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Fig. 3. Principal Component Axes 1 and 2 in Revision of the African cichlid fish genus <em><em>Ctenochromis</em></em> (Teleostei, Cichliformes), including a description of the new genus <em>Shuja</em> from Lake Tanganyika and the new species <em><em>Ctenochromis</em></em> <em>scatebra</em> from northern Tanzania
Fig. 3. Principal Component Axes 1 and 2 of morphological measurements of specimens of Ctenochromis pectoralis Pfeffer, 1893 of the type series from Korogwe, compared with specimens of C. pectoralis from the Ruvu River, and C. scatebra Genner, Ngatunga & Turner sp. nov. from Chemka Springs. The image of C. pectoralis from Korogwe is from the original description (Pfeffer 1893). Collection localities are in parentheses following the species names. In total, Principal Component Axes 1 and 2
[Stimulus Set] Evoking the N400 event-related potential (ERP) component using a publicly available novel set of sentences with semantically incongruent or congruent eggplants (endings)
<p>During speech comprehension, the ongoing context of a sentence is used to predict sentence outcome by limiting subsequent word likelihood. Neurophysiologically, violations of context-dependent predictions result in amplitude modulations of the N400 event-related potential (ERP) component. While N400 is widely used to measure semantic processing and integration, no publicly-available auditory stimulus set is available to standardize approaches across the field. Here, we developed an auditory stimulus set of 442 sentences that utilized the semantic anomaly paradigm, provided cloze probability for all stimuli, and was developed for both children and adults. With 20 neurotypical adults, we validated that this set elicits robust N400's, as well as two additional semantically-related ERP components: the recognition potential (~250 ms) and the late positivity component (~600 ms). This stimulus set (<a href="https://doi.org/10.5061/dryad.9ghx3ffkg">https://doi.org/10.5061/dryad.9ghx3ffkg</a>) and the 20 high-density (128-channel) electrophysiological datasets (<a href="https://doi.org/10.5061/dryad.6wwpzgmx4">https://doi.org/10.5061/dryad.6wwpzgmx4</a>) are made publicly available to promote data sharing and reuse. Future studies that use this stimulus set to investigate sentential semantic comprehension in both control and clinical populations may benefit from the increased comparability and reproducibility within this field of research.</p>
Fig. 3. Principal Component Axes 1 and 2 in Revision of the African cichlid fish genus Ctenochromis (Teleostei, Cichliformes), including a description of the new genus Shuja from Lake Tanganyika and the new species Ctenochromis scatebra from northern Tanzania
Fig. 3. Principal Component Axes 1 and 2 of morphological measurements of specimens of Ctenochromis pectoralis Pfeffer, 1893 of the type series from Korogwe, compared with specimens of C. pectoralis from the Ruvu River, and C. scatebra Genner, Ngatunga & Turner sp. nov. from Chemka Springs. The image of C. pectoralis from Korogwe is from the original description (Pfeffer 1893). Collection localities are in parentheses following the species names. In total, Principal Component Axes 1 and 2 captured 74.5% of the observed morphological variation.
Manufacturing of Hybrid Overmoulded FRP Components: Impact of Process and Environmental Parameters on the Mechanical Properties
<p>A manufacturing parametric study was carried out on a hybrid part, consisting of two organo sheets and injection moulded rib reinforcements, made out of a short fibre reinforced plastic. The effect of the temperature of all components, the pressure profile throughout the injection moulding process as well as the subsequent storage conditions on the mechanical properties was investigated. For this purpose a total of 96 parts was manufactured with different processing parameter combinations. Afterwards all parts were subjected to a cantilever beam test, analysing initial stiffness, deformation work and peak force. Furthermore a variety of potentially influencing factors such as temperature, humidity, order of testing, transfer durations and many more were tracked.</p> <p>Parameter definition:</p> <ul> <li><strong>part_ID</strong>: Unique part identifier.</li> <li><strong>OS-degradation</strong>: Degradation of the organo-sheet(OS) because of thermal decomposition at temperatures above 260°C. Given as percentage of degraded mass.</li> <li><strong>heating-duration</strong>: Time of heating the OS in seconds.</li> <li><strong>heating_temperature-OS</strong>: Surface temperature of the OS at the end of the heating period in °C.</li> <li><strong>heating_field-temp.</strong>: Temperature of the heating field immediately before the heating process begins in °C.</li> <li><strong>stiffness</strong>: Bending stiffness of the structure in N/mm. Determined from the force-deflection-curve between 50 and 150 N.</li> <li><strong>maximum_force</strong>: Highest force value measured during the cantilever beam test in kN.</li> <li><strong>deflection</strong>: Value corresponding to the maximum force in mm.</li> <li><strong>deformation_work</strong>: Absorbed work due to deformation in kN*mm. Determined by integrating the force-deflection-curve from 5 to 30 mm with a lower bound of 0.05 kN on the force.</li> <li><strong>corrected-x</strong>: Value of x corrected by taking into account the water intake.</li> <li><strong>rib_lengths-x</strong>: Length of the rib in mm (1à5<sup>th</sup>, 2à7<sup>th</sup> , 3à10<sup>th</sup>).</li> <li><strong>sprue_width</strong>: Diameter of the sprue in mm.</li> <li><strong>part_length</strong>: Total part length in mm.</li> <li><strong>mould_filled-x</strong>: Flag indicating whether the mould was filled (indicated by 1) at position x (1àbroad end, 2àmid, 3ànarrow end)</li> <li><strong>rib_length</strong>: Mean of the measured rib lengths in mm.</li> <li><strong>mould_filled</strong>: Mean of the flags for fill state.</li> <li><strong>day_of_testing</strong>: Day on which the part was tested (1,2,3).</li> <li><strong>no._of_test_per_day</strong>: Number of test on the respective day.</li> <li><strong>no._of_test_total</strong>: Number of tests in total.</li> <li><strong>delay_of_transfer</strong>: Duration between removal of the OS from the heating field and begin of the transfer in s.</li> <li><strong>transfer_temp_beg.-x</strong>: Surface temperature in °C of the OS at the beginning of the transfer at position x.</li> <li><strong>transfer_temp_end-x</strong>: Surface temperature in °C of the OS at the end of the transfer at position x.</li> <li><strong>tool_surface_temp.-x</strong>: Surface temperature in °C of the tool at position x.</li> <li><strong>fixing-x</strong>: Flag indicating whether the OS was fixed (indicated by 1) at position x (1àbroad end, 2àmid, 3ànarrow end).</li> <li><strong>fixing</strong>: Mean of the flags for fixing.</li> <li><strong>duration-rapid_traverse</strong>: Duration of the rapid motion phase of the press in s.</li> <li><strong>duration-deformation</strong>: Duration of the motion phase of the press deforming the OS in s.</li> <li><strong>press_profile</strong>: ID for translational velocity of the press (0àslow, 1àfast).</li> <li><strong>duration-closing</strong>: Sum of duration-rapid_traverse and duration-deformation.</li> <li><strong>duration-injection</strong>: Duration of the pure injection process in s.</li> <li><strong>duration-holding_pressure</strong>: Time for which the holding pressure was kept up in s.</li> <li><strong>temp.-cylinder-x</strong>: Mean of the temperature over one cycle at one heating band in °C.</li> <li><strong>temp-hot_runner-x</strong>: Mean of the temperature over one cycle at one heating element in the hot runner in °C.</li> <li><strong>temp.-defl._tool-x</strong>: Mean of the temperature over one cycle in the deflection tool at position x.</li> <li><strong>delay-injection</strong>: Time between the press fully closing and the beginning of injection in s.</li> <li><strong>holding_pressure-beg.-x</strong>: Holding pressure at the beginning of holding and position x in bar.</li> <li><strong>holding_pressure-end-x</strong>: Holding pressure at the ned of holding and position x in bar.</li> <li><strong>duration-form_stability-x</strong>: Time in s between maximum melt pressure and form stability, characterised by a pressure below 75 bar.</li> <li><strong>max.-pressure-melt-x</strong>: Maximum pressure during the injection process at position x in bar.</li> <li><strong>transmission-hold._press.-beg.</strong>: Ratio of pressure signal from the sensor at screw and in tool at beginning of holding.</li> <li><strong>transmission-hold._press.-end</strong>: Ratio of pressure signal from the sensor at screw and in tool at end of holding.</li> <li><strong>cooling_rate-hold._press.-x</strong>: Measured cooling rate at position x during the holding phase in °C/s.</li> <li><strong>cooling_rate-cooling-x</strong>: Measured cooling rate at position x during the cooling phase in °C/s.</li> <li><strong>tool-temp.-x</strong>: Measured tool temperature at position x in °C.</li> <li><strong>max.-melt-temp-x</strong>: Highest measured melt temperature at position x in °C.</li> <li><strong>demoulding-temp.-x</strong>: Measured tool temperature at position x at demoulding in °C.</li> <li><strong>storage-standard_atmosphere</strong>: Storage duration at standard atmosphere in h.</li> <li><strong>absoprtion_water-std.atm.</strong>: Water absorption during the storage at standard atmosphere in g.</li> <li><strong>absoprtion_water-climate_chamber.</strong>: Water absorption during the storage in the climate chamber in g.</li> <li><strong>storage-climate_chamber</strong>: Storage duration in climate chamber in h.</li> <li><strong>vert._position-climate_chamber</strong>: Vertical position in the climate chamber in cm.</li> <li><strong>air-temp.</strong>: Air temperature during manufacturing in °C.</li> <li><strong>air-rel._humidity</strong>: Relative humidity during manufacturing in %.</li> <li><strong>no.-production-day</strong>: Consecutive number indicating parts manufactured before the respective part.</li> <li><strong>factor_level</strong>: Factor level in the DOE.</li> <li><strong>prod.-date</strong>: Date of production.</li> <li><strong>prod-time</strong>: Time of production in CEST.</li> <li><strong>batch_number</strong>: ID in which batch the part was manufactured.</li> </ul>
EPIC: Annotated epileptic EEG independent components for artifact reduction
<p>Scalp electroencephalogram is a non-invasive multi-channel biosignal that records the brain’s electrical activity. It is highly susceptible to noise that might overshadow important data. Independent component analysis is one of the most used artifact removal methods. Independent component analysis separates data into different components, although it can not automatically reject the noisy ones. Therefore, experts are needed to decide which components must be removed before reconstructing the data. To automate this method, researchers have developed classifiers to identify noisy components. However, to build these classifiers, they need annotated data. Manually classifying independent components is a time-consuming task. Furthermore, few labeled data are publicly available. This dataset is composed of a source of annotated electroencephalogram independent components acquired from patients with epilepsy (EPIC Dataset). This dataset contains 77,426 independent components obtained from approximately 613 hours of electroencephalogram, visually inspected by two experts, which was already successfully utilized to develop independent component classifiers.</p>
Decomposing niche components reveals simultaneous effects of opposite deterministic processes structuring alpine small mammal assembly
<p><span>Our knowledge of community assembly dynamics under multiple stressors is limited because of opposite niche-based processes, i.e., limiting similarity and habitat filtering could simultaneously occur, masking the overall patterns. Alpine biomes provide the ideal systems to explore the influences of co-occurrence processes as these communities usually face multiple stresses such as resources limitation and habitat constraints. However, the assembly processes of mammals in alpine areas have hardly been exclusively studied. Here, we</span> <span>aimed to address how different processes structured small mammal communities at the tree line transition zone, which represents one of the most distinct vegetation boundaries separating alpine from montane habitats. We compiled a regional dataset including species list, phylogeny, and functional traits from field collections across 18 mountains of southwest China and complemented them with published data sources. The traits were decomposed into different niche components to determine the respective effects of specific stressors. Phylogenetic and functional diversity indices representing evolutionary history, trait space, and pairwise species distance were calculated and compared with null expectations. Linear mixed-effect models were constructed to assess the increasing or decreasing tendencies of diversity values against increasing elevation. The results showed that phylogenetic and functional richness were strongly correlated with species richness, unlike the distance-based indices which were uncorrelated with species richness. There was no evidence found to support non-random phylogenetic or overall trait patterns. However, the resource acquisition niche tended to be more overdispersed (positive slopes), while the habitat affinity niche tended to be more clustered (negative slopes) as habitats became less productive and less vegetated. We conclude that limiting similarity and habitat filtering simultaneously structure small mammal communities in alpine areas. Altogether, the present study provides vital insights into the complexity of co-occurring assembly processes by niche decomposition, and highlights the importance of considering different diversity dimensions when assessing community structure.</span></p>
Figure 5. Principal component plot for the 4 in Integrative taxonomy reveals cryptic diversity in North American Lasius ants, and an overlooked introduced species
Figure 5. Principal component plot for the 4 most diagnostic morphometric variables (GUHL, dCLAN, MP6 and nSt) to distinguish individual specimens of Lasius ponderosae sp. nov. (n = 39) from those belonging to morphologically similar-looking Palearctic species (n = 49). For a definition of variables see Supplementary Table S3 and Fig. S1.
A wildfire risk index and its components and subcomponents - NUTS2 Centro, Portugal
<p>The dataset, presented as a MS Excel file and an ArcGIS Shapefile, includes a wildfire risk index and its components and subcomponents, as well as the results of a clustering process based on the main components of the wildfire risk index. The analysis units are the civil parishes comprised within the NUTS2 Centro territorial unit in central Portugal, identified by name in the column <em>ParishName </em>of the Excel file.</p> <p>All variables are identified in the Excel file Data, and all are included as attributes to the parish polygons in the shapefile.</p>
REMODEL. WP6. Sensory Systems and Mechatronic Tools. T6-2. Development and optimization of sensory system components. Data related to a paper published in MDPI Machines 2021
<p>The datasets contain the data related to the experiment presented in the publication:</p> <p>A. Cirillo, G. Laudante, and S. Pirozzi, “Proximity sensor for thin wire recognition and manipulation,” Machines, vol. 9, no. 9, art. 188, Sept. 2021. (DOI: 10.3390/machines9090188)</p>
REMODEL. WP6. Sensory Systems and Mechatronic Tools. T6-2. Development and optimization of sensory system components. Data related to IMM2021 publication
<p>The datasets contain data related to the experiments presented in the publication:</p> <p>Costanzo, M., Pirozzi, S., “Optical Force/Tactile Sensors for Robotic Applications” (2021) IEEE Instrumentation and Measurement Magazine, 24 (5), art. no. 9491003, pp. 28-35. DOI: 10.1109/MIM.2021.9491003</p>
Evoking the N400 Event-Related Potential (ERP) component using a publicly available novel set of sentences with semantically incongruent or congruent eggplants (endings)
<p class="MsoNoSpacing"><span>During speech comprehension, the ongoing context of a sentence is used to predict sentence outcome by limiting subsequent word likelihood. Neurophysiologically, violations of context-dependent predictions result in amplitude modulations of the N400 event-related potential (ERP) component. While N400 is widely used to measure semantic processing and integration, </span><span>no publicly-available auditory stimulus set is available to standardize approaches across the field. Here, we developed an auditory stimulus set of 442 sentences that utilized the semantic anomaly paradigm, provided cloze probability for all stimuli, and was developed for both children and adults. With 20 neurotypical adults, we validated that this set elicits robust N400's, as well as two additional semantically-related ERP components: the recognition potential (~250 ms) and the late positivity component (~600 ms). This stimulus set (<a href="https://doi.org/10.5061/dryad.9ghx3ffkg">https://doi.org/10.5061/dryad.9ghx3ffkg</a>) and the 20 high-density (128-channel) electrophysiological datasets (<a href="https://doi.org/10.5061/dryad.6wwpzgmx4">https://doi.org/10.5061/dryad.6wwpzgmx4</a>) </span><span>are made publicly available to promote data sharing and reuse. Future studies that use this stimulus set to investigate sentential semantic comprehension in both control and clinical populations may benefit from the increased comparability and reproducibility within this field of research.</span></p>
Cytoplasmic components of the machinery mediating telomere-led rapid chromosome movements in mouse meiosis
<p>Telomere-led rapid chromosome movements (RPMs) are a prominent characteristic of chromosome dynamics during meiosis. Although of crucial importance in maintaining germ cell integrity, the extranuclear portion of the machinery supporting RPMs in mammals is poorly understood. Using an unbiased proteomic approach to identify motor proteins associated to microtubules in mouse meiotic cells, complemented with co-immunoprecipitation confirmation, we uncovered kinesins as candidate of the machinery mediating RPMs in mouse spermatocytes. Further biochemical, microscopy, and functional analysis shows that KIF5B and KIF2B interact with KASH5 and act as motor proteins mediating the LINC complex-microtubule interactions. Our results show that member of the kinesin family of molecular motors act as novel critical modules of the machinery promoting complex dynamic chromosomes in mammals.</p>
Figure 1. The component elements and technological dimension of private life-Educational Research on the Technological Dimension of Private Life
<p>At the level of each component element there are ten principal/main dimensions:<br> objective, biological, psycho-social, esthetic, religious, technological, economical, historical,<br> cultural - political, juridical. The analysis of all the aspects presented above offers a holistic<br> view on the concept of private life, a view that allows a complete representation of all the<br> components. We plot the dynamic structure of the components of privacy by means of two<br> axes, in which the vertical scale is characteristic and essential elements horizontally (Figure<br> 1).</p>
Figure 4. The graphic representation of the means for the elements component of the technological dimension variable according to the group variable (teachers versus students)
<p>The second hypothesis is confirmed. There are differences between teachers’ and<br> students’ representations on the technological dimension of private life. Test t results show<br> that teachers have a more positive perception than students for the next component of<br> technological dimensions: Personal Self [t(2344) = 4,446, p <0,05], Adaptive Self [t(2344) =<br> 2,757, p <0,05], Primary groups [t(2344) = 3,192, p <0,005] (Table 3, Figure 4).</p>
BRAIN Journal-Brain-Like Artificial Intelligence for Automation-Figure 3. Basic "Components" of Artificial and Biological (Brain-Controlled) Automation Systems
<p>Although basing on different concepts concerning their details, artificial and biological (brain-controlled) automation systems show common points concerning their principal components (see Figure 3).</p>
State of Practice and Challenges of Issue Management for Component-based and Service-Oriented Systems: An Empirical Study
<p>Modern software systems often consist of independently developed components, e.g., libraries or (micro-)services, that can be combined to form a larger architecture. Many of these components are developed externally, i.e., in other projects by other teams, which is particularly the case in service-oriented architectures. Even though the components are independently developed, bugs may arise that propagate along the call chains, which sometimes negatively affect the calling components. However, as such components are typically managed in separate issue management systems (IMS), identifying that a downstream component is affected by an upstream component's issues is complex and time-consuming. Even though some scientific works and IMS forums discuss how to manage such cross-component issues, there is no systematic study on the state of practice and the challenges of issue management when different components are affected. Therefore, this study aims to determine which types of components are usually included in modern software projects, how developers identify and manage issue propagation between components, and how often they face such propagations. To get these insights, we conducted an empirical study through a questionnaire with 64 industry experts and open-source contributors and interviewed seven of them. Our key takeaways help researchers and software engineers to understand possible impacts and to improve cross-component issue management. We identified, for example, that related issues currently are non-semantically linked via URLs in issue comments.</p>
Data for publication: A pipeline for in-depth analysis of DNA virus populations by profiling the low abundant virus variants and partial genomic components
<p>Raw and processed sequence data from Oxford Nanopore and BGI short read sequencing platforms used in the publication: "A pipeline for in-depth analysis of DNA virus populations by profiling the low abundant virus variants and partial genomic components".</p>
Differential impacts of land use change on multiple components of common Milkweed (Asclepias syriaca) pollination success
<p>Land-use change is one the greatest threats to biodiversity and is projected to increase in magnitude in the coming years, stressing the importance of better understanding how land-use change may affect vital ecosystem services, such as pollination. Past studies on the impact of land-use change have largely focused on only one aspect of the pollination process (e.g. pollinator composition, pollinator visitation, pollen transfer), potentially misrepresenting the full complexity of land-use effects on pollination services. Evaluating the impacts across multiple components of the pollination process can also help pinpoint the underlying mechanisms driving land-use change effects. This study evaluates how land-use change affects multiple aspects of the pollination process in common milkweed populations, including pollinator community composition, pollinator visitation rate, pollen removal, and pollen deposition. Overall, land-use change altered floral visitor composition, with small bees having a larger presence in developed areas. Insect visitation rate and pollen removal were also higher in more developed areas, perhaps suggesting a positive impact of land-use change. However, pollen deposition did not differ between developed and undeveloped sites. Our findings highlight the complexity evaluating land-use change effects on pollination, as these likely depend on the specific aspect of pollination evaluated and on the of the intensity of disturbance. Our study stresses the importance of evaluating multiple components of the pollination process in order to fully understand overall effects and mechanisms underlying land-use change effects on this vital ecosystem service.</p>
Datasets for the Results of Scratch Tests of Green Wood and Results of Scratch Tests of Timber Components (D2.1) and Output Database for Selected Wood Parts and Timber Components: Moisture Contents and Temperatures, Moisture Induced Strains and Stresses and Crack Risk (D2.2) of 5G-TIMBER EU Project
<p>7 June 2024: added D2.2_data_statistics.zip and D2.2_analysis_results.zip, which are the datasets for D2.2 "<span>Output Database for Selected Wood Parts and Timber Components: Moisture Contents and Temperatures, Moisture Induced Strains and Stresses and Crack Risk" of the Horizon Europe Innovation Action project "5G-TIMBER: Secure 5G-Enabled Twin Transition for Europe's TIMBER Industry Sector" (project reference: 101058505).</span></p> <p>D2.2 presents the Hygro-Thermo-Mechanical (HTM) models and the finite element (FE) analyses of selected wooden components that use the material properties of wood presented in deliverable D2.1 "Input database for selected wood parts and timber components: material properties, representative environmental conditions,<br>and loads" (see below). </p> <p>------</p> <p>Figures_22_23_24_25.xlsx : Results of Scratch Tests of Green Wood</p> <p>corrected_Figures_26_27_28_29_30.xlsx : Results of results of Scratch Tests of Timber Components (new version, uploaded on 26 October 2023)</p> <p>This dataset consists of 2 Excel files that correspond to the scratch test results reported in the deliverable D2.1 "Input Database for Selected Wood Parts and Timber Components: Material Properties, Representative Environmental Conditions and Loads" of the Horizon Europe Innovation Action project "5G-TIMBER: Secure 5G-Enabled Twin Transition for Europe's TIMBER Industry Sector" (project reference: 101058505).</p> <p>The purpose of D2.1, to which this dataset is related, is to present the input data needed for the Hygro-Thermo-Mechanical (HTM) models and the related finite element (FE) analyses planned for a follow-up deliverable, i.e., the D2.2. (Output Database for Selected Wood Parts and Timber Components: Moisture Contents and Temperatures, Moisture Induced Strains And Stresses And Crack Risk). The data include the material properties for green wood and selected wooden components, as well as the plans to collect environmental conditions and loads to be considered in the analyses for prediction of the crack risk of timber components under moisture variations. In additions, new results of scratch tests of wood and wooden components, supported by computed tomography (CT) investigations, are collected to define a model for shear failure risk to be added to the HTM computational models.</p> <p>In D2.1, scratch tests carried out at VTT are described and their results are collected to provide information about the moisture effects of wood logs during cutting operations in sawmills, as well as on relevant fracture and shear properties for wooden components in sawing centres before using them to produce wooden elements of modular buildings in the production. The scratch tests are supported by CT tomography investigations and these results are also reported in the deliverable.</p> <p>D2.1 is available here: <a title="Deliverable D2.1 "Input Database for Selected Wood Parts and Timber Components: Material Properties, Representative Environmental Conditions and Loads" " href="../records/10577505" target="_blank" rel="noopener">https://zenodo.org/records/10577505</a> </p>
Self-reported and accelerometry measures of sleep components in adolescents living in Pacific Island countries and territories: Exploring the role of sociocultural background
<p>Data from self-report questionnaires and accelerometer extraction on sleep components (onset sleep time, wake-up time and sleep duration on weekdays and weekend).</p> <p>Participant characteristics: 10 to 16 years old students.</p> <p>Number of participants: 182.</p> <p>Year of the study: 2018 - 2019.</p> <p>Place of the study: New Caledonia.</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.