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4,376 results for “magnetism”
Measuring Magnetic 1/f Noise in Superconducting Microstructures and the Fluctuation-Dissipation Theorem - Data
<p>Figures and corresponding data associated with the manuscript 'Measuring Magnetic 1/f Noise in Superconducting Microstructures and the Fluctuation-Dissipation Theorem' by Herbst et al.</p>
NMR data for "Rapid and simple 13C-hyperpolarization by 1H dissolution dynamic nuclear polarization followed by an in-line magnetic field inversion"
<p>Liquid-state and solid-state NMR data for "Rapid and simple 13C-hyperpolarization by 1H dissolution dynamic nuclear polarization followed by an in-line magnetic field inversion".</p> <p>The data enclosed are NMR data generated by the software Topspin by Burker Biospin. The experiments are dDNP runs that come in two parts: a solid-state and a liquid-state part.</p> <ul> <li>Experiments from 1 to 9 are reference experiments used to quantify polarization in other experiments</li> <li>Experiments 11-19, 21-29, 31-39, ... 61-69 correspond to 6 dDNP runs performed a different samples from the same batch. The numbers correspond between solid and liquid-state datasets</li> </ul> <p>The codes used to analyze the data are available at in a next upload.</p> <p>Refer to the main text of the paper and its supplementary material at 10.26434/chemrxiv-2023-6gd0l for more information.</p>
Magnetic resonance spectroscopy data acquired in tinnitus subjects and healthy volunteers using PRESS sequence
<p>This dataset contains raw free induction decay (FID) signals collected during 1H magnetic resonance spectroscopy (MRS) study in 52 individuals with tinnitus (24 with unilateral and 28 with bilateral tinnitus) and 25 healthy volunteers (described in detail in a separate article doi:10.1038/s41598-023-45024-3).</p><p>Data acquisition was performed using 3T Siemens Prisma Fit scanner with a 20-channel receiver head-coil. A single voxel spectroscopy (SVS) PRESS (Point-Resolved Spectroscopy Sequence) sequence was applied for collection of MRS data, using standard Siemens water suppression (water saturation, 50 Hz bandwidth) and no lipid suppression. MRS data was collected from four cubic 3.75 cm3 (1.5 cm x 1.5 cm x 1.5 cm) regions-of-interest in the brain, placed in the left temporal lobe, right temporal lobe, left frontal lobe, and right frontal lobe. The MRS sequence parameters were: TR (time of repetition) = 2000 ms, TE (time of echo) = 40 ms, TA (time of acquisition) = 4 min 26 s, 128 averages with 1024 time points and 1200 Hz bandwidth.</p><p>MRS data is stored in RDA file format, developed by Siemens (see doi:10.1002/nbm.4257, Table 1). Each RDA file contains a text header (which can be viewed using a standard notepad application) and binary FID signal under the header. Data can be imported for analysis using several open-source packages (tested with FID-A doi:10.1002/mrm.26091 and spant doi:10.21105/joss.03646). </p><p>Naming scheme of files is as follows:</p><p><participant ID>_<hemisphere: L or R>_<region: F (frontal) or T (temporal)>.rda</p><p>For example: <i>001_L_F.rda</i> is data from participant 001 collected from a voxel placed in a ROI in the left frontal lobe.</p><p>In order to allow replication of the results from the original article, we also added information about the group of each of the subjects. This information is stored in a TSV file containing two columns: <i>participant_ID</i> and<i> group</i> (C – control, TU – unilateral tinnitus, TB – bilateral tinnitus).</p><p>Aside from replication of our results this dataset may be used e.g. for testing of different MRS data processing pipelines.</p>
Synthetic magnetic nanoparticles for remote-controlled stemcell therapies of neurodegenerative disorders
<p>In the context of the MAGNEURON european project, we developed different types of magnetic nanoparticles that can act as nanoactuators to manipulate intracellular proteins involved in signaling pathways.</p> <p>Four types of particles are presented here. First, size-sorted maghemite cores of different diameter (8 to 20 nm) were synthesized. Then these cores were used to make Fe2O3@SiO2 core-shell nanoparticles that are colloidally stable and easy to functionalize, and poly(acrylic acid) coated nanoparticles. Both types of particles can be rendered fluorescent by the addition of a fluorophore. Finally, we also developed a way to synthesize micro-needles made of aligned maghemite cores encapsulated in a silica layer.</p> <p>In this dataset are presented some electron microscopy images of the optimized particles and their characterizations in terms of sizes and magnetic properties. These particles have then been used by the other members of the Magneuron consortium in order to manipulate different intracellular signalling pathways.</p>
Magnetism and anomalous transport in the Weyl semimetal PrAlGe: Possible route to axial gauge fields
<p>The file ManuscriptDataFiles.7z contains the raw experimental data from which the figures are made in the manuscript entitled "Magnetism and anomalous transport in the Weyl semimetal PrAlGe: Possible route to axial gauge fields" that appeared in npj Quantum Materials <strong>5</strong>, 5 (2020).</p> <p>Paper Abstract: In magnetic Weyl semimetals, where magnetism breaks time-reversal symmetry, large magnetically sensitive anomalous transport responses are anticipated that could be useful for topological spintronics. The identification of new magnetic Weyl semimetals is therefore in high demand, particularly since in these systems Weyl node configurations may be easily modified using magnetic fields. Here we explore experimentally the magnetic semimetal PrAlGe, and unveil a direct correspondence between easy-axis Pr ferromagnetism and anomalous Hall and Nernst effects. With sizes of both the anomalous Hall conductivity and Nernst effect in good quantitative agreement with first principles calculations, we identify PrAlGe as a system where magnetic fields can connect directly to Weyl nodes via the Pr magnetization. Furthermore, we find the predominantly easy-axis ferromagnetic ground state co-exists with a low density of nanoscale textured magnetic domain walls. We describe how such nanoscale magnetic textures could serve as a local platform for tunable axial gauge fields of Weyl fermions.</p>
Reconnection rates of the paper "Simulation of plasmaspheric plume impact on dayside magnetic reconnection"
<p>This repository contains the dataset needed for the paper "Simulation of plasmaspheric plume impact on dayside magnetic reconnection", i.e. the magnetic reconnection rates at each time and the quantities needed to normalize them. All the data are stored in the file "rates_norm.h5". The file "si_content.pdf" explain how the data are stored and how you can extract them.</p>
3D motion of flexible ferromagnetic filaments under rotating magnetic field
<p>This repository contains experimental data and numerical results related to the publication: A. Zaben, G. Kitenbergs, A. Cēbers (2020), 3D motion of flexible ferromagnetic filaments under rotating magnetic field. Soft Matter, <a href="https://doi.org/10.1039/D0SM00403K">https://doi.org/10.1039/D0SM00403K</a> / <a href="https://arxiv.org/abs/2003.03737">https://arxiv.org/abs/2003.03737</a>.</p> <p>Figs_data.xlsx contains the data presented in the figures. Experimental_Data.rar contains experimental images used to obtain the results for Fig. 3 and 9. The files are named with the operating frequency, field strength and filament length. Numerical.rar contains numerical results used in Fig.6, 8 and 9. The files are named with Cm values. The results are in .dat files named with Cm values followed by wt (wend_cm_wt). The first column is for time(t) followed by x,y,z values of filament tips. </p> <p> </p>
Dynamo in weakly collisional non-magnetized plasmas impeded by Landau damping of magnetic fields
<p>This dataset contains a collection of simulation inputs and results used in the paper [I. Pusztai et al (2020) Phys. Rev. Lett., Dynamo in weakly collisional non-magnetized plasmas impeded by Landau damping of magnetic fields, https://arxiv.org/abs/2001.11929]. References to figures below refer to this publication. </p> <p>These simulations are performed using the kinetic-Vlasov solver Gkeyll [version: cd65328c077f+ 2228+ default], for more information on the code visit https://gkyl.readthedocs.io/en/latest/index.html, or consult [J. Juno et al (2018) J. Comp. Phys 353, 110].</p> <p>The input files are found with .lua extension in each simulation directory</p> <p>Content:</p> <p>* Galloway-Proctor-flow_Fig1-kinetic-and-Fig2 <br> Kinetic simulation of the Galloway-Proctor flow, corresponding to the solid lines in Fig. 1 and Fig. 2. </p> <p>* Cnu-and-k-scan_Fig3-and-Fig4a<br> This is a parameter scan in wavelength of the magnetic perturbations [ranging from L0 ("L0") to L0/8 ("L0per8"), with baseline domain size L0] and collision frequencies [ranging from 0.05 ("Cnu005") to 1 ("Cnu1") times the baseline values]. These results are presented in Fig. 3 and Fig. 4a.</p> <p>* Magnetization-scan_Fig4b<br> Scan in magnetization shown in Fig. 4 b. The magnetic field varies between 1 and 100 T ["B1" and "B100", respectively].</p> <p>* Roberts-flow_Fig5 <br> Kinetic simulations of the Roberts flow, shown in Fig. 5. The collision frequency is scaled to 0.3 the physical value (dashed lines, "Roberts_Cnu03_Fig5"), and zero (solid lines, "Roberts_Cnu00_Fig5"). </p> <p>* Pencil_Run_12x12x12.tar.gz<br> Input files for PENCIL CODE simulations.</p>
Flow Magnetic Tweezers: Gyrase dynamics in absence of drug Ciprofloxacin
<p>The video contains a whole field from a force spectroscopy experiment called Flow Magnetic Tweezers (FMT). It shows E. coli DNA Gyrase manipulating DNA topology by relaxing positive and introducing negative coils in absence of Ciprofloxacin, reaction of Gyrase to external torque and eventual wash with SDS.</p>
Magnetization versus applied dc magnetic field data for Li0.7[Cr(pyz)2]Cl0.7·(THF)
<p>Magnetization versus applied dc magnetic field data in the –7 to 7 T field range from 1.85 K to 520 K for Li<sub>0.7</sub>[Cr(pyz)<sub>2</sub>]Cl<sub>0.7</sub>·(THF). The data are provided in a tab-delimited text format.</p>
Datasets For "Estimating Maximum Extent of Auroral Equatorward Boundary using Historical and Simulated Surface Magnetic Field Data", Blake et al. (2020), JGR
<p>Datasets and sample Python codes for the 2020 paper <em>"Estimating Maximum Extent of Auroral Equatorward Boundary using Historical and Simulated Surface Magnetic Field Data"</em>, by Blake et al., submitted to the Journal of Gephysical Research, Space Physics. </p> <p>Up-to-date Python codes can be found at <a href="https://github.com/TerminusEst/Auroral_Boundary_Geomag">https://github.com/TerminusEst/Auroral_Boundary_Geomag</a></p> <p>The complete SWMF simulation folders (including parameter and log files etc.) can be requested from <a href="https://ccmc.gsfc.nasa.gov/index.php">NASA's Community Coordinated Modeling Center</a>.</p> <p>#########</p> <p><strong>Data/ </strong>contains the following:</p> <p><strong>Data/HIST_DATA.txt </strong>contains the minimum Dst values and calculated maximum extents of the auroral equatorward boundaries for 25 years of INTERMAGNET data (1991-2016). The fourth column is the standard deviation of the calculated auroral boundary in degrees. </p> <p><strong>Data/Boundary_Fits.csv </strong>contains the calculated minimum Dst values, and calculated auroral boundaries using Method 1 and Method 2 (see main paper's ttext), for each of the 15 SWMF simulations. Also included are the uncertainties for each calculation.</p> <p><strong>Data/SWMF_outputs/ </strong>contains 15<strong> </strong>.txt files,<strong> </strong>each of which correspond to an SWMF simulation of the same name given in Table 1 in the main text. These data are for the magnetic longitude, magnetic latitude and maximum calculated <em>E<sub>H</sub> </em>(V/km) for each simulation.</p> <p>#########</p> <p><strong>Codes/ </strong>contains two python scripts, and some sample data. These scripts correspond to Section 2 in the main text:</p> <p>1) <strong>Boundary_Calc.py</strong> calculates the extent of the auroral boundary using magnetic latitudes and maximum calculated <em>E<sub>H</sub></em> values from multiple INTERMAGNET sites. </p> <p>2) <strong>Efield_Calc.py </strong>calculates the E-field for a single INTERMAGNET site using the Quebec 1-D resistivity model.</p> <p>A more detailed description of these codes can be found here: <a href="https://github.com/TerminusEst/Auroral_Boundary_Geomag">https://github.com/TerminusEst/Auroral_Boundary_Geomag</a></p> <p> </p>
Magnetism of Topological Boundary States Induced by Boron Substitution in Graphene Nanoribbons
<p>OPEN DATA related to the research publication:</p> <p>Niklas Friedrich, Pedro Brandimarte, Jingcheng Li, Shohei Saito, Shigehiro Yamaguchi, Iago Pozo, Diego Peña, Thomas Frederiksen, Aran Garcia-Lekue, Daniel Sánchez-Portal, and José Ignacio Pascual, <em>Magnetism of Topological Boundary States Induced by Boron Substitution in Graphene Nanoribbons</em>, Phys. Rev. Lett. <strong>125</strong>, 146801 (2020) [arXiv:2004.10280]</p> <p>Abstract: Graphene nanoribbons (GNRs), low-dimensional platforms for carbon-based electronics, show the promising perspective to also incorporate spin polarization in their conjugated electron system. However, magnetism in GNRs is generally associated with localized states around zigzag edges, difficult to fabricate and with high reactivity. Here we demonstrate that magnetism can also be induced away from physical GNR zigzag edges through atomically precise engineering topological defects in its interior. A pair of substitutional boron atoms inserted in the carbon backbone breaks the conjugation of their topological bands and builds two spin-polarized boundary states around them. The spin state was detected in electrical transport measurements through boron-substituted GNRs suspended between the tip and the sample of a scanning tunneling microscope. First-principle simulations find that boron pairs induce a spin 1, which is modified by tuning the spacing between pairs. Our results demonstrate a route to embed spin chains in GNRs, turning them into basic elements of spintronic devices.</p>
Data for: Physics-based Reconstruction Methods for Magnetic Resonance Imaging
<p>Magnetic Resonance Imaging measurement data used in our paper about 'Physics-based Reconstruction Methods for Magnetic Resonance Imaging' (DOI: 10.1098/rsta.2020.0196). (In version 2 the IR-FLASH data set was replaced with one which is from the same volunteer and slice as the ME-SE data set.) </p> <p>The data is acquired from healthy volunteers and stored in the format of the BART toolbox (DOI: <a href="http://doi.org/10.5281/zenodo.592960">10.5281/zenodo.592960</a>).</p> <p>The acquisition parameters are shown in the following table:</p> <p>flip angle[◦] TR/TE/ Delta TE[ms] bandwidth [Hz/px] matrix spokes TA[s] FOV[mm] slice[mm]</p> <p>IR-FLASH 6 4.10/2.58 630 256 × 256 1020 4 192 5<br> ME-SE 90/180 2500/9.9/9.9 390 256 × 256 25 × 16 80 192 3<br> ME-FLASH 5 10.60/1.37/1.34 960 200× 200 33 × 7 0.35a 320 5<br> PC-FLASH 10 4.46/2.96 1250 210 × 210 2 × 7 15 320 5<br> fmSSFPb 15 4.5/2.25 840 192× 192 4 × 101 × 40 137 192 1</p>
Three-dimensional magnetic reconnection in particle-in-cell simulations of anisotropic plasma turbulence (Simulation Data)
<p>This folder contains the output of the following simulation: </p> <p>We use the explicit Plasma Simulation Code (PSC, Germaschewski et al.2016) to simulate eight anisotropic counter-propagating Alfvén waves in an ion-electron plasma. The anisotropy of the initial fluctuation is set up according to the theory of critical balance by Sridhar & Goldreich (1994) and Goldreich & Sridhar (1995) at the small scale end of the inertial range: <span class="math-tex">\(k_{\parallel} d_{i} = C (|k_{\perp}|d_{i})^{2/3}\)</span>, where <span class="math-tex">\(C= 10^{-4/3}\)</span>. The normalization parameters are the speed of light <span class="math-tex">\(c = 1\)</span>, the vacuum permittivity <span class="math-tex">\(\epsilon_{0} = 1\)</span>, the magnetic permeability <span class="math-tex">\(\mu_{0} = 1\)</span>, the Boltzmann constant <span class="math-tex">\(k_{b}=1\)</span>, the elementary charge <span class="math-tex">\(q=1\)</span>, the ion mass <span class="math-tex">\(m_{i}=1\)</span>, the density of ions and electrons <span class="math-tex">\(n_{i}=n_{e}=1\)</span> and the ion inertial length <span class="math-tex">\(d_{i}=c/\omega_{pi}\)</span> where <span class="math-tex">\(\omega_{pi}=\sqrt{n_{i}q^{2}/m_{i}\epsilon_{0}}\)</span> is the ion plasma frequency. We set <span class="math-tex">\(\beta_{s,\parallel}=1\)</span> and <span class="math-tex">\(T_{s,\parallel}/T_{s,\perp}=1\)</span>, where <span class="math-tex">\(\beta_{s,\parallel}=2 n_s \mu_{0} k_{B}T_{s,\parallel}/B_{0}^{2}\)</span> is the ratio between the plasma pressure parallel to the background magnetic field <span class="math-tex">\(\mathbf{B}_{0}\)</span> and the magnetic pressure and $T_{s,\parallel}$ is the parallel temperature. The magnetic field is normalised to <span class="math-tex">\(B_{0}=V_{A}/c\)</span>, where <span class="math-tex">\(V_{A}=B_{0} / \sqrt{\mu_{0}n_{i}m_{i}}\)</span> is the ion Alfvén speed. We use 100 particles per cell (100 ions and 100 electrons), a mass ratio of <span class="math-tex">\(m_{i}/m_{e} = 100\)</span> so that <span class="math-tex">\(d_e = 0.1 d_{i}\)</span> where <span class="math-tex">\(m_{e}\)</span> is the electron mass and <span class="math-tex">\(d_{e}\)</span> is the electron inertial length. The simulation box size is <span class="math-tex">\(L_{x} \times L_{y} \times L_{z} = 24d_{i}\times24d_{i}\times125d_{i}\)</span> and the spatial resolution is <span class="math-tex">\(\Delta x =\Delta y = \Delta z = 0.06d_{i}\)</span>. We use a time step <span class="math-tex">\(\Delta t =0.06/ \omega_{pi}\)</span>. In our normalisation, the Debye length <span class="math-tex">\(\lambda_{D}=d_{i}\sqrt{\beta_{i}/2}V_{A}/c\)</span> defines the minimum spatial distance that needs to be resolve in the simulation and <span class="math-tex">\(\lambda_D=0.07d_i\)</span>.</p> <p>This output corresponds to <span class="math-tex">\(t=120 \omega_{pi}\)</span>. </p> <p>These data were produced using the Data Intensive at Leicester (DIaL) facility provided by the DiRAC project<br> dp126 "Identifying and Quantifying the Role of Magnetic Reconnection in Space Plasma Turbulence".</p>
1st_dataset-Minimal radius of magnetic skyrmions: statics and dynamics
<p>In a broad range of applied magnetic fields and material parameters isolated magnetic skyrmions<br> condense into skyrmion lattices. While the geometry of isolated skyrmions and their lattice<br> counterparts strongly depend on field and Dzyaloshinski–Moriya interaction, this issue has not been<br> adequately addressed in previous studies. Meanwhile, this information is extremely important for<br> applications, because the skyrmion size and the interskyrmion distance have to be tuned for skyrmion<br> based memory and logic devices. In this investigation we elucidate the size and density-dependent<br> phase diagram showing traditional phases in field versus material parameters space by means of<br> Monte-Carlo simulations on a discrete lattice. The obtained diagram permits us to establish that, in<br> contrast to the continuum limit, skyrmions on a discrete lattice cannot be smaller than some critical<br> size and have a very specific shape. These minimal skyrmions correspond to the micromagnetic<br> configuration at the energy barrier between the ferromagnetic and the skyrmionic states.<br> Furthermore, we use atomistic Landau–Lifshitz–Gilbert simulations to study dynamics of the<br> skyrmion annihilation. It is shown that this procees consists of two stages: the continuous skyrmion<br> contraction and its discontinuous annihilation. The detailed analysis of this dynamical process is<br> given.</p>
Symmetry breaking in spin spirals and skyrmions by in-plane and canted magnetic fields
<p>The influence of in-plane and canted magnetic fields on spin spirals and skyrmions in atomic bilayer<br> islands of palladium and iron on an Ir(111) substrate is investigated by scanning tunneling microscopy<br> at low temperatures. It is shown that the spin spiral propagation direction is determined by the island’s<br> border which can be explained by equilibrium state calculations on a triangular lattice.Wefind a<br> different response of spin spirals to in-plane magnetic fields for a propagation direction parallel to the<br> applied field as compared to perpendicular, which originates from their cycloidal nature. As a result,<br> the spin spiral propagation direction may be reorientated by in-plane fields. Furthermore, it is<br> demonstrated that also skyrmions are distorted in canted fields which allows to determine the sense of<br> magnetization rotation as enforced by the interfacial Dzyaloshinskii–Moriya interaction.</p>
Pinning and movement of individual nanoscale magnetic skyrmions via defects
<p>An understanding of the pinning of magnetic skyrmions to defects is crucial for the development of<br> future spintronic applications. While pinning is desirable for a precise positioning of magnetic<br> skyrmions it is detrimental when they are to be moved through a material.Weuse scanning tunneling<br> microscopy (STM) to study the interaction between atomic scale defects and magnetic skyrmions that<br> are only a few nanometers in diameter. The studied pinning centers range from single atom inlayer<br> defects and adatoms to clusters adsorbed on the surface of our model system.Wefind very different<br> pinning strengths and identify preferred positions of the skyrmion. The interaction between a cluster<br> and a skyrmion can be sufficiently strong for the skyrmion to follow when the cluster is moved across<br> the surface by lateral manipulation with the STMtip.</p>
Dirac's magnetic monopole (figure).
<p>A schematic representation of Dirac’s magnetic monopole. The monopole is imagined to be the end point of a semi-infinitely long, infinitesimally thin solenoid known as a "Dirac string", here shown from the side (red lines). The magnetic field lines (black arrows) are shown emanating from the point at the end of the string (imagine the red lines are infinitely close together). If such Dirac monopoles exist, it is the requirement that the string is undetectable that means electric charge must be quantised. Image credit: The Institute for Research in Schools 2016.</p> <p>CERN@school DRN: CAS-PUB-MDL-000007-v1.0</p>
Tailoring noncollinear magnetism by misfit dislocation lines
<p>Data for the publication:</p> <p>"The large epitaxial stress induced by the misfit between a triple atomic layer Fe film and an Ir(111) substrate<br> is relieved by the formation of a dense dislocation line network. Spin-polarized scanning tunneling microscopy<br> investigations show that the strain is locally varying within the Fe film and that this variation affects the magnetic<br> state of the system. Two types of dislocation line regions can be distinguished and both exhibit spin spirals<br> with strain-dependent periods (ranging from 3 to 10 nm). Using a simple micromagnetic model, we attribute the<br> changes of the period of the spin spirals to variations of the effective exchange coupling in the magnetic film.<br> This assumption is supported by the observed dependence of the saturation magnetic field on the period of the<br> zero-field spin spiral. Moreover, magnetic skyrmions appear in an external magnetic field only in one type of<br> dislocation line area, which we impute to the different pinning properties of the dislocation lines."</p>
Dataset for "Reconfigurable Magnonic Crystals Based on Imprinted Magnetization Textures in Hard and Soft Dipolar-Coupled Bilayers"
<p>The dataset consist of the data of the numerical simulations used to prepare the figures for the manuscript: </p><p>Krzysztof Szulc, Silvia Tacchi, Aurelio Hierro-Rodríguez, Javier Díaz, Paweł Gruszecki, Piotr Graczyk, Carlos Quirós, Daniel Markó, José Ignacio Martín, María Vélez, David S. Schmool, Giovanni Carlotti, Maciej Krawczyk, and Luis Manuel Álvarez-Prado. <i>Reconfigurable Magnonic Crystals Based on Imprinted Magnetization Textures in Hard and Soft Dipolar-Coupled Bilayers</i>. ACS Nano <strong>2022</strong> <i>16</i> (9), 14168-14177.</p><p>Please read README.txt file to see the description of the data in the files.</p>
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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.