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40 results for “gait stability”
Data and code from: Healthy young adults use distinct gait strategies to enhance stability when walking on mild slopes and when altering arm swing
<p>This repository contains the Julia code, Jupyter notebook, and data used in the study “Healthy young adults use distinct gait strategies to enhance stability when walking on mild slopes and when altering arm swing” by MacDonald et al.</p> <p><strong>Instructions</strong></p> <p>To run this analysis on your computer, both Julia and Jupyter Notebook must be installed. A version of Julia appropriate for your OS can be downloaded from the <a href="https://julialang.org/downloads/">Julia website</a>, and Jupyter can be installed from within Julia (in the REPL) with</p> <pre><code>] add IJulia</code></pre> <p>Alternate instructions for installing Jupyter can be found on the <a href="https://github.com/JuliaLang/IJulia.jl">IJulia github</a> or the <a href="https://jupyter.org/install">Jupyter homepage</a> (not recommended).</p> <p>From within the main repository directory, start Julia and then start Jupyter in the Julia REPL</p> <pre><code>using IJulia notebook(;dir=pwd())</code></pre> <p>or if using a system Jupyter installation, start Jupyter from your favorite available shell (e.g. Powershell on Windows, bash on any *nix variant, etc.). In Jupyter, open the <code>notebooks/analysis.ipynb</code> notebook. Running all cells will reproduce the results for this paper.</p> <p><strong>Description of data</strong></p> <p>The <code>data</code> directory contains all the data used in the production of the results which were statistically tested.</p> <p>Each <code>.mat</code> file contains events and data generated in Visual3D:</p> <ul> <li>Events <ul> <li><code>LTO</code>/<code>RTO</code> (Left/right toe-off)</li> <li><code>LHS</code>/<code>RHS</code> (Left/right heel-strike)</li> <li><code>HIST</code>/<code>HIEN</code> (Hilly start/end)</li> <li><code>ROST</code>/<code>ROEN</code> (Rocky start/end)</li> <li><code>MLST</code>/<code>MLEN</code> (ML translation start/end)</li> </ul> </li> <li>Data <ul> <li><code>LFootPos</code>/<code>RFootPos</code> (Left/right foot COM position)</li> <li><code>TrunkPos/TrunkVel</code>/<code>TrunkAcc</code> (Trunk COM position, velocity, and acceleration)</li> <li><code>HeadPos/HeadVel</code>/<code>HeadAcc</code> (Head COM position, velocity, and acceleration)</li> <li><code>COG</code> (Whole-body COM/COG)</li> </ul> </li> </ul> <p>The <code>.csv</code> files contain system state of the CAREN system produced by D-Flow software, which includes various system and software settings, most pertinent of which is the treadmill speed.</p> <p>The <code>.c3d</code> files contain the raw motion capture data from Vicon Nexus.</p> <ul> </ul> <p>The results of the <code>notebooks/analysis.ipynb</code> notebook are found in the <code>results</code> folder. Please see the paper for a list of the dependent variables and statistical analyses.</p>
The validation of new phase-dependent gait stability measures: a modelling approach
<p><span><span><span><span><span><span><span><span><span><span><span>Identification of individuals at risk of falling is important when designing fall prevention methods. Current stability measures that estimate gait stability and robustness appear limited in predicting falls in older adults. Inspired by recent findings of phase-dependent local stability changes within a gait cycle, we used compass-walker models to test several phase-dependent stability metrics for their usefulness to predict gait robustness. These metrics are closely related to the often-employed maximum finite-time Lyapunov exponent and maximum Floquet multiplier. They entail linearizing the system in a rotating hypersurface orthogonal to the period-one solution, and estimating the local divergence rate of the swing phases and the foot strikes. We correlated the metrics with the gait robustness of two compass walker models with either point or circular feet to estimate their prediction accuracy. To also test for the metrics' invariance under coordinate transform, we represented the point-feet walker in both Euler-Lagrange and Hamiltonian canonical form. Our simulations revealed that for most of the metrics, correlations differ between models and also change under coordinate transforms, severely limiting the prediction accuracy of gait robustness. The only exception that consistently correlated with gait robustness is the divergence of foot strikes. These results admit challenges of using phase-dependent stability metrics as objective measure to quantify gait robustness.</span></span></span></span></span></span></span></span></span></span></span></p>
Code and data for manuscript: Is phase-dependent stability related to phase-dependent gait robustness?
<p>Code and code data for manuscript: Is phase-dependent stability related to phase-dependent gait robustness?</p>
The Effect of Lumbar Stabilization Exercise and Gait Training on Lower Back Muscles- Electromyographic(EMG) Analysis
ClinicalTrials.gov study NCT02938169. IPD Sharing: NO. Countries: 1. Publications: 1.
Data from: The effect of sampling methods on the validity and reliability of the estimation of the orbital stability of human gait
Open the record for dataset details and reuse information.
The validation of new phase-dependent gait stability measures: a modelling approach
Open the record for dataset details and reuse information.
Dataset and analyses for : Can foot placement during gait be trained? Adaptations in stability control when ankle moments are constrained
<p>Here you'll find the dataset and analyses belonging to the publication "Can foot placement during gait be trained? Adaptations in stability control when ankle moments are constrained". Participants walked on a treadmill with and without shoes constraining ankle moment control. We evaluated whether participants improved their degree of foot placement control, during and after walking with ankle moment constraints. Ground reaction forces and full body kinematics have been collected.</p> <p>For more detail on the folders' contents please see "Read me - Can foot placement during gait be trained.docx".</p>
Data for: Effects of vestibular stimulation on gait stability when walking at different step widths
<p><strong>Read me - Effects of vestibular stimulation on gait stability when walking at different step widths</strong></p> <p> </p> <p>In this folder you will find the data (folders named Data) and analysis (folder named software) belonging to the manuscript “Effects of vestibular stimulation on gait stability when walking at different step widths”(Magnani et al. 2021). To re-run the analysis, create a folder, and put the file subject_numbers.m, as well as the contents of data.zip and software.zip in that top level folder. Next, navigate to the “software” folder, and run scripts C_main_all_outcomes_paper2 and E_main_stats_paper2.</p> <p> </p> <p>The following subject numbers were included in the analysis: 4 5 6 8 12 14 16 17 18 19 20 21 22 23 (see also subject_numbers.m, which includes explanation of why some subjects were excluded). We had problems with dust due to reconstruction in nearby labs, so some of the kinematic data was simply not useable.</p> <p> </p> <p>The scripts were written for data from 12 conditions, being analyzed the conditions numbered 1 2 5 6 7 8 :</p> <ol> <li>Steady state walking under vestibular stimulation (control, EVS)</li> <li>Steady state walking (control, no-EVS)</li> <li>Stabilization frame walking under vestibular stimulation (frame, EVS)</li> <li>Stabilization frame walking (frame, no-EVS)</li> <li>Narrow-base walking under vestibular stimulation (narrow, EVS)</li> <li>Narrow-base walking (narrow, no-EVS)</li> <li>Wide-base walking under vestibular stimulation (wide, EVS)</li> <li>Wide-base walking (wide, no-EVS)</li> <li>Stabilization frame ML walking under vestibular stimulation looking to the left side (left_frame, EVS)</li> <li>Stabilization frame ML (left_frame, no-EVS)</li> <li>Stabilization frame AP/ML walking under vestibular stimulation looking to the left side (left_frame_AP, EVS)</li> <li>Stabilization frame AP/ML walking looking to the left side (left_frame_AP, no- EVS)</li> </ol> <p> </p> <p>Below we describe the most important contents:</p> <table> <tbody> <tr> <td> <p><strong>Folders</strong></p> </td> <td> <p><strong>Content</strong></p> </td> </tr> <tr> <td> <p><em>Data.zip</em></p> </td> <td> <p>Data of all participants. Each subject has a separate subfolder.</p> <p> </p> <p>These subfolders contain 1 excel files (used to match the conditions with the corresponding data files), as well as the pointer file corresponding to the pointer used during the measurement, needed to digitize the bony landmarks and the muscles names.</p> <p>Each subject subfolder has the following subfolders:</p> </td> </tr> <tr> <td> <p>OPTO</p> </td> <td> <p>Optotrak and force plate files</p> <ul> <li>.ndf (motion capture data)</li> <li>.afp (force plate data)</li> <li>.hs calculated heelstrikes, as done in B_main_heelstrikes.m</li> </ul> </td> </tr> <tr> <td> <p>EMG</p> </td> <td> <p>EMG data stored at .mat and .bin files (not used in current manuscript)</p> </td> </tr> <tr> <td> <p>Software</p> </td> <td> <p><em>=VU 3D model=</em></p> </td> <td> <p>Contains general functions for the analysis of our kinematic and force plate data.</p> </td> </tr> <tr> <td> <p>Functions</p> </td> <td> <p>Functions written specifically for the analysis of this dataset, including some unused functions</p> </td> </tr> <tr> <td> <p>Local Dynamic Stability</p> </td> <td> <p>Functions written specifically for the local dynamic stability.</p> <p>(Bruijn 2017).</p> </td> </tr> <tr> <td> <p>Results</p> </td> <td> <p>Contains storage of some intermediate results.</p> <p>The figures folder includes all</p> <p> </p> </td> </tr> <tr> <td> <p>A_main_check_kin</p> </td> <td> <p>Scripy used to check the kinematics</p> </td> </tr> <tr> <td> <p>B_main_heelstrikes</p> </td> <td> <p>Script to identify gait events were identified from center of pressure data (Roerdink et al. 2008), results are stored in .hs files in subject data folder</p> </td> </tr> <tr> <td> <p>C_main_all_outcomes_paper2</p> </td> <td> <p>Script to calculate all outcomes</p> </td> </tr> <tr> <td> <p>E_main_stats_paper2</p> </td> <td> <p>Scripts of the statistical analysis, which also creates the figure files as seen in the manuscript.</p> </td> </tr> <tr> <td> <p>figure1.eps</p> </td> <td> <p>Mean values of stride width and stride width variability (represents figure 2 from paper)</p> </td> </tr> <tr> <td> <p>figure2.eps</p> </td> <td> <p>Mean values of step time and step time variability (represents figure 3 from paper)</p> </td> </tr> <tr> <td> <p>figure3.eps</p> </td> <td> <p>Mean values and standard deviation of local divergence exponent and center of mass variability (represents figure 4 from paper)</p> </td> </tr> <tr> <td> <p>figure4.eps</p> </td> <td> <p>Mean values of R<sup>2</sup> (percentage of explained variance in foot placement) and the residual variance in foot placement (represents figure 5 from paper)</p> </td> </tr> <tr> <td> <p>ANOVA.csv</p> </td> <td> <p>ANOVA results for each variable</p> </td> </tr> <tr> <td> <p>Posthocs_condition.csv</p> </td> <td> <p>Posthoc results of the condition effect</p> </td> </tr> <tr> <td> <p>Posthocs_interaction.csv</p> </td> <td> <p>Posthoc results of the interaction effect</p> </td> </tr> <tr> <td> <p>Settings_rina.xls</p> </td> <td> <p>The setting of pointer, markers, and segments. </p> </td> </tr> <tr> <td> <p>Stimulationfig.pdf</p> </td> <td> <p>Figure of the electrical stimulation signal (corresponds to figure 1 from paper)</p> </td> </tr> <tr> <td> <p>Svs_5mA_0-25Hz_2000Hz_120s.txt</p> </td> <td> <p>File containing the random electrical vestibular stimulation from the zero-mean low-pass filtered (25 Hz cutoff, zero lag, fourth-order Butterworth) white noise, the peak amplitude of 5mA, root mean square (RMS) of ~ 1.2 mA, range frequency between 0 to 25Hz, and intensity of 2000Hz for 120 seconds of duration.</p> </td> </tr> <tr> <td> <p>Svs_5mA_0-25Hz_2000Hz_480s.txt</p> </td> <td> <p>File containing the electrical vestibular stimulation from the zero-mean low-pass filtered (25 Hz cutoff, zero lag, fourth-order Butterworth) white noise, the peak amplitude of 5mA, root mean square (RMS) of ~ 1.2 mA, range frequency between 0 to 25Hz, and intensity of 2000Hz for 480 seconds of duration.</p> </td> </tr> </tbody> </table> <p> </p> <p> </p> <p>Bruijn SM (2017) Local Dynamic Stability. https://zenodo.org/record/1181937#.Y1Fj7i0w354</p> <p>Magnani RM, van Dieen JH, Bruijn SM (2021) Effects of vestibular stimulation on gait stability when walking at different step widths. bioRxiv 459650:. https://doi.org/https://doi.org/10.1101/2021.09.09.459650</p> <p>Roerdink M, Coolen BH, Clairbois BHE, et al (2008) Online gait event detection using a large force platform embedded in a treadmill. J Biomech 41:2628–32. https://doi.org/10.1016/j.jbiomech.2008.06.023</p> <p> </p>
Dataset and analyses for: Force-field perturbations and muscle vibration strengthen stability-related foot placement responses during steady-state gait in healthy adults
<p>We have collected kinematic data (heel and pelvis markers) from healthy adults during treadmill walking, whilst force-field perturbations and timed muscle vibrations were applied. We assessed the (after-)effects of these two interventions by evaluating foot placement control through outcome measures derived from a regression model which predicts foot placement based on the center-of-mass kinematic state. The data and analyses provided belong to the scientific publication: "Force-field perturbations and muscle vibration strengthen stability-related foot placement responses during steady-state gait in healthy adults". In the manuscript we place these analyses in the context of stability control and speculate on how these trainining interventions may improve stability control in patient populations.</p>
Comparison of Exergaming and Vestibular Training on Gaze Stability, Balance and Gait Performance of Older Adults.
ClinicalTrials.gov study NCT04414462. IPD Sharing: NO. Countries: 1. Publications: 6.
Gait and Functional Outcomes Study Following Total Knee Arthroplasty With Medial-pivot or Posterior-stabilized Implants
ClinicalTrials.gov study NCT02589197. IPD Sharing: NO. Countries: 1. Publications: 1.
Effects of Otago and Gaze Stabilization Exercises on Balance, Gait and QOL in Elderly Stroke Patients
ClinicalTrials.gov study NCT06845709. IPD Sharing: NO. Countries: 1. Publications: 3.
Stochastic Resonance Stimulation Effect on Gait Stability in Parkinson Disease
ClinicalTrials.gov study NCT06829342. IPD Sharing: UNDECIDED. Countries: 1. Publications: 0.
Effects of Stabilization-based Pilates Exercise on Gait and Balance in Women With Flexible Pesplanus
ClinicalTrials.gov study NCT06583434. IPD Sharing: YES. Countries: 1. Publications: 23.
Study Aims to Compare the Effect of Robotic-assisted Gait Training and Conventional Treadmill Training on Postural Stability in Ambulatory Children With Cerebral Palsy.
ClinicalTrials.gov study NCT06719271. IPD Sharing: UNDECIDED. Countries: 1. Publications: 1.
Data: The effects of general fatigue induced by incremental exercise test and active recovery modes on energy cost, gait variability and stability in male soccer players
<p>Data, code, and movies for Mahaki et al. (2020); The effects of general fatigue induced by incremental exercise test and active recovery modes on energy cost, gait variability and stability in male soccer players. Published in The Journal of Biomechanics (<a href="https://doi.org/10.1016/j.jbiomech.2020.109823">https://doi.org/10.1016/j.jbiomech.2020.109823</a>).</p> <p><strong>Gas data</strong> - contains all Oxygen data plus a script to run the data.</p> <p> - Subjectxx - folder with oxygen data.</p> <p> - GasdataMohammad [type of file: MATLAB code (.m)] - script to analyze the oxygen data. The outcomes have been saved as RestECnet, PWSECnet, and IVTECnet [type of files: MATLAB data (.mat)].</p> <p> - EC_Stat_boxplot [type of file: MATLAB code (.m)] - script to statistically test the hypotheses in terms of energetic cost, to calculate the effect sizes of main effects of Time, Recovery and Interaction effect (Time vs Recovery) and to show the outcome in boxplot together with individual data points (The results have been presented in <strong>Fig 2.</strong>)</p> <p> </p> <p><strong>Kinematic Data</strong> - contains all Kinematic data plus scripts to run the data:</p> <p> - Subjectxx - folder with kinematics data.</p> <p> - Rest_VAR [type of file: MATLAB code (.m)] - script to analyze the kinematics data in the Rest recovery session. The outcomes have been saved as RestVAR [type of file: MATLAB data (.mat)]. The corresponding plots, per subject & per trial, have been saved in the Plots folder.</p> <p> - PWS_VAR [type of file: MATLAB code (.m)] - script to analyze the kinematics data in the PWS recovery session. The outcomes have been saved as PWSVAR [type of file: MATLAB data (.mat)]. The corresponding plots, per subject & per trial, have been saved in the Plots folder.</p> <p> - IVT_VAR [type of file: MATLAB code (.m)] - script to analyze the kinematics data in the IVT recovery session. The outcomes have been saved as IVTVAR [type of file: MATLAB data (.mat)]. The corresponding plots, per subject & per trial, have been saved in the Plots folder.</p> <p> - VAR_Stat_boxplot [type of file: MATLAB code (.m)] - script to statistically test the hypotheses in terms of gait variability (VAR sagittal, frontal, and horizontal) and to show the outcome in boxplot together with individual data points (The results have been presented in <strong>Fig 3.</strong>).</p> <p> - VAR_Sagittal_Stat_boxplot [type of file: MATLAB code (.m)] - script to statistically test the hypotheses in terms of gait variability in sagittal plane, to calculate the effect sizes of main effects of Time, Recovery and Interaction effect (Time vs Recovery), and to show the outcome in boxplot together with individual data points.</p> <p> - VAR_Frontal_Stat_boxplot [type of file: MATLAB code (.m)] - script to statistically test the hypotheses in terms of gait variability in frontal plane, to calculate the effect sizes of main effects of Time, Recovery and Interaction effect (Time vs Recovery), and to show the outcome in boxplot together with individual data points.</p> <p> - VAR_Horizontal_Stat_boxplot [type of file: MATLAB code (.m)] - script to statistically test the hypotheses in terms of gait variability in horizontal plane, to calculate the effect sizes of main effects of Time, Recovery and Interaction effect (Time vs Recovery), and to show the outcome in boxplot together with individual data points.</p> <p> - normalizetimebase [type of file: MATLAB code (.m)] – function to normalize VAR from 0 to 100% of the gait cycle.</p> <p> - VAR_Sagittal [type of file: JASP/Jamovie files (.jasp/.omv)] - file to statistically test gait variability in sagittal plane. Imported data have been saved as VAR_Sagittal [type of file: Excell file (.csv)].</p> <p> - VAR_Frontal [type of file: JASP/Jamovie files (.jasp/.omv)] - file to statistically test gait variability in frontal plane. Imported data have been saved as VAR_Frontal [type of file: Excell files (.csv)].</p> <p> - VAR_Horizontal [type of file: JASP/Jamovie files (.jasp/.omv)] - file to statistically test gait variability in horizontal plane. Imported data have been saved as VAR_Horizontal [type of file: Excell file (.csv)].</p> <p> + Trunk Stability - folder includes all outcomes and codes in terms of gait stability:</p> <p> -Thoracic [type of file: Excell file (.xlsx)] - general file includes all outcomes in terms of gait stability.</p> <p> - LDS_Stat_boxplot [type of file: MATLAB code (.m)] - script to statistically test the hypotheses in terms of gait stability (λ sagittal, λ frontal, and λ horizontal) and to show the outcome in boxplot together with individual data points (The results have been presented in <strong>Fig 5.</strong>).</p> <p> - LDS_Sagittal_Stat_boxplot [type of file: MATLAB code (.m)] - script to statistically test the hypotheses inn terms of gait stability in sagittal plane, to calculate the effect sizes of main effects of Time, Recovery and Interaction effect (Time vs Recovery), and to show the outcome in boxplot together with individual data points.</p> <p> - LDS_Frontal_Stat_boxplot [type of file: MATLAB code (.m)] - script to statistically test the hypotheses in terms of gait stability in frontal plane, to calculate the effect sizes of main effects of Time, Recovery and Interaction effect (Time vs Recovery), and to show the outcome in boxplot together with individual data points.</p> <p> - LDS_Horizontal_Stat_boxplot [type of file: MATLAB code (.m)] - script to statistically test the hypotheses in terms of gait stability in horizontal plane, to calculate the effect sizes of main effects of Time, Recovery and Interaction effect (Time vs Recovery), and to show the outcome in boxplot together with individual data points.</p> <p> - Rest_LDS_Sagittal [type of file: Excell file (.xlsx)] - file includes LDS outcomes in the Rest recovery session and in the sagittal plane.</p> <p> - Rest_LDS_Frontal [type of file: Excell file (.xlsx)] - file includes LDS outcomes in the Rest recovery session and in the frontal plane.</p> <p> - Rest_LDS_Horizontal [type of file: Excell file (.xlsx)] - file includes LDS outcomes in the Rest recovery session and in the horizontal plane.</p> <p> - PWS_LDS_Sagittal [type of file: Excell file (.xlsx)] - file includes LDS outcomes in the PWS recovery session and in the sagittal plane.</p> <p> - PWS_LDS_Frontal [type of file: Excell file (.xlsx)] - file includes LDS outcomes in the PWS recovery session and in the frontal plane.</p> <p> - PWS_LDS_Horizontal [type of file: Excell file (.xlsx)] - file includes LDS outcomes in the PWS recovery session and in the horizontal plane.</p> <p> - IVT_LDS_Sagittal [type of file: Excell file (.xlsx)] - file includes LDS outcomes in the IVT recovery session and in the sagittal plane.</p> <p> - IVT_LDS_Frontal [type of file: Excell file (.xlsx)] - file includes LDS outcomes in the IVT recovery session and in the frontal plane.</p> <p> - IVT_LDS_Horizontal [type of file: Excell file (.xlsx)] - file includes LDS outcomes in the IVT recovery session and in the horizontal plane.</p> <p> - LDS_sagittal [type of files: JASP/Jamovie files (.jasp/.omv)] - file to statistically test gait stability in sagittal plane. Imported data have been saved as LDS_sagittal [type of file: Excell file (.csv)].</p> <p> - LDS_frontal [type of files: JASP/Jamovie files (.jasp/.omv)] - file to statistically test gait stability in frontal plane. Imported data have been saved as LDS_frontal [type of file: Excell file (.csv)].</p> <p> - LDS_horizontal [type of files: JASP/Jamovie file (.jasp/.omv)] - file to statistically test gait stability in horizontal plane. Imported data have been saved as LDS_horizontal [type of file: Excell file (.csv)].</p> <p> </p> <p><strong>Movies</strong> –contains some movies [type of files: .mp4] to show the Noraxon calibration, IMUs placement on body segments, fatigue protocol, walking at PWS, and resting metabolic cost measurement.</p> <p> </p> <p><strong>The characteristics of participants</strong> [type of file: Excell file (.xlsx)] – file includes 4 sheets:</p> <p> - Sheet 1 includes height (cm), weight (kg), age (year), BMI, and body fat percentage of each participant.</p> <p> - Sheets 2-4 include the physiological parameters of each participant during IVT, PWS, and Rest recovery modes. The physiological parameters such as Vo2, Vo2max, HR, and RER of each participant have been reported during rest (i.e. sitting position) and incremental exercise test.</p> <p> </p>
Gait, Stair Climbing and Postural Stability in Knee Osteoarthritis Patients After Hyaluronic Acid Injection
ClinicalTrials.gov study NCT02063373. IPD Sharing: Not stated. Countries: 0. Publications: 1.
Prosthetic Components and Stability in Amputee Gait
ClinicalTrials.gov study NCT00167778. IPD Sharing: Not stated. Countries: 1. Publications: 0.
The Influence of Stability Boots on Gait Pattern in Healthy Adults
ClinicalTrials.gov study NCT03038815. IPD Sharing: NO. Countries: 1. Publications: 0.
Effects of Core Stability Training on Gait in Multiple Sclerosis Patients
ClinicalTrials.gov study NCT03442049. IPD Sharing: NO. Countries: 0. Publications: 5.
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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.