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343 results for “lock”
Photophysical lock-in detection enables background-free upconversion emission imaging
<p><strong><span lang="EN-GB">This folder contains all raw data underlying the results presented in a manuscript, submitted to <em>Nano Letters</em>, and entitled:</span></strong></p> <p><strong><span lang="EN-GB">Photophysical lock-in detection enables background-free upconversion emission imaging</span></strong></p> <p><strong><span lang="EN-GB">Authored by:</span></strong></p> <p><span lang="EN-GB">Niusha Bagheri<sup>a</sup>, Chenyi Wang<sup>b</sup>, Du Guo<sup>a</sup>, Anbharasi Lakshmanan<sup>a</sup>, Qi Zhu<sup>a</sup>, Xu Chen<sup>a</sup>, Nahid Ghazyani<sup>c</sup>, Qiuqiang Zhan<sup>b</sup>, Georgios A. Sotiriou<sup>d</sup>, Haichun Liu*<sup>a</sup>, Jerker Widengren*<sup>a</sup> </span></p> <p><em><sup><span lang="EN-GB">a</span></sup></em><em><span lang="EN-GB"> Experimental Biomolecular Physics, Department of Applied Physics, KTH Royal Institute of Technology, SE-106 91, Stockholm, Sweden</span></em></p> <p><em><sup><span lang="EN-GB">b</span></sup></em><em><span lang="EN-GB"> Centre for Optical and Electromagnetic Research, South China Academy of Advanced Optoelectronics, South China Normal University, Guangzhou 510006, P. R. China</span></em></p> <p><em><sup><span lang="EN-GB">c</span></sup></em><em><span lang="EN-GB"> Faculty of Physics, Kharazmi University, Tehran, Iran.</span></em></p> <p><em><sup><span lang="EN-GB">d</span></sup></em><em><span lang="EN-GB"> Department of Microbiology Tumor and Cell Biology Karolinska Institute, SE-171 77, Stockholm, Sweden</span></em></p> <p><span lang="EN-GB">Corresponding authors:</span></p> <p><span lang="EN-GB">*haichun@kth.se, jwideng@kth.se</span></p> <p><strong><span lang="EN-GB">The data files containing raw data and results of the analysis are grouped according to the different figures in the manuscript where the extracted results are presented.</span></strong></p> <p><strong><span lang="EN-GB">ABSTRACT</span></strong></p> <p><span><span lang="EN-GB">Lanthanide-based upconversion nanoparticles (UCNPs) have attracted considerable attention in biomedical applications, due to their anti-Stokes shifted emission enabling autofluorescence-free signal detection. However, residual excitation light can still interfere with their relatively low brightness. While commonly used lock-in detection can distinguish weak signals from substantial random background, concurrently modulated residual excitation light is not eliminated. This remains a challenge, particularly under demanding experimental conditions.</span></span></p> <p><span><span lang="EN-GB">Here, we </span></span><span><span><span lang="EN-GB">pro</span></span></span><span><span><span lang="EN-GB">pose a photophysical lock-in detection (PP-LID) approach based on the discovery that UCNPs can act as frequency mixers in response to intensity-modulated excitation. Particularly, modulated excitation with more than one base modulation frequency can generate additional low-frequency beating-signals. These signals are resolvable by frame-rate-limited cameras, devoid of ambient and residual excitation light, and can be regulated through nanoparticle engineering. Extracting beating-signals by PP-LID thus provides a strategy to significantly enhance signal-to-background conditions in UCNP-based bioimaging and biosensing.</span></span></span></p> <p><strong><span lang="EN-GB">Keywords: </span></strong><span lang="EN-GB">Upconversion nanoparticles (UCNPs), nonlinearity, modulation, lock-in detection, second harmonic, beating frequency, fast Fourier Transform (FFT)</span></p>
LOCKED: A dataset of sociodemographic, economic, living, and health features to measure the impact of the Spanish lockdown during COVID-19 on mental health conditions
<p>A dataset aimed at enhancing the understanding of the mental health effects of the COVID-19 lockdown in Spain. This dataset serves as a valuable resource by integrating psychological assessments, such as the SA-45 pyschological test, with comprehensive socioeconomic, living, and health-related information. By combining these diverse data points, the dataset enables researchers to analyze how various invidual factors influenced nine mental health conditions during the lockdown, providing a robust foundation for further studies on this critical topic.</p>
Pad Lock
3D model of a very well-preserved padlock made of iron. Physical object held at the National Museum of Iceland nr: 2008-36-562. Found 08/07/2008 by BB https://sarpur.is/Adfang.aspx?AdfangID=1471343 Part of the Skriðuklaustur Monastery 1550 reconstruction. Digitisation by Open Virtual Worlds, a research team within the School of Computer Science, University of St Andrews, in cooperation with the Gunnar Gunnarsson Institute at Skriðuklaustur and the National Museum of Iceland. 3D digitisation was done by Catherine Cassidy and Iain Oliver with archaeological assistance provided by Skúli Gunnarsson. Funded by the EU Northern Periphery and Arctic Programme 2014-2020 through the "Connected Culture and Natural Heritage in a Northern Environment" (CINE) project. Source: Objaverse 1.0 / Sketchfab
Camden Lock - 360 Measurements (E,B)
Camden Lock, London, UK "Camden Lock is a small part of Camden Town, London Borough of Camden, England, which was formerly a wharf with stables on the Regent's Canal." 360 Measurements - Preview (External, Black&White) SIAD REF : OX116 Source: Objaverse 1.0 / Sketchfab
Canal Lock Park Huber Heights, Ohio
Please Like Before Downloading. Thank You! Canal Rock Park is not only a site offering natural beauty but a small slice of history also awaits you here. Earlier, this site was one of the most important centers of transportation and has a great importance in early Ohio history. #photogrammetry Created in RealityCapture by Capturing Reality from 2016 images. If you use this in a scene please share. Would be great to see. Thanks Source: Objaverse 1.0 / Sketchfab
Box lock from the house of Szymon Kluger
Full name: **Surface-mount box lock from the house of Szymon Kluger in Oświęcim, Poland** Surface-mount box lock from the house of Szymon Kluger in Oświęcim, preserved before the 2013-14 renovation of the building. At present, part of the interior design of Café Bergson, run by the Auschwitz Jewish Center (AJC). **For more images and further information, visit:** https://muzea.malopolska.pl/en/lista-obiektow/3011 Inventory number: MZ-416-O Localisation of the physical object: [Auschwitz Jewish Center](https://ajcf.pl/en/), Oświęcim, Poland **Digitalisation: Regional Digitalisation Lab, Małopolska Institute of Culture in Kraków, Poland; "Virtual Museums of Małopolska" project** Source: Objaverse 1.0 / Sketchfab
Data and codes for "Chapter 2: Particle-laden gravity currents: the lock-release slumping regime at the laboratory scale"
<div> <div> <h1>PALAGRAM Monograph</h1> </div> <p>This repository contains the data used in the book chapter:</p> <blockquote> <p>Gadal, C., Schneider, J., Bonamy, C., Chauchat, J., Dossmann, Y., Kiesgen de Richter, S., Mercier, M.J., Naaim-Bouvet, F., Rastello, M. and Lacaze, L. (2025). <strong>Particle-laden Gravity Currents: The Lock-release Slumping Regime at the Laboratory Scale.</strong> In Particulate Gravity Currents. <a href="https://doi.org/10.1002/9781394216727.ch2">10.1002/9781394216727.ch2</a></p> </blockquote> <div> <h2>Repository organization</h2> </div> <div> <pre><code> palagram_monograph │ └───data: data are stored here │ └───input_data: input data as sent by everyone │ └─── ... : NETCDF files │ └───output_data: processed data output by analysis.py (also contains input_data) │ └─── ... : NETCDF files └───analysis: └───analysis.py: analysis code, that reads input_data and writes output_data └───paper: contains source files for article │ └───figures: contains source figures │ └─── ... : PDF files │ └─── figure_scripts: contains figure scripts that reads data in data/output_data and writes figures in paper/figures │ └─── *.py : python scripts for figures │ └─── ... : various files (.tex, .bib, ...) │ └─── main.pdf : article preprint </code></pre> <div> </div> </div> <div> <h2>Data organization</h2> </div> <p>The CSV file <code>dataset_summary.csv</code> offers a summary of all runs and corresponding experimental parameters, allowing for easier access to the data.</p> <p>The folder <code>data/output_data</code> contains 287 netcdf4 files corresponding to each experimental run used in the paper. For each run, the structure of the NetCDF file is the following:</p> <ul> <li> <p>attributes:</p> <ul> <li>particle_type: particle type used (silica sand, glass beads, etc..)</li> <li>label: filename</li> <li>lab: lab where this run has been performed</li> <li>run_oldID: Old filename, corresponding to the experimental notebook</li> <li>author: author(s) that acquired this run</li> <li>setup: setup used to acquire the data. See article.</li> <li>dataset: Dataset classification of this run, See paper.</li> </ul> </li> <li> <p>dimensions(sizes): time(n)</p> </li> <li> <p>variables(dimensions):</p> <ul> <li>At(): Atwood number</li> <li>Fr(): Froude number (adi. initial current velocity)</li> <li>H0(): initial heavy fluid height inside the lock</li> <li>H_a(): ambient fluid height outside the lock</li> <li>L0(): streamwise lock length</li> <li>L_1(): streamwise tank length after the lock</li> <li>Re(): Reynolds number</li> <li>S(): Settling number</li> <li>St(): Stokes number</li> <li>T_a(): ambient temperature</li> <li>T_f(): heavy fluid temperature inside the lock</li> <li>W0(): crossstream lock width</li> <li>a(): lock aspect ratio</li> <li>alpha(): bottom slope</li> <li>d(): particle diameter</li> <li>gprime(): specific gravity</li> <li>lamb(): adi. attenuation parameter</li> <li>nu_a(): ambient viscosity</li> <li>nu_f(): heavy fluid lock viscosity</li> <li>phi(): initial particle volume fraction inside the lock</li> <li>rho_a(): ambient fluid density</li> <li>rho_c(): heavy fluid mix density inside the lock</li> <li>rho_f():</li> <li>rho_p(): particle density</li> <li>t('time',): time vector</li> <li>t0(): characteristic timescale, t0 = L0/u0</li> <li>u0(): characteristic velocity scale, u0 = sqrt(gprime*H0)</li> <li>vs(): particle Stokes velocity</li> <li>x_front('time',): front position vector</li> </ul> </li> </ul> <p>Variables can sometimes possess the following attributes:</p> <ul> <li>unit: corresponding unit</li> <li>std: error(s) on the given quantity, calculated by error propagation from measurement uncertainties using the <code>uncertainties</code> module (<a href="https://pythonhosted.org/uncertainties/" rel="nofollow">https://pythonhosted.org/uncertainties/</a>) in Python.</li> <li>comments: comments on the given quantity (definition, formulas, etc ..)</li> </ul> <div> <h2>Related works</h2> </div> <ul> <li> <p>Gadal, C., Schneider, J., Bonamy, C., Chauchat, J., Dossmann, Y., Kiesgen de Richter, S., Mercier, M.J., Naaim-Bouvet, F., Rastello, M. and Lacaze, L. (2025). Particle-laden Gravity Currents: The Lock-release Slumping Regime at the Laboratory Scale. In Particulate Gravity Currents. <a href="https://doi.org/10.1002/9781394216727.ch2">10.1002/9781394216727.ch2</a></p> </li> <li>Gadal, C., Mercier, M. J., Rastello, M., & Lacaze, L. (2023). Slumping regime in lock-release turbidity currents. <em>Journal of Fluid Mechanics</em>, 974, A4. <a href="https://doi.org/10.1017/jfm.2023.762" rel="nofollow">doi:10.1017/jfm.2023.762</a></li> <li> <p>Gadal, C., Mercier, M., Rastello, M., & Lacaze, L. (2023). Data used in 'Slumping regime in lock-release turbidity currents' [Data set]. In Journal of Fluid Mechanics (Vol. 974, p. A4). <em>Zenodo</em>. <a href="https://doi.org/10.5281/zenodo.10058946" rel="nofollow">https://doi.org/10.5281/zenodo.10058946</a></p> </li> <li> <p>Schneider, J., Dossmann, Y., Farges, O. et al. Investigation of particle laden gravity currents using the light attenuation technique. <em>Exp Fluids</em>, 64, 23 (2023). <a href="https://doi.org/10.1007/s00348-022-03562-y" rel="nofollow">doi:10.1007/s00348-022-03562-y</a></p> </li> <li> <p>Chauchat, J., Cheng, Z., Nagel, T., Bonamy, C., and Hsu, T.-J. (2017) SedFoam-2.0: a 3-D two-phase flow numerical model for sediment transport, <em>Geosci. Model Dev.</em>, 10, 4367-4392, <a href="https://doi.org/10.5194/gmd-10-4367-2017" rel="nofollow">doi:10.5194/gmd-10-4367-2017</a> and <a href="https://github.com/sedfoam/sedfoam">github</a></p> </li> </ul> </div>
3D localization AFM (3D-LAFM) density map of glutamate transporter GltPh inward facing state open, kinetically locked, (IFSopen-1) conformation at apo condition, imaged from the cytoplasmic side
<p>3D localization AFM (3D-LAFM) density map of glutamate transporter GltPh inward facing state open, kinetically locked, (IFSopen-1) conformation at apo condition, imaged from the cytoplasmic side , in <code>.afm</code> format and in <code>.mrc</code> format.</p> <p>Note: The <code>.afm</code> file encodes details for constructing 3D-LAFM density maps and includes experimental conditions in its header. Using <code>.afm</code> files requires the additional installation of the AFM file encoder (available from <a href="https://github.com/rafaeljiang23/3D-LAFM/tree/main/ChimeraX-AfmFormat_v2">GitHub</a>). Once the relevant installation is complete, <code>.afm</code> files can be opened in ChimeraX via drag-and-drop. In contrast, <code>.mrc</code> files, which encode only the density values equivalent to <code>.afm</code> files, can be directly opened in ChimeraX without requiring additional software installation.</p> <p>The deposited <code>.afm</code> file follows the 'AFM1' (metacode) format standard.</p>
Raw data and scripts for "The Period-Modulated Harmonic Locked Loop (PM-HLL): A low-effort algorithm for rapid time-domain multi-periodicity estimation"
<p>This package contains all required scripts to generate the simulations and figures from the study "The Period-Modulated Harmonic Locked Loop (PM-HLL): A low-effort algorithm for rapid time-domain multi-periodicity estimation" by Volker Hohmann, published in Acta Acustica:</p> <p>The Period-Modulated Harmonic Locked Loop (PM-HLL): A low-effort algorithm for rapid time-domain multi-periodicity estimation<br>Volker Hohmann<br>Acta Acust. 5 56 (2021)<br>DOI: 10.1051/aacus/2021050</p> <p>When referring to this work, please cite the journal paper.</p> <p>Note that additive noise is generated at random, i.e., small differences in the estimation accuracy occur when repeating a simulation. For further details see the journal paper.</p> <p>Thank you for downloading the package. Your comments are very welcome!</p> <p>Method patented: DE Patent DE102021207339B3</p> <p>Author: Volker Hohmann, Carl von Ossietzky Universität Oldenburg, Germany</p>
Lock-in and Standard DPC raw images associated to publication 10.1364/PRJ.445896
<p>Raw images obtained with helicam C3 in a DPC microscope setup. The raw images were used for the figures in the publication Chiara Bonati, Damien Loterie, Timothé Laforest, Christophe Moser. Lock-in incoherent differential phase contrast imaging. Photonics Research, 2022, 10(1):237.</p> <p>Contents of the data set:</p> <ol> <li><strong>Contrast comparison</strong>: images used for Figure 4. Several USAF targets of different height, introducing varying phase differences. Samples were imaged under both standard and lock-in DPC. <ol> <li><strong>Lock-in DPC</strong>: lock-in DPC image sets. Each image was collected over four cycles of 140 us each. <ol> <li><strong>5_mrad</strong>: 5 mrad sample <ul> <li><strong>Background</strong>: no sample image <ul> <li><strong>I</strong>: Frame I</li> <li><strong>Q</strong>: Frame Q</li> </ul> </li> <li><strong>Sample</strong>: sample image <ul> <li><strong>I</strong>: Frame I</li> <li><strong>Q</strong>: Frame Q</li> </ul> </li> </ul> </li> <li><strong>13dot8_mrad</strong>: 13.8 mrad sample</li> <li><strong>15dot1_mrad</strong>: 15.1 mrad sample</li> <li><strong>18dot9_mrad</strong>: 18.9 mrad sample</li> <li><strong>35dot2_mrad</strong>: 35.2 mrad sample</li> <li><strong>50dot5_mrad</strong>: 50.5 mrad sample</li> </ol> </li> <li><strong>Standard DPC: </strong>Same set of images, under standard DPC conditions. Each illumination (left and right) was recorded for 1 us. <ol> <li><strong>5_mrad</strong>: 5 mrad sample <ul> <li><strong>Background</strong>: no sample image <ul> <li><strong>L</strong>: Image under left illumination</li> <li><strong>R</strong>: Image under right illumination</li> </ul> </li> <li><strong>Sample</strong>: sample image <ul> <li><strong>L</strong>: Image under left illumination</li> <li><strong>R</strong>: Image under right illumination</li> </ul> </li> </ul> </li> <li><strong>13dot8_mrad</strong>: 13.8 mrad sample</li> <li><strong>15dot1_mrad</strong>: 15.1 mrad sample</li> <li><strong>18dot9_mrad</strong>: 18.9 mrad sample</li> <li><strong>35dot2_mrad</strong>: 35.2 mrad sample</li> <li><strong>50dot5_mrad</strong>: 50.5 mrad sample</li> </ol> </li> </ol> </li> <li><strong>Reconstruction</strong>: Image sets used for figures 5 and 6 <ol> <li><strong>USAF_50dot5mrad</strong>: Image sets of a 50.5 mrad glass USAF target. <ol> <li><strong>Illumination</strong>: Folder containing the back-focal plane characterisation of the imaging system, used to compute the transfer functions for phase reconstruction. <ul> <li>BFP: the back-focal plane aperture of the 0.4 NA objective</li> <li>P_1: reduced pupil used in the experiments</li> <li>s_L: left source</li> <li>s_R: right source</li> </ul> </li> <li><strong>Lock-in DPC</strong>: lock-in DPC image set. The equivalent exposure time was 464 us.</li> <li><strong>Standard DPC</strong>: standard DPC image set. Each illumination was exposed for 8 us.</li> </ol> </li> <li><strong>Onion</strong>: Image sets of onion epidermal cells. <ol> <li><strong>Lock-in DPC</strong>: lock-in DPC images for varying equivalent exposure times. <ul> <li>104 us</li> <li>120 us</li> <li>136 us</li> <li>152 us</li> <li>168 us</li> <li>184 us</li> <li>200 us</li> <li>216 us</li> <li>232 us</li> <li>248 us</li> </ul> </li> <li><strong>Standard DPC</strong>: Standard DPC image set at 7 us exposure time</li> </ol> </li> </ol> </li> </ol> <p> </p> <p> </p>
Data and R codes from: Exploring the effect of 195 years-old locks on species movement: Landscape genetics of painted turtles in the Rideau Canal, Canada
<p>Aquatic systems have been extensively altered by human structures (e.g., construction of dams/canals) and these have major impacts on the connectivity of wildlife populations through the loss and isolation of suitable habitats. Habitat loss and isolation affect gene flow and influence the persistence of populations in time and space by restricting movements. Isolation can result in higher inbreeding, lower genetic diversity, and greater genetic structure, which may render populations more vulnerable to environmental changes, and thus to extinction. Given the ubiquity and the persistence of dams and canals in space and time, it is crucial to understand their effects on the population genetics of aquatic species. Here, we documented the genetic diversity and structure of painted turtle (<em>Chrysemys picta</em>) populations in the Rideau Canal, Ontario, Canada. More specifically, we used 13 microsatellites to evaluate the influence of locks on genetic variation in 822 painted turtles from 22 sites evenly distributed along the 202-km canal. Overall, we found low, but significant, genetic differentiation suggesting that some dispersal is occurring throughout the canal. In addition, we showed that locks contribute to the genetic differentiation observed in the system. Clustering analysis revealed two distinct genetic groups whose boundary is associated with a series of six locks. Our results illustrate how artificial waterways, such as canal systems, can influence population genetic structure. We highlight the importance of adopting management plans that can mitigate the impacts of human infrastructure and preserve gene flow across the landscape to maintain viable populations.</p>
Platicon microcomb generation using laser self-injection locking
<p>This dataset contains data presented in the Figures of the paper "Platicon microcomb generation using laser self-injection locking"</p>
Travel Time Statistics for Links with Locks from L&D 16 to L&D 20
<p>This is an Excel spreadsheet that contains multiple travel time performance statistics for the Upper Mississippi River from L&D 16 to L&D 20. It includes a map depicting the links in the table.</p>
Travel Time and Speed Statistics for Links Containing Locks 16 through 20
<p>This is an Excel spreadsheet that records the travel times/speeds of each trip through a lock in the range of Lock & Dam 16 through Lock & Dam 20 in the Upper Mississippi River. Each lock is part of a three sublink set: a sublink upriver from the lock, the lock itself, and a sublink downriver . A table of links used by the study, a link map, and heat maps are also included.</p>
Lock Jaw
High resolution full color scan of a classic 80s toy, MadBalls. Done for local shop the Gnarly Toybox. For more information and to add something to your collection reach out to @thetoyclown on instagram or find the ganrly toybox if you are in the Denver Area. For more information on Full Color 3D scanning, 3D scanners and Reality 3D please visit us at www.Reality3D.net or send us your questions at Info@reality3D.net Source: Objaverse 1.0 / Sketchfab
Door Lock Full
This lock is original surface mount hardware to Rennold's Manor in Essex County, Va, ca 1790-1800 (renamed Poverty Ridge in early 20th century). Original door frames fitted to Carpenter locks still in place. Source: Objaverse 1.0 / Sketchfab
Lock (water navigation) TM2027
This wooden model was built by Jonas Norberg in 1761. It was created according to Christopher Polhem´s construction of a lock (water navigation) in Stockholm. Norberg worked closely with Polhem and knew the construction in detail. The model is part of the Swedish Royal Model Chamber and was used instead of drawings in case the construction needed to be repaired. The model is now part of the collections of the Swedish National Museum of Science and Technology. TM 2027 (TEKS0021755) [TM2027](https://digitaltmuseum.se/021026304527/stockholms-sluss-modell"2027") Read more about [Polhem](https://en.wikipedia.org/wiki/Christopher_Polhem"polhem") on Wikipedia. Source: Objaverse 1.0 / Sketchfab
Codes and data for Software lock-in processing
<p>These codes and data sets are going to be published in:</p> <p>Oppermann, F., Günther, T.: A remote-control datalogger for large-scale resistivity surveys and robust processing of its signals using a software lock-in approach; Geosci. Instrum. Method. Data Syst.</p>
DAVE - Measuring run on Mittellandkanal in Hannover, Germany - Lock entrance
<p>The dataset was collected during a measurement run on the Mittellandkanal in Hanover, Germany.</p> <p>The data is provided in the ros2bag mcap storage format.</p> <p>The bag files contain data from the following sensors </p> <ul> <li>Lidar</li> <li>Camera</li> <li>GPS</li> <li>Wind</li> </ul> <p>The bag file can be played using the free foxglove studio software. A layout json file is also provided. </p> <p>This bag file shows the lock Anderten in the canal.</p> <p> </p> <p>This publication is a result of the research of the Center of Excellence CoSA and funded by the Federal Ministry for Digital and Transport of the Federal Republic of Germany (Id 19F2225C, DAVE).</p> <p> </p> <p>Project website: https://www.th-luebeck.de/cosa/projekt/dave/</p>
Data for the manuscript "Bridged Nucleic Acid ASOs over Locked Nucleic Acid ASOs and their impact on the structure and stability of ASO/RNA duplexes"
<p>The dataset contains: DFT and MD Data for the manuscript "Bridged Nucleic Acid ASOs over Locked Nucleic Acid ASOs and their impact on the structure and stability of ASO/RNA duplexes". </p> <p> </p> <p> </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.