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42 results for “Whiskers”
Data set for "Optogenetic stimulation of cortex to map evoked whisker movements in awake head-restrained mice"
<p>Data set for: Auffret M, Ravano VL, Rossi GMC, Hankov N, Petersen MFA, Petersen CCH (2017) Optogenetic stimulation of cortex to map evoked whisker movements in awake head-restrained mice. Neuroscience, http://dx.doi.org/10.1016/j.neuroscience.2017.04.004</p> <p>There are 9 files in this data upload:</p> <ol> <li>'2017_Auffret_Neuroscience.pdf' - this is a pdf version of the online publication.</li> <li>'Auffret_data.mat' - this is a Matlab data structure, which contains all the data for the publication.</li> <li>'Auffret_data.npy' - this is a Python data structure, which contains all the data for the publication. The Python data was generated from 'Auffret_data.mat' by 'DataViewer.py'.</li> <li>'Auffret_data.xlsx' - this is an Excel file, which contains all the data for the publication. This Excel file was generated from 'Auffret_data.mat'.</li> <li>'DataViewer.fig' - this is a Matlab Figure file, which is the GUI layout for 'DataViewer.m'.</li> <li>'DataViewer.m' - this is a Matlab Code, which displays the data contained in 'Auffret_data.mat'.</li> <li>'DataViewer.py' - this is a Python Code, which generates 'Auffret_data.npy' from 'Auffret_data.mat', and displays an example trial.</li> <li>'FigureViewer.fig' - this is a Matlab Figure file, which is the GUI layout for 'FigureViewer.m'.</li> <li>'FigureViewer.m' - this is a Matlab Code, which analyses the data in 'Auffret_data.mat', and displays the results in the same way as the published figures (Auffret et al., 2017).</li> </ol>
Data set for "Distinct contributions of whisker sensory cortex and tongue-jaw motor cortex in a goal-directed sensorimotor transformation"
<p>Data set for: Mayrhofer JM, El-Boustani S, Foustoukos G, Auffret M, Tamura K, Petersen CCH (2019) Distinct contributions of whisker sensory cortex and tongue-jaw motor cortex in a goal-directed sensorimotor transformation. Neuron https://doi.org/10.1016/j.neuron.2019.07.008</p> <p>There are 2 files in this upload:</p> <p>1. The file named "2019_Mayrhofer_Neuron.pdf" is the Open Access pdf file of the manuscript published in Neuron.</p> <p>2. The file named "Mayrhofer_data_code.zip" (~20 GB) is a zipped version of a folder "Mayrhofer_data_code" (~57 GB), which contains the data analysed in the study along with the Matlab code used to generate the published figures. The analysis code is in a subfolder named "MatlabCode", and the specific code for generating each figure panel is in a sub-subfolder named "Figures_tjM1_paper". When running the code, you need to set the Matlab file path to be "Mayrhofer_data_code". In addition, you should add the folder "Mayrhofer_data_code" with subfolders in Matlab "Set Path". The figures will be saved in a subfolder named "Figures". Some parts of the code rely upon previous results, and need to be executed sequentially in the order of the figure panels in the journal publication.</p>
Data set for "Cell class-specific long-range axonal projections of neurons in mouse whisker-related somatosensory cortices"
<p>Data set for: Liu Y, Bech P, Tamura K, Délez LT, Crochet S, Petersen CCH (2024) Cell class-specific long-range axonal projections of neurons in mouse whisker-related somatosensory cortices. eLife 13: RP97602. https://doi.org/10.7554/eLife.97602</p> <p>There are 3 files in this upload:</p> <p>1. The file named "2024_Liu_eLife.pdf" is the Open Access pdf of the online publication in eLife.</p> <p>2. The file named "Liu_anatomy_data_code.zip" (~35 GB) is a zipped version of a folder "Liu_anatomy_data_code" (~111 GB), which contains the anatomical data analysed in the study along with the Python codes used to generate the published figures 1-7 and their associated figure supplements. </p> <p>3. The file named "Liu_function_data_code.zip" (~10 GB) is a zipped version of a folder "Liu_function_data_code" (~35 GB), which contains the functional data analysed in the study along with the Python codes used to generate the published figure 8 and its associated figure supplement. </p> <p>After unzipping, the Python codes should run as a Jupyter notebook (anatomy .ipynb code) or Python code (function .py code) in Anaconda.</p>
Neural coding in barrel cortex during whisker-guided locomotion
<p>Data accompanying publication at <a href="https://doi.org/10.7554/eLife.12559">https://doi.org/10.7554/eLife.12559</a> and code at <a href="https://doi.org/10.5281/zenodo.2949955">https://doi.org/10.5281/zenodo.2949955</a>. For example usage see the notebooks in the repository.</p> <p>The data is organized according to animal id, `00` - `18`.</p> <p>Animals `00` - `12` are electrophysiology data. Each electrophysiology animal data contains the timestamps of the extracted spikes and various processed tabular data. For usage see the `ephys-traces.ipynb` and `ephys-table.ipynb`. Raw voltage traces are not provided.</p> <p>Animals `13` - `18` are imaging data. Each imaging animal data contains timeseries of extracted calcium transients, pixel-wise regression maps of the field of view and various processed tabular data. For usage see the `imaging-raw.ipynb`, `imaging-traces.ipynb`, and `imaging-traces.ipynb`. Raw imaging movies are not provided.</p>
Data set for "Dopamine dynamics in nucleus accumbens across reward-based learning of goal-directed whisker-to-lick sensorimotor transformations in mice"
<p>Data set for: Huang J, Crochet S, Sandi C, Petersen CCH (2024) Dopamine dynamics in nucleus accumbens across reward-based learning of goal-directed whisker-to-lick sensorimotor transformations in mice. Heliyon 10: e37831. https://doi.org/10.1016/j.heliyon.2024.e37831<br><br></p> <p>There are 2 files in this upload:</p> <p>1. The file named "2024_Huang_Heliyon.pdf" is the Open Access pdf of the online publication in Heliyon.</p> <p>2. The file named "Huang_data_code.zip" (~6 GB) is a zipped version of a folder "Huang_data_code" (~6 GB), which contains the data analysed in the study along with the Matlab codes used to generate the published figures. To access the data and codes, first unzip the file. You need to install the Matlab 'Signal Processing' and 'Curve Fitting' Toolboxes. In Matlab, add the path of the folder "Huang_data_code" and all subfolders. The main folder unzips into three subfolders: i) "Huang_dLight_data_code", which contains the dLight data; ii) "Huang_muscimol_data_code", which contains the behavioral data for muscimol inactivation experiments; and iii) "Huang_singletrial_example", which contains the data for the single trial example data shown in Figure 1C (note for this to run you first need to load the data file "JH056_190308_WD.mat"). In the folder "Huang_dLight_data_code", you can also find a "DataViewer" to visualise the data trial-by-trial, which you can run by executing "DataViewer.mlapp" directly from the subfolder "Huang_dLight_data_code" after loading the data "Huang_database.mat".</p>
Data set for "Membrane potential dynamics of excitatory and inhibitory neurons in mouse barrel cortex during active whisker sensing"
<p>Data set for: Kiritani T, Pala A, Gasselin C, Crochet S, Petersen CCH (2023) Membrane potential dynamics of excitatory and inhibitory neurons in mouse barrel cortex during active whisker sensing. PLOS ONE 18: e0287174. doi: 10.1371/journal.pone.0287174</p> <p>There are 2 files in this upload:</p> <p>1. The file named "2023_Kiritani_PLOSONE.pdf" is the Open Access pdf of the online publication in PLOS ONE.</p> <p>2. The file named "Kiritani_data_code.zip" (~5 GB) is a zipped version of a folder "Kiritani_data_code" (~5 GB), which contains the data analysed in the study along with the Matlab codes used to generate the published figures. To access the data and codes, first unzip the file. You need to install the Matlab 'Signal Processing' and 'Curve Fitting' Toolboxes. In Matlab, add the path of the folder 'Kiritani_data_code' and all subfolders. Directly from this folder, you should first run the codes in the folder 'Data_Analysis_Codes', sequentially executing 'Analysis_1.m' through to 'Analysis_9.m'. Note, execution of 'Analysis_9.m' can take a long time (~1 hour on a good desktop PC). You can then run the codes in the folder 'Figure_Plotting_Codes' to generate the figures published in the journal article. In the folder 'Data', you can also find a DataViewer to visualise the data sets, which you can run by executing 'DataViewer.m' directly from the subfolder ‘Data’.</p> <p> </p>
Data set for "Anatomically and functionally distinct thalamocortical inputs to primary and secondary mouse whisker somatosensory cortices"
<p>Data set for: El-Boustani S, Sermet BS, Foustoukos G, Oram TB, Yizhar O, Petersen CCH (2020) Anatomically and functionally distinct thalamocortical inputs to primary and secondary mouse whisker somatosensory cortices. Nature Communications 11: 3342. doi: 10.1038/s41467-020-17087-7</p> <p>There are 4 files in this upload:</p> <p>1. The file named "2020_El-Boustani_NCOMMS.pdf" is the Open Access pdf file of the manuscript published in Nature Communications.</p> <p>2. The file named "2020_El-Boustani_NCOMMS_SupMovie1.avi" is Supplementary Movie 1 in .avi format, accompanying the Nature Communications publication.</p> <p>2. The file named "2020_El-Boustani_NCOMMS_SupMovie2.avi" is Supplementary Movie 2 in .avi format, accompanying the Nature Communications publication.</p> <p>4. The file named "El-Boustani_data_code.zip" (~36 GB) is a zipped version of a folder "El-Boustani_data_code" (~45 GB), which contains the data analysed in the study along with the Matlab code used to generate the published figures. To access the data and the code, first unzip the file. In the main folder, data for all experiments are stored within folders starting by the prefix “SB”. The code for generating population data and plotting figures from the paper are in the folder “Matlab_code”. In this folder, several Matlab scripts are named after the panels or figures they will plot such as “Plot_Fig3d_Axon_GCaMP6s_traces_example.m”. After opening each file, executing the script will automatically plot the panels and name them accordingly. In some files, the type of data to plot should be specified at the very beginning of the script: “VPM” for VPM data, “POMf” for POm-FO data and “Layer1” for POm-HO data in layer 1. For figure 2, the code is located in a dedicated folder where a Matlab file “Plot_Fig2d_g_Populatin_Plot_POm_FO_HO.m” is used to generate the figures. Finally, other Matlab files are included that are used to create population .mat files or for additional analysis related to the manuscript.</p>
Data set for "Projection-specific activity of layer 2/3 neurons imaged in mouse primary somatosensory barrel cortex during a whisker detection task"
<p>Data set for: Vavladeli A, Daigle T, Zeng H, Crochet S, Petersen CCH (2020) Projection-specific activity of layer 2/3 neurons imaged in mouse primary somatosensory barrel cortex during a whisker detection task. FUNCTION 1: zqaa008. doi: 10.1093/function/zqaa008</p> <p>There are 2 files in this upload:</p> <p>1. The file named "2020_Vavladeli_FUNCTION.pdf" is the Open Access pdf file of the manuscript published in FUNCTION.</p> <p>2. The file named "Vavladeli_data_code.zip" (~2 GB) is a zipped version of a folder named "Vavladeli_data_code" (~2 GB), which contains the data analysed in the study along with the Matlab code used to generate the published figures. When unzipped, the folder contains 8 Matlab '.m' files with analysis code and two '.mat' data files. In order to run the analysis of the data set, you need to execute the '.m' file with the corresponding figure name.</p>
Data from: Whiskers provide time-series of toxic and essential trace elements, Se:Hg molar ratios, and stable isotope values of an apex Antarctic predator, the leopard seal
<p>In an era of rapid environmental change and increasing human presence, researchers need efficient tools for tracking contaminants to monitor the health of Antarctic flora and fauna. Here, we examined the utility of leopard seal whiskers as a biomonitoring tool that reconstructs time-series of significant ecological and physiological biomarkers. Leopard seals (<em>Hydrurga leptonyx</em>) are a sentinel species in the Western Antarctic Peninsula due to their apex predator status and top-down effects on several Antarctic species. However, there are few data on their contaminant loads. We analyzed leopard seal whiskers (n = 18 individuals, n = 981 segments) collected during 2018–2019 field seasons to acquire longitudinal profiles of non-essential (Hg, Pb, and Cd) and essential (Se, Cu, and Zn) trace elements, stable isotope (ẟ<sub>15</sub>N and ẟ<sub>13</sub>C) values and to assess Hg risk with Se:Hg molar ratios. Whiskers provided between 46 and 286 cumulative days of growth with a mean ~125 days per whisker (n = 18). Adult whiskers showed variability in non-essential trace elements over time that could partly be explained by changes in diet. Whisker Hg levels were insufficient (<20 ppm) to consider most seals being at "high" risk for Hg toxicity. Nevertheless, maximum Hg concentrations observed in this study were greater than that of leopard seal hair measured two decades ago. However, variation in the Se:Hg molar ratios over time suggest that Se may detoxify Hg burden in leopard seals. Overall, we provide evidence that the analysis of leopard seal whiskers allows for the reconstruction of time-series ecological and physiological data and can be valuable for opportunistically monitoring the health of the leopard seal population and their Antarctic ecosystem during climate change.</p>
Whisker vibrations measured with acoustic methods
<p>Original voltage traces measured with a mouse whisker of 21.5mm long that is consecutively trimmed. </p> <p>Data are used for all figures in the manuscript</p>
Stable carbon and nitrogen isotope analysis data for sequentially sampled whiskers of caracals (Caracal caracal) on the Cape Peninsula, South Africa
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Extensive variation in feather ornaments of Whiskered Auklets in the Aleutian Islands reflects age, sex, condition, and geography
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Data from: Whiskers provide time-series of toxic and essential trace elements, Se:Hg molar ratios, and stable isotope values of an apex Antarctic predator, the leopard seal
Open the record for dataset details and reuse information.
FIG. 5 in A new species of South-East Asian Myotis (Chiroptera: Vespertilionidae), with comments on Vietnamese 'whiskered bats'
FIG. 5. Camera lucida tracings of the skull of M. annatessae sp. nov. (paratype ZMMU S-165043). Scale bar = 5 mm
FIG. 4 in A new species of South-East Asian Myotis (Chiroptera: Vespertilionidae), with comments on Vietnamese 'whiskered bats'
FIG. 4. Neighbour-joining tree of COI sequences of 25 species of Eurasian Myotis included in comparative molecular analysis (see Appendix for list of sequences used). Only bootstrap supports over 70% are shown
FIG. 2. Bivariate scatterplot for the 1 in A new species of South-East Asian Myotis (Chiroptera: Vespertilionidae), with comments on Vietnamese 'whiskered bats'
FIG. 2. Bivariate scatterplot for the 1st and 2nd Principal Components, calculated for 20 cranial and dental measurements of 100 specimens of small Asian mouse-eared bats. For factor loadings and eigenvalues, see Table 1
FIG. 3 in A new species of South-East Asian Myotis (Chiroptera: Vespertilionidae), with comments on Vietnamese 'whiskered bats'
FIG. 3. Camera lucida traces of penial bones (bacula) in five smaller species of the Asiatic Myotis: a, b — M. annatessae sp. nov., Vietnam, ZMMU S-164989 (dorsal, ventral, right lateral views), ZMMU S-165043 (dorsal, ventro-lateral, right lateral views); c — M. ater, Vietnam, ZMMU S-172604 (dorsal, right lateral views); d — M. siligorensis, Vietnam, ZMMU S-167188 (ventral, left lateral views); e, f, g — M. muricola, Vietnam, ZMMU S-172616 (dorsal, right lateral views), ZMMU S-173413 (dorsal, ventrolateral, left lateral views), ZMMU S-172626 (dorsal, right lateral views); h — M. muricola, Nepal, ZMMU S-164491 (dorsal, right ventro-lateral views)
On following pages: 452. Long-toed Myotis (Myotis secundus); 453. Bornean Whiskered Myotis (Myotis borneoensis); 454. Malaysian Whiskered Myotis (Myotis federatus): 455. Indochinese Myotis (Myotis indochinensis); 456. Peyton's Myotis (Myotis peyton); 457. Burmese Whiskered Myotis (Myotis montivagus); 458. Long-fingered Myotis (Myotis capaccinii); 459. Chinese Water Myotis (Myotis laniger); 460. Csorba's Myotis (Myotis csorbal); 461. Kashmir Cave Myotis (Myotis longipes); 462. Annamit Myotis (Myotis annamiticus); 463. Phan Luong's Myotis (Myotis phanluongi); 464. Himalayan Whiskered Myotis (Myotis siligorensis); 465. Chestnut Myotis (Myotis badius); 466. Ridley's Myotis (Myotis ridley); 467. Thick-thumbed Myotis (Myotis rosseti); 468. Horsfield's Myotis (Myotis horsfieldi); 469. Pallid Large-footed Myotis (Myotis macrotarsus); 470. Stalker's Myotis (Myotis stalkeri); 471. Gray Large-footed Myotis (Myotis adversus); 472. Maluku Myotis (Myotis moluccarum); 473. Southern Myotis (Myotis macropus); 474. Lesser Large-footed Myotis (Myotis hasselti). in Vespertilionidae
On following pages: 452. Long-toed Myotis (Myotis secundus); 453. Bornean Whiskered Myotis (Myotis borneoensis); 454. Malaysian Whiskered Myotis (Myotis federatus): 455. Indochinese Myotis (Myotis indochinensis); 456. Peyton's Myotis (Myotis peyton); 457. Burmese Whiskered Myotis (Myotis montivagus); 458. Long-fingered Myotis (Myotis capaccinii); 459. Chinese Water Myotis (Myotis laniger); 460. Csorba's Myotis (Myotis csorbal); 461. Kashmir Cave Myotis (Myotis longipes); 462. Annamit Myotis (Myotis annamiticus); 463. Phan Luong's Myotis (Myotis phanluongi); 464. Himalayan Whiskered Myotis (Myotis siligorensis); 465. Chestnut Myotis (Myotis badius); 466. Ridley's Myotis (Myotis ridley); 467. Thick-thumbed Myotis (Myotis rosseti); 468. Horsfield's Myotis (Myotis horsfieldi); 469. Pallid Large-footed Myotis (Myotis macrotarsus); 470. Stalker's Myotis (Myotis stalkeri); 471. Gray Large-footed Myotis (Myotis adversus); 472. Maluku Myotis (Myotis moluccarum); 473. Southern Myotis (Myotis macropus); 474. Lesser Large-footed Myotis (Myotis hasselti).
On following pages: 424. Black-and-orange Myotis (Myotis formosus); 425. Geoffroy's Myotis (Myotis emarginatus); 426. Temminck's Myotis (Myotis tricolon; 427. Welwitsch''s Myotis (Myotis welwitschii); 428. Reddish-black Myotis (Myotis rufonigen; 429. Scott's Myotis (Myotis scott); 430. Morris's Myotis (Myotis morrisi); 431. Bocage's Myotis (Myotis bocagil); 432. Malagasy Myotis (Myotis goudoti); 433. Anjouan Myotis (Myotis anjouanensis); 434. Kock's Myotis (Myotis dieteri); 435. Alcathoe Whiskered Myotis (Myotis alcathoe); 436. Hyrcanian Myotis (Myotis hyrcanicus); 437. Pond Myotis (Myotis dasycneme); 438. lkonnikov's Myotis (Myotis ikonnikovi); 439. Sichuan Myotis (Myotis altarium); 440. Common Whiskered Myotis (Myotis mystacinus); 441. David's Myotis (Myotis davidii); 442. Valley Myotis (Myotis ancricola); 443. Anna Tess's Myotis (Myotis annatessae);, 444. Gomantong Myotis (Myotis gomantongensis); 445. Peters's Myotis (Myotis ater); 446. Nepalese Whiskered Myotis (Myotis muricola); 447. Brown's Whiskered Myotis (Myotis brown); 448. Insular Myotis (Myotis insularum). in Vespertilionidae
On following pages: 424. Black-and-orange Myotis (Myotis formosus); 425. Geoffroy's Myotis (Myotis emarginatus); 426. Temminck's Myotis (Myotis tricolon; 427. Welwitsch''s Myotis (Myotis welwitschii); 428. Reddish-black Myotis (Myotis rufonigen; 429. Scott's Myotis (Myotis scott); 430. Morris's Myotis (Myotis morrisi); 431. Bocage's Myotis (Myotis bocagil); 432. Malagasy Myotis (Myotis goudoti); 433. Anjouan Myotis (Myotis anjouanensis); 434. Kock's Myotis (Myotis dieteri); 435. Alcathoe Whiskered Myotis (Myotis alcathoe); 436. Hyrcanian Myotis (Myotis hyrcanicus); 437. Pond Myotis (Myotis dasycneme); 438. lkonnikov's Myotis (Myotis ikonnikovi); 439. Sichuan Myotis (Myotis altarium); 440. Common Whiskered Myotis (Myotis mystacinus); 441. David's Myotis (Myotis davidii); 442. Valley Myotis (Myotis ancricola); 443. Anna Tess's Myotis (Myotis annatessae);, 444. Gomantong Myotis (Myotis gomantongensis); 445. Peters's Myotis (Myotis ater); 446. Nepalese Whiskered Myotis (Myotis muricola); 447. Brown's Whiskered Myotis (Myotis brown); 448. Insular Myotis (Myotis insularum).
On following pages: 396. Yuma Myotis (Myotis yumanensis); 397. Cave Myotis (Myotis velifer); 398. Peninsular Myotis (Myotis peninsularis); 399. Guatemalan Myotis (Myotis cobanensis); 400. Chilean Myotis (Myotis chiloensis); 401. Silver-tipped Myotis (Myotis albescens); 402. Yellowish Myotis (Myotis levis); 403. Dinelli's Myotis (Myotis dinelli); 404. I1zecksohn's Myotis (Myotis izecksohni); 405. LaVal's Myotis (Myotis lavali); 406. Montane Myotis (Myotis oxyotus); 407. Clyde Jones's Myotis (Myotis clydejonesi); 408. Schwartz's Myotis (Myotis martiniquensis); 409. Dominican Myotis (Myotis dominicensis); 410. Barbados Myotis (Myotis nycton; 411. Atacama Myotis (Myotis atacamensis); 412. Curagao Myotis (Myotis nesopolus); 413. Colombian Black Myotis (Myotis caucensis); 414. Sir David Attenborough''s Myotis (Myotis attenboroughi); 415. Handley's Myotis (Myotis handleyi); 416. Diminutive Myotis (Myotis diminutus); 417. Common Black Myotis (Myotis nigricans); 418. Brandt's Myotis (Myotis brandftii); 419. Siberian Whiskered Myotis (Myotis sibiricus). in Vespertilionidae
On following pages: 396. Yuma Myotis (Myotis yumanensis); 397. Cave Myotis (Myotis velifer); 398. Peninsular Myotis (Myotis peninsularis); 399. Guatemalan Myotis (Myotis cobanensis); 400. Chilean Myotis (Myotis chiloensis); 401. Silver-tipped Myotis (Myotis albescens); 402. Yellowish Myotis (Myotis levis); 403. Dinelli's Myotis (Myotis dinelli); 404. I1zecksohn's Myotis (Myotis izecksohni); 405. LaVal's Myotis (Myotis lavali); 406. Montane Myotis (Myotis oxyotus); 407. Clyde Jones's Myotis (Myotis clydejonesi); 408. Schwartz's Myotis (Myotis martiniquensis); 409. Dominican Myotis (Myotis dominicensis); 410. Barbados Myotis (Myotis nycton; 411. Atacama Myotis (Myotis atacamensis); 412. Curagao Myotis (Myotis nesopolus); 413. Colombian Black Myotis (Myotis caucensis); 414. Sir David Attenborough''s Myotis (Myotis attenboroughi); 415. Handley's Myotis (Myotis handleyi); 416. Diminutive Myotis (Myotis diminutus); 417. Common Black Myotis (Myotis nigricans); 418. Brandt's Myotis (Myotis brandftii); 419. Siberian Whiskered Myotis (Myotis sibiricus).
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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.