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1,457 results for “feedbacks”
Data and Code in support of Caterpillar abundance in a northern hardwood forest: exogenous effects, endogenous feedbacks, and multidecadal trends.
In this study, we analyzed caterpillar abundance and biomass measured over 50 years (1970 - 2021) in the Hubbard Brook Experimental Forest, New Hampshire, USA. We tested mechanisms for determination of caterpillar abundance that included weather, host plant quality, and predator abundance. This dataset includes data, R code, and spatial files supporting this study. These data were gathered as part of the Hubbard Brook Ecosystem Study (HBES). The HBES is a collaborative effort at the Hubbard Brook Experimental Forest, which is operated and maintained by the USDA Forest Service, Northern Research Station.
FeedBES - FeedBack signals from Episodic and Semantic memories.
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EEG: Probabilistic Learning with Affective Feedback: Exp #2
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EEG: Probabilistic Learning with Affective Feedback: Exp #1
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Sonic Kayak feedback survey results
<p>This data set is part of the Sonic Kayak project https://fo.am/activities/kayaks/</p> <p>An anonymous survey was performed online in August/September 2020, to gather people's opinions on the Sonic Kayak project, as we were not able to take people out to try the kayaks in person. A video explainer was provided (https://www.youtube.com/watch?v=puLXKj1AVAk) followed by optional prompting questions. The data presented is in its raw form.</p>
Data to "Humans Can Visually Judge Grasp Quality and Refine Their Judgments Through Visual and Haptic Feedback"
<p>This record contains experimental and analysis scripts (written in Matlab) as well as raw and processed data to reproduce the results shown in:</p> <p>Maiello, G.^, Schepko, M.^, Klein, L. K., Paulun, V. C., and Fleming, R. W. (2021) Humans Can Visually Judge Grasp Quality and Refine Their Judgments Through Visual and Haptic Feedback. Front. Neurosci. 14:591898.<br> doi: 10.3389/fnins.2020.591898</p> <p>A preprint version of the manuscript is available at: https://doi.org/10.1101/2020.08.11.246173</p>
SAAM Sleep Coaching User Feedback
<p>The data set was collected within the SAAM Project (Supporting Active Aging through Multimodal coaching, https://saam2020.eu/), and was used to develop a preference learning methodology with the aim of improving user's acceptance of coaching actions. The data set contains a set of sleep quality coaching actions and userćs feedback for each of them.</p>
An Experiences Survey about Sprint Feedback for Teams
<p>This survey elicits thoughts and experiences from researchers and practitioners towards the relevance of sprint feedback for teams in agile software development. The survey covers the following aspects: demographics, team-driven factors, information usages for Sprint planning, and the overall experiences on lived team feedback, also Information demands by teams.</p> <p>Available under: <a href="http://survey.se.uni-hannover.de/index.php/57192?lang=en">http://survey.se.uni-hannover.de/index.php/57192?lang=en</a></p> <p> </p> <p> </p>
Mangrove diversity loss under sea-level rise triggered by bio-morphodynamic feedbacks and anthropogenic pressures
<p>To whom concerned,</p> <p>This dataset is the supplementary dataset for the publication in <em>Environmental Research Letters</em> entitled '<a href="https://dx.doi.org/10.1088/1748-9326/abc122"><em>Mangrove diversity loss under sea-level rise triggered by bio-morphodynamic feedbacks and anthropogenic pressures</em></a>' authored by Danghan Xie, et al. in 2020. The publication can be freely downloaded here: <a href="https://iopscience.iop.org/article/10.1088/1748-9326/abc122">https://iopscience.iop.org/article/10.1088/1748-9326/abc122</a>. The dataset consists of both model results and corresponding codes that one can easily reproduce figures either in the manuscript or the supplementary document. </p> <p>To use the code, one needs to pre-install the Matlab (R2017a) and changes the pre-set route (in the code) to the directory where the dataset is stored. The figure shapes may vary with the size of the user's monitor so output figures may be either squeezed or extended in unpredictable ways, but the window size of the figure can be adjusted to match the shape and the results will not be affected.</p> <p>The author is appreciated that any potential concerns or questions regarding our research from any party or person, so please contact me through the email: <a href="mailto:d.xie@uu.nl">d.xie@uu.nl</a> or <a href="mailto:xiedanghan@gmail.com">xiedanghan@gmail.com</a>. To know more about my research, you can also follow the <a href="https://www.researchgate.net/profile/Danghan_Xie">ResearchGate</a>.</p> <p>With Kind Regards,</p> <p>Danghan</p> <p>11th of November, 2020</p>
Dataset: Temporal recalibration in response to delayed visual feedback of active versus passive actions
<p>Data set related to the manuscript: </p><p>Kufer, K., Schmitter, C. V, Kircher, T., Straube, B., 2023. Temporal recalibration in response to delayed visual feedback of active versus passive actions: An fMRI study. https://doi.org/10.21203/RS.3.RS-3493865/V1</p><p>Abstract:</p><p>The brain can adapt its expectations about the relative timing of actions and their sensory outcomes in a process known as temporal recalibration. This might occur as the recalibration of timing between the outcome and (1) the motor act (sensorimotor) or (2) tactile/proprioceptive information (inter-sensory). This fMRI recalibration study investigated sensorimotor contributions to temporal recalibration by comparing active and passive conditions. Subjects were repeatedly exposed to delayed (150ms) or undelayed visual stimuli, triggered by active or passive button presses. Recalibration effects were tested in delay detection tasks, including visual and auditory outcomes. We showed that both modalities were affected by visual recalibration. However, an active advantage was observed only in visual conditions. Recalibration was generally associated with the left cerebellum (lobules IV, V and vermis) while action related activation (active > passive) occurred in the right middle/superior frontal gyrus during adaptation and test phases. Recalibration transferred from vision to audition was related to action specic activations in the cingulate cortex, the angular gyrus and left inferior frontal gyrus. Our data provide new insights in sensorimotor contributions to temporal recalibration via the superior frontal gyrus and inter-sensory contributions mediated by the cerebellum.</p>
User Feedback Dataset from the Top 15 Downloaded Mobile Applications
<p>This dataset comprises user feedback data collected from 15 globally acclaimed mobile applications, spanning diverse categories. The included applications are among the most downloaded worldwide, providing a rich and varied source for analysis. <i><strong>The dataset is particularly suitable for Natural Language Processing (NLP) applications</strong></i>, such as text classification and topic modeling.</p><p><strong>List of Included Applications:</strong></p><ul><li>TikTok</li><li>Instagram</li><li>Facebook</li><li>WhatsApp</li><li>Telegram</li><li>Zoom</li><li>Snapchat</li><li>Facebook Messenger</li><li>Capcut</li><li>Spotify</li><li>YouTube</li><li>HBO Max</li><li>Cash App</li><li>Subway Surfers</li><li>Roblox</li><li>Data Columns and Descriptions:</li></ul><p><strong>Data Columns and Descriptions:</strong></p><ul><li>review_id: Unique identifiers for each user feedback/application review.</li><li>content: User-generated feedback/review in text format.</li><li>score: Rating or star given by the user.</li><li>TU_count: Number of likes/thumbs up (TU) received for the review.</li><li>app_id: Unique identifier for each application.</li><li>app_name: Name of the application.</li><li>RC_ver: Version of the app when the review was created (RC).</li></ul><p><strong>Terms of Use:</strong></p><p>This dataset is open access for scientific research and non-commercial purposes. Users are required to acknowledge the authors' work and, in the case of scientific publication, cite the most appropriate reference:</p><p>M. H. Asnawi, A. A. Pravitasari, T. Herawan, and T. Hendrawati, "The Combination of Contextualized Topic Model and MPNet for User Feedback Topic Modeling," in IEEE Access, vol. 11, pp. 130272-130286, 2023, doi: <a href="https://doi.org/10.1109/ACCESS.2023.3332644">10.1109/ACCESS.2023.3332644</a>.</p><blockquote><p>Researchers and analysts are encouraged to explore this dataset for insights into user sentiments, preferences, and trends across these top mobile applications. If you have any questions or need further information, feel free to contact the dataset authors.</p></blockquote>
National Open Access Monitor, Draft Report: Stakeholder Feedback: Response Dataset
<p>This dataset contains the response data from the 'National Open Access Monitor, Draft Report: Stakeholder Feedback' Form which was open from 16th to 30th November 2023 under the National Open Access Monitor Project. A PDF reference copy of the Feedback Form is available here: <a href="https://zenodo.org/doi/10.5281/zenodo.10141988">https://zenodo.org/doi/10.5281/zenodo.10141988</a></p><p>The purpose of the form was to capture stakeholder feedback on the National Open Access Monitor, Ireland Draft Report, for actioning by OpenAIRE in the final National Open Access Monitor Report to be delivered in January 2024. The draft is an interim report, and includes reference to the initial feedback from IReL and the National Open Access Monitor Project Advisory Group.</p><p><strong>To note: </strong></p><ul><li>Responses have been pseudonymised to the level of stakeholder-group e.g. Contributor I, Research Performing Organisation I, where requested by the participant in the participant consent form: <a href="https://doi.org/10.5281/zenodo.7589770">https://doi.org/10.5281/zenodo.7589770</a></li><li>This is the original raw data file, in csv format, as downloaded from the Online Surveys platform and subsequently pseudonymised.</li></ul><p>-----------------------</p><p>The context for the feedback form is detailed in the National Open Access Monitor Project Plan: <a href="https://doi.org/10.5281/zenodo.7331431">https://doi.org/10.5281/zenodo.7331431</a>, the National Open Access Monitor Advisory Group Meeting Minutes, 27th October 2023: <a href="https://zenodo.org/doi/10.5281/zenodo.10105023 ">https://zenodo.org/doi/10.5281/zenodo.10105023 </a>and the OpenAIRE National Open Access Monitor Ireland, Draft Report: <a href="https://zenodo.org/doi/10.5281/zenodo.10136295">https://zenodo.org/doi/10.5281/zenodo.10136295</a></p><p>This project is managed by <a href="http://www.irel.ie/">IReL </a>and has received funding from Ireland's National Open Research Forum under the NORF Open Research Fund. <a href="https://norf.ie/funding/">https://norf.ie/funding/ </a><a href="https://norf.ie/orf-projects-announcement/">https://norf.ie/orf-projects-announcement/</a></p>
Data underpinning "Engineering unsteerable quantum states with active feedback"
<div> <p>We provide the raw data used to produce plots shown in our paper "Engineering unsteerable quantum states with active feedback". The data is structured by: entangled state - number of qubits - target fidelity F*. For each parameter configuration 10 simulation runs were performed.</p> <p> </p> </div> <h2>Abstract</h2> <p>We propose active steering protocols for quantum state preparation in quantum circuits where each ancilla qubit (detector) is connected to a single system qubit, employing a simple coupling selected from a small set of steering operators. The decision is made such that the expected cost function gain in one time step is maximized. We apply these protocols to several many-qubit models. Our results are underlined by three remarkable insights. First, we show that the standard fidelity does not give a useful cost function; instead, successful steering is achieved by including local fidelity terms. Second, although the steering dynamics acts on each system qubit separately, entanglement in the generated target state is introduced, and can be tuned at will, by performing Bell measurements on ancilla qubit pairs after every time step. This implements a weak-measurement variant of entanglement swapping. Third, numerical simulations suggest that the active steering protocol can reach arbitrarily designated target states, including passively unsteerable states such as the N-qubit W state.</p>
Small Group and Survey Datasets: "Fostering Metacognition and Feedback Loops in a Summer Undergraduate Research Program: A Pilot Study"
<p>These datasets accompany the paper "Fostering Metacognition and Feedback Loops in a Summer Undergraduate Research Program: A Pilot Study" by Chad Curtis PhD and Kaytlin Gomez.</p> <p>The first dataset consists of free responses from n=12 students researchers during a Small Group Metacognitive Practice (SGMP) intervention conducted during the 2023 INBRE Summer Undergraduate Research Fellowship (iSURF) at Nevada State University. The files include:</p> <ul> <li><strong>transcription.docx</strong>: Transcriptions of both individual (n=12) and small group (n=4) responses from the SGMP session.</li> <li><strong>codingR1.xlsx</strong>: Codings used for the thematic analysis, as coded by the primary investigator.</li> <li><strong>codingR2.xlsx: </strong>Codings used for the thematic analysis, as coded by the co-author.</li> <li><strong>KrippendorffAlpha.xlsx</strong>: Inter-coder reliability calculations using Krippendorff's alpha.</li> </ul> <p>The survey data was collected from n=11 participants at the end of the summer research program. The files include:</p> <ul> <li><strong>surveyData.csv</strong>: Anonymized responses to survey questions regarding the SGMP intervention.</li> </ul> <p>This study was approved by the Nevada State University Review Board (Protocol #2305-0346). All procedures in the study were conducted in accordance with approved protocols. Written informed consent was obtained from the subjects for their anonymized information to be published with the article.</p>
CO2-dependence of Longwave Clear-sky Feedback is sensitive to Temperature [Dataset]
<p>These data are simulated from PyRads (https://github.com/danielkoll/PyRAD) and are used to plot figures in our study.</p>
Supplementary data for "Effect of Uncertainty in Water Vapor Continuum Absorption on CO2 Forcing, Longwave Feedback, and Climate Sensitivity"
<h3>This dataset is supplementary to the article "Effect of Uncertainty in Water Vapor Continuum Absorption on CO2 Forcing, Longwave Feedback, and Climate Sensitivity".</h3> <h3>spectral_olr.nc</h3> <p>This file contains the spectral outgoing longwave radiation (OLR) calculated using the line-by-line radiative transfer model ARTS and the radiative-convective equilibrium model konrad. It contains spectral OLR for surface temperatures from 270K to 330K for different strengths of the water vapor continuum absorption.</p> <h3>opacity_emission_level.py</h3> <p>This file also contains the spectrally resolved optical depth and the emission level of outgoing longwave radiation for the considered absorption species (H2O lines, H2O continuum, H2O self continuum, H2O foreign continuum, CO2, N2, and O2).</p> <h3>continuum_reference_conditions.nc</h3> <p>This file contains the reference continuum absorption coefficients that were used to calculate the adjustment to the foreign continuum for the single-constraint experiment.</p> <h3>continuum_all_profiles.nc</h3> <p>This file contains the reference continuum absorption coefficients that were used to calculate the adjustment to the foreign continuum for the general-constraint experiment.</p> <h3>modified_continuum_input_files_single_constraint.zip and modified_continuum_input_files_general_constraint.zip</h3> <p>These files contain the modified continuum data files used for the implementation of the MT_CKD continuum model in the line-by-line model ARTS for the single-constraint and general-constraint experiments, respectively.</p> <h3>tau_column.nc and tau_profile.nc</h3> <p>These files contain separately for each absorption species the vertically integrated opacity spectra, and the opacity profiles at two selected wavenumbers.</p> <p> </p>
Supplemental data for "Intramolecular feedback regulation of the LRRK2 Roc G domain by a LRRK2 kinase dependent mechanism" (Gilsbach et al., eLife 2024, doi:10.7554/eLife.91083)
<p><strong>Supportive data for the eLife version of record.</strong></p> <p><strong>(1) Data used for the Michaelis Menten Kinetics.</strong></p> <p><strong>HPLC-based assay.</strong> Steady-state kinetic measurements of LRRK2-mediated GTP hydrolysis were performed as previously described (Ahmadian et al., 1997). Briefly, 0.1 µM of full-length LRRK2 was incubated with different amounts of GTP (0, 25, 75, 150, 250, 500, 1000, 2000, 3000 and 5000 µM) and production of GDP was monitored by reversed phase C18 HPLC. To this end, the samples (10 µl) were directly injected on a reversed-phase C18 column (pre-column: Hypersil Gold, 3µm particle size, 4.6x10mm; main column: Hypersil Gold, 5µm particle size, 4.6x250mm, Thermo Scientific) using an Ultimate 3000 HPLC system (Thermo Scientific, Waltham, MA, USA) in HPLC-buffer containing 50 mM KH<sub>2</sub>PO<sub>4</sub>/K<sub>2</sub>HPO<sub>4</sub> pH 6.0, 10 mM tetrabutylammonium bromide and 10-15% acetonitrile. Subsequently, samples were analyzed using the HPLC integrator (Chromeleon 7.2, Thermo Scientific, Waltham, MA, USA). Initial rates of GDP production were plotted against the GTP concentration using GraFit5 (v.5.0.13, Erithacus Software). The number of experiments is indicated in the graph and data point is the average (±s.e.m.) of indicated repetitions. The Michaelis-Menten equation was fitted to determine K<sub>M</sub> (±s.e.) and k<sub>cat</sub> (±s.e.). Excel sheets used for the calculation of means are provided. No values are reported if the HPLC separation failed (e.g. unstable baseline).</p> <p><strong>Charcoal GTP hydrolysis assay. </strong>The [γ-32P]GTP charcoal assay was performed as previously described (Bollag and McCormick, 1995). Briefly, 0.1 µM full-length LRRK2 or 0.5 µM 6xHIS-MBP-RocCOR was incubated with different GTP concentrations, ranging from 75 µM to 8 mM, in the presence of [γ-<sup>32</sup>P] GTP in GTPase assay buffer (30 mM Tris pH 8, 150 mM NaCl, 10 mM MgCl<sub>2</sub>, 5% (v/v) Glycerol and 3 mM DTT). Samples were taken at different time-points and immediately quenched with 5% activated charcoal in 20 mM phosphoric acid. All non-hydrolyzed GTP and proteins were stripped by the activated charcoal and sedimented by centrifugation. The radioactivity of the isolated inorganic phosphates was then measured by scintillation counting. The initial rates of γ-phosphate release and the Michaelis-Menten kinetics were calculated as described above.</p> <p><strong>(2) Profile plots (Raw data) obtained for the Mass photometry analysis for T1343A vs WT LRRK2.</strong></p> <p>MP was performed as described in (Guaitoli et al., 2023).<strong> </strong>Briefly, the dimer ratio of LRRK2 was determined on a Refeyn Two MP instrument (Refeyn). Prior to the experiment, a standard curve relating particle contrasts to molecular weight was established using a Native molecular weight standard (Invitrogen, 1:200 dilution in HEPES-based elution buffer: 50 mM HEPES [pH 8.0], 150 mM NaCl supplemented with 200 µM desthiobiotin). Prior to mass photometry, the proteins, either WT or T1343A LRRK2, were incubated with 0.5 mM ATP or buffer (control) for 30 min at 30 ℃. The LRRK2 protein was diluted to 2x of the final concentration (end concentrations: 75 nM and 100 nM) in elution buffer. The optical setup was focused in 10 μl elution buffer before adding 10 µl of the adjusted protein sample. Depending on the obtained count numbers, acquisition times were chosen between 20 s to 1 min. The dimer ratio in each measurement was normalize according to the equation. The measurement was perfomed in triplicates.</p> <p><strong>(3) AlphaFold3 model of LRRK2-pT1343 either bound to GDP/Mg or GTP/Mg.</strong></p> <p>Using AlphaFold3 (Abramson et al., 2024), we modeled and compared the GDP vs the GTP-state of phospho-T1343 LRRK2. Interestingly, the AlphaFold3 model suggests, that the phosphate group of the pT1343 residue is orientated inwards thereby substituting the gamma phosphate of the GTP in the GDP-bound state of LRRK2. This finding is in well agreement with MD simulations published recently (Stormer et al., 2023).</p> <p><strong>(4) Western blot RAW files for the cell-based phospho Rab asssay (RAW data for Figure 6 supplement 2/ Supplemental Figure 4 in the preprint version, Gilsbach et al, 2024)</strong></p> <p>Cell-based LRRK2 activity assays were performed as previously described (Singh et al., 2022). Briefly,<strong> </strong>HEK293T cells were cultured in DMEM (supplemented with 10% Fetal Bovine Serum and 0.5% Pen/Strep). For the assay, the cells were seeded onto six-well plates and transfected at a confluency of 50-70% with SF-tagged LRRK2 variants using PEI-based lipofection. After 48 hours cells were lysed in lysis buffer [30 mM Tris-HCl (pH7.4), 150 mM NaCl, 1% NonidentP-40 substitute, complete protease inhibitor cocktail, PhosStop phosphatase inhibitors (Roche)]. Lysates were cleared by centrifugation at 10,000 x g and adjusted to a protein concentration of 1 µg/µl in 1x Laemmli Buffer. Samples were subsequently subjected to SDS PAGE and Western Blot analysis to determine LRRK2 pS935 and Rab10 T73 phosphorylation levels, as described below. Total LRRK2 and Rab10 levels were determined as a reference for normalization. For Western blot analysis, protein samples were separated by SDS–PAGE using NuPAGE 10% Bis-Tris gels (Invitrogen) and transferred onto PVDF membranes (Thermo Fisher). To allow simultaneous probing for LRRK2 on the one hand and Rab10 on the other hand, membranes were cut horizontally at the 140 kDa MW marker band. After blocking non-specific binding sites with 5% non-fat dry milk in TBST (1 h, RT) (25 mM Tris, pH 7.4, 150 mM NaCl, 0.1% Tween-20), membranes were incubated overnight at 4°C with primary antibodies at dilutions specified below. Phospho-specific antibodies were diluted in TBST/ 5% BSA (Roth GmbH). Non-phospho-specific antibodies were diluted in TBST/ 5% non-fat dry milk powder (BioRad). Phospho-Rab10 levels were determined by the site-specific rabbit monoclonal antibody anti-pRAB10(pT73) (Abcam, ab230261) and LRRK2 pS935 was determined by the site-specific rabbit monoclonal antibody UDD2 (Abcam, ab133450), both at a dilution of 1:2,000. Total LRRK2 levels were determined by the in-house rat monoclonal antibody anti-pan-LRRK2 (clone 24D8; 1:10,000) (Carrion et al., 2017). Total Rab10 levels were determined by the rabbit monoclonal antibody anti-RAB10/ERP13424 (Abcam, ab181367) at a dilution of 1:5,000. For detection, goat anti-rat IgG or anti-rabbit IgG HRP-coupled secondary antibodies (Jackson ImmunoResearch) were used at a dilution of 1:15,000 in TBST/ 5% non-fat dry milk powder. Antibody–antigen complexes were visualized using the ECL plus chemiluminescence detection system (GE Healthcare) using the Stella imaging system (Raytest) for detection and quantification.</p> <p><strong>Figure 6 Source Data 1:</strong> <span>Images generated by the Stella system are shown which were used for quantification. The annotation file equals Figure6-figure supplement 2 (Gilsbach et al., eLife 2024, doi:10.7554/eLife.91083). The lines corresponding to </span>LRRK2 pS935, total LRRK2, Rab10 pT73 and total Rab10 were <span>used for the quantification shown in Figure 6.</span></p>
Data used to create figures and tables in the ACP manuscript "Two-way coupled meteorology and air quality models in Asia: a systematic review and meta-analysis of impacts of aerosol feedbacks on meteorology and air quality" by Gao et al. (2022)
<p>This dataset contains the original data that extracted from all collected papers refering applications of two-way coupled models in Asia. It is supplied to the review paper, which titled as "Review on two-way coupled meteorology and air quality models in Asia: impacts of aerosol feedbacks on meteorology and air quality". The dataset includes three excel files (in the format of xlsx) as follows:</p> <p>1. Basic information of literatures (Table S1.xlsx)</p> <p>2. Model performance metrics (Table S2.xlsx)</p> <p>3. Quantitative results of aerosol effects on meteorological and air quality variables (Table S3.xlsx)</p> <p>4. Basic information of model setup for two-way coupled model applications in Asia (Table S4.xlsx)</p> <p>5. Summary of aerosol-induced variations of simulated shortwave and longwave radiative forcing at the bottom and top of atmosphere and in the atmosphere in Asia (Table S5.xlsx)</p> <p>.</p>
Data Analysis files for "Dissipative Quantum Feedback in Measurements Using a Parametrically Coupled Microcavity"
<p>Data Analysis for the paper "Dissipative Quantum Feedback in Measurements Using a Parametrically Coupled Microcavity", which is published in PRX Quantum <strong>3</strong>, 020309 (2022).</p>
Monitoring feedback to authors on the quality of trials evaluating interventions aimed at preventing and treating COVID-19
<p>We aimed to assess transparency of reporting and risk of bias of randomized trials evaluating interventions aimed at preventing and treating COVID-19.</p> <p>This review is part of a larger project: the COVID-NMA project (Boutron 2020a). The COVID-NMA project aims to provide decision-makers with a complete, high-quality and up-to-date synthesis of evidence on interventions for the prevention and treatment of COVID 19. For this purpose, we perform a living mapping of all registered randomized controlled trials and a living evidence synthesis of data from RCTs. We developed a master protocol on the effect of all interventions for the prevention and treatment of COVID-19 (first published on April 8, 2020; an update on May 11, 2020, June 17, 2020, and September 8, 2020) (Boutron 2020b). We set-up a platform (<a href="https://covid-nma.com/">https://covid-nma.com</a>) where all our results are made available and updated weekly.</p>
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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.