 053F01 (2019), extended to include the T2K data, and also with modifications to follow the model described in the paper. These two analyses compute profile likelihood on a grid of oscillation parameters of interest to produce measurements of these parameters.</p> <p>In terms of the differences between analyses mentioned in the paper, Bayesian2 is the analysis that does a simultaneous fit of the T2K near detector data with the events observed at SK, and the one for which the momentum scale uncertainty is not correlated between the atmospheric and T2K events observed at SK. The three other analyses use a covariance matrix to propagate the constraint on systematic uncertainties from T2K near detector data to the analysis of the events observed at SK, and treat the momentum scale uncertainty as correlated between atmospheric and T2K far detector events.</p> <p>**************************************<br>***** Example codes<br>**************************************<br>Example codes are provided for each of the four analyses, showing how to produce the pdf file from this analysis from the corresponding ROOT file. How to run these example codes is indicated in the comments at the start of each of the example files.</p> <p>**************************************<br>***** Objects inside the ROOT files<br>**************************************<br>The ROOT objects contained inside the files are named first with an identifier of which parameter(s) are being shown, followed by the reactor constraint tag, followed by the mass ordering tag.</p> <p>For the Bayesian results, there is an additional tag to indicate if the results was obtained with a prior probability uniform in deltaCP (“flatdcp”) or uniform in sin(deltaCP) (“flatsindcp”)</p> <p>A glossary is provided at the end of this readme.</p> <p>**************************************<br>*** 2D regions<br>**************************************<br>Objects of the form:<br>gr2D_varX_varY_wRC_<NO,IO,both>_<conf,cred><68,90,955,997>(_N)<br>are TGraphs corresponding to the 2D confidence ("conf") or credible ("cred") regions for the 2 variables (varX, varY). <br>N is the iterator for different TGraphs corresponding to the same region; these occur when confidence regions are discontinuous (for example when deltaCP loops over from +pi to -pi).</p> <p>68, 90, 955, 997 are the percentage credible/confidence levels.</p> <p>Most of the 2D frequentist regions were computed using the standard DeltaChi^2 values (from the Gaussian case), and therefore have only approximate coverage. However, the {sin^2(theta_23), deltaCP} confidence regions of analysis Frequentist1 were built using critical DeltaChi^2 values computed with the Feldman-Cousins method. To distinguish them from other confidence regions, a tag "FC" is included in the name of the corresponding TGraph.</p> <p>The best fit markers are also provided for the 2D results:<br>gr2D_varX_varY_wRC_<NO,IO,both>_bestfit</p> <p>The best fit markers and contour lines are generally for each MO *separately*, i.e. assuming DeltaChi^2 is 0 at the minimum or that the total posterior probability integrates to 1 in the mass ordering considered. There are some exceptions, in particular some 2D regions for (sin^2(theta_23), dcp) are also provided using a best fit over both MO to allow for comparisons with other experiments using this convention. This special set of contours has an extra tag "globalMO" in its name to distinguish it from the others.</p> <p><br>**************************************<br>*** 1D and 2D histograms<br>**************************************<br>Objects of the form<br>h1D_var_<chi2,posterior>_wRC,_<NO,IO, both, profMO><br>h2D_var1_var2_<chi2,posterior>_wRC_<NO,IO, both><br>are respectively TH1D of the DeltaChi^2 ("chi2") or posterior probability ("posterior") for oscillation parameter "var" or TH2D for the couple of parameters (var1, var2)</p> <p>The Bayesian and frequentist results use different conventions with respect to the mass ordering:<br>- DeltaChi^2 plots use a global minimum over both hierarchies<br>- Posterior probability plots integrate to unity *individually*</p> <p>**************************************<br>***** Critical values for frequentist results<br>**************************************<br>For the 1D plots, critical delta chi2 values obtained with the Feldman-Cousins method are provided for theta23 and deltaCP <br>grCritical_{variable}_chi2_wRC_{NO,IO,profMO}_conf{68, 90, 955}<br>variable: th23, dCP</p> <p>The FC-corrected confidence intervals for these 2 variables can be obtained as the region for which the corresponding 1D DeltaChi^2 histogram is below the grCritical graph of a given level.</p> <p>**************************************<br>***** Additional notes for Bayesian results<br>**************************************<br>For plots involving the mass splitting, the mass ordering is given by the sign:<br> dm32>0 is normal hierarchy (Delta m^2_{32} > 0)<br> dm32<0 is inverted hierarchy (Delta m^2_{32} < 0)</p> <p>Note that the posteriors have not been smoothed, and may contain small discontinuities due to MCMC statistical uncertainties.</p> <p>Plots with "_bestfit" appended indicate the point in the 2D parameter space (marginalized over the other parameters) with the highest posterior density, and is not necessarily the global minimum of the likelihood.</p> <p>For the 1D posterior distributions, the user can freely calculate credible intervals from the distributions. It is recommended to start at the point of the highest posterior density, and moving down in posterior density to produce highest posterior credible intervals, which is the kind of credible intervals reported in the paper. </p> <p>**************************************<br>***** Glossary of tags used in objects names<br>**************************************</p> <p>"wRC" - Uses “reactor constraint” on theta13, sin^2(2theta_13)=(8.53+-0.27) x 10^{-2}<br>"FC" - Feldman-Cousins<br>"NO" - Normal mass Ordering<br>"IO" - Inverted mass Ordering<br>"both" - Marginalised over normal and inverted mass orderings<br>"profMO" - Profiled over normal and inverted mass orderings<br>"cred" - Credible interval<br>"conf" - Confidence interval<br>"68" - 68.3% (1 sigma)<br>"90" - 90%<br>"955" - 95.5% (2 sigma)<br>"997" - 99.7% (3 sigma)<br>"chi2" - DeltaChi^2 (-2lnL) for parameter<br>"Critical" - Critical DeltaChi^2 computed using Feldman-Cousins method<br>"th13" - sin^2(theta_13)<br>"th23" - sin^2(theta_23)<br>"dCP" - delta CP<br>"dm2" - Delta m^2_{23} (NO), |Delta m^2_{13} (IO)| for confidence intervals; used for frequentist analyses results.<br>"dm32" - Delta m^{2_{23} regardless of mass ordering; in the Bayesian analyses, Delta m^2_{23} is always the variable that is plotted.<br>"jarlskog" - Jarlskog invariant<br>"flatdcp" - Using prior probability uniform in deltaCP<br>"flatsindcp" - Using prior probability uniform in sin(deltaCP)</p>
Data for "Strong linkage of El Niño-Southern Oscillation to the polar cold air mass in the Northern Hemisphere"
<p>This repository archives codes for analysis and plot presented in Abdillah et al. (2018): "Strong linkage of El Niño-Southern Oscillation to the polar cold air mass in the Northern Hemisphere". The codes are written in GrADS, Octave, and NCL format. </p> <p>The repository also includes a Fortran package for isentropic polar cold air mass diagnosis as in Iwasaki et al. (2014). The package was specifically created by Dr. Y. Kanno.</p> <p>Reference:</p> <p>Abdillah, M. R., Kanno, Y., Iwasaki, T. (2018). Strong linkage of El Niño‐Southern Oscillation to the polar cold air mass in the Northern Hemisphere. <em>Geophysical Research Letters, in press. </em>https://doi.org/10.1029/2018GL077612</p> <p>Iwasaki, T., Shoji, T., Kanno, Y., Sawada, M., Ujiie, M., & Takaya, K. (2014). Isentropic Analysis of Polar Cold Airmass Streams in the Northern Hemispheric Winter. <em>Journal of the Atmospheric Sciences</em>, <em>71</em>(6), 2230–2243. https://doi.org/10.1175/JAS-D-13-058.1</p>
Raw Data from Fluoroacetate Dehalogenase Solved by Serial Oscillation Crystallography (1° oscillation per crystal), PDB 6MUH
<p>This is the raw data for PDB 6MUH: Fluoroacetate dehalogenase, room temperature structure solved by serial 1 degree oscillation crystallography.</p> <p>Data was taken at Beamline G3 of CHESS at 10.2 keV (1.2155 Å). Collection date was 2018-03-04. Beam size 7 µm V x 9 µm H, flux 2e11 ph/s. Detector: Dectris EIGER X 1M. Data format: Dectris HDF5 for EIGER. Rotation was counterclockwise about the laboratory Z-axis ( 0 -1 0 in the XDS coordinate system). Detector distance was 45 mm.</p> <p>One degree from each data well was collected, at 0.2° per frame. Each well has five data frames. Data was collected in four successive iterations, labeled 000-003, of 1600 wells; each *master.h5 corresponds to 8000 data frames. </p>
Forward Asteroseismic Modeling of Stars with a Convective Core from Gravity-mode Oscillations: Parameter Estimation and Stellar Model Selection
<p>MESA inlists associated with <a href="https://ui.adsabs.harvard.edu/#abs/arXiv:1806.06869">Aerts et al. (2018)</a>. MESA version 10108.</p> <p>Publication DOI: <a href="https://doi.org/10.3847/1538-4365/aaccfb">10.3847/1538-4365/aaccfb</a></p>
Asymptotic analysis of dipolar mixed modes of oscillations in red giant stars
<p>MESA inlists associated with <a href="https://ui.adsabs.harvard.edu/?#abs/2016PASJ...68..109T">Asymptotic analysis of dipolar mixed modes of oscillations in red giant stars</a></p>
Modules for Experiments in Stellar Astrophysics (MESA): Planets, Oscillations, Rotation, and Massive Stars
<p>MESA inlists associated with <a href="https://ui.adsabs.harvard.edu/?#abs/2013ApJS..208....4P">Modules for Experiments in Stellar Astrophysics (MESA): Planets, Oscillations, Rotation, and Massive Stars</a></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.