The MS-ASL dataset is a large-scale isolated American Sign Language dataset containing 25,000 samples from 1000 different signs performed by 200 different signers.

A collection of 1 brain maps. Each brain map is a 3D array of values representing properties of the brain at different locations.

Collection description

Collection description

Subject species

homo sapiens

Modality

Structural MRI

Cognitive paradigm (task)

2nd-order rule acquisition

Map type

T

This is the combined diffusion-weighed / arterial spin labelling data set from the work 'Non-invasive MRI of Blood-Cerebrospinal Fluid Barrier Function' (Evans et al., 2020, Figure 1E].

The experiments were designed to ensure there was negligible intra-vascular signal contributions from the BCSFB-ASL signal.

The data is in Matlab format. The BCSFB-ASL data is in a 4D array where the first two array elements are the 2D MRI images, the 3rd element is the interleaved tagged and control images (inner most loop) together with the B0 and diffusion weighted images (b=200 s/mm2) together with the number of repetitions (outer most loop, 20 repetitions) and the 4th element is the number of inflow times (750, 2750 and 6500 ms).The traditional ASL data is in the same format but there is only 1 inflow time (750ms) and 5 rather then 20 repetitions.

This dataset contains resting state data collected using a multiband, multiecho simultaneous pseudocontinous ASL (pCASL) and BOLD acquisition. Additional information regarding the sequence is as follows:

The sequence consists of an unbalanced pseudo-continuous ASL (pCASL) tagging module, followed by a post labeling delay period (PLD). Following the PLD, a multiband excitation and multi-echo, gradient-echo EPI readout was implemented. Blipped-CAIPI was also applied to reduce g-factor noise amplification caused by the slice-unaliasing in MB imaging. Each echo in the multi-echo acquisition was obtained consecutively as part of one shot. The last repetition is the M0 image collected for quantification of CBF. Each subject underwent one bilateral finger tapping task MBME ASL/BOLD scan, which utilized an unbalanced pCASL labeling scheme with labeling time=1.5 s and PLD=1.5 s. A partial k-space acquisition was employed with 20 overscan lines. To keep the later TEs within reasonable ranges and reduce total readout time, in-plane acceleration was employed with R=2. Additional parameters for the MBME ASL/BOLD run were as follows: number of echoes=4, TE=9.1, 25, 39.6, 54.3 ms, TR=3.5 s, MB-factor=4, number of excitations=11 (total slices=11×4=44), FOV=240 mm, resolution=3×3×3 mm, FA=90°, RF pulse width=6400 ms. Scans lasted 356s, which included 64s of calibration reps at the beginning of the scan. In total 73 repetitions were acquired.

Comments added by Openfmri Curators

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General Comments

T2 data wasn’t used for any of the analysis in the paper though they were acquired as per the paper.

Defacing

Pydeface was used on all anatomical images to ensure de-identification of subjects. The code can be found at https://github.com/poldracklab/pydeface

Quality Control

MRIQC was run on the dataset. Results are located in derivatives/mriqc. Learn more about it here: https://mriqc.readthedocs.io/en/stable/

Where to discuss the dataset

1) www.openfmri.org/dataset/ds******/ See the comments section at the bottom of the dataset page. 2) www.neurostars.org Please tag any discussion topics with the tags openfmri and dsXXXXXX. 3) Send an email to submissions@openfmri.org. Please include the accession number in your email.

Known Issues

Background and purposeArterial spin-labeling (ASL) was recently introduced as a noninvasive method to evaluate cerebral hemodynamics. The purposes of this study were to assess the ability of ASL imaging to detect crossed cerebellar diaschisis (CCD) in patients with their first unilateral supratentorial hyperacute stroke and to identify imaging or clinical factors significantly associated with CCD.Materials and methodsWe reviewed 204 consecutive patients who underwent MRI less than 8 hours after the onset of stroke symptoms. The inclusion criteria were supratentorial abnormality in diffusion-weighted images in the absence of a cerebellar or brain stem lesion, bilateral supratentorial infarction, subacute or chronic infarction, and MR angiography showing vertebrobasilar system disease. For qualitative analysis, asymmetric cerebellar hypoperfusion in ASL images was categorized into 3 grades. Quantitative analysis was performed to calculate the asymmetric index (AI). The patients’ demographic and clinical features and outcomes were recorded. Univariate and multivariate analyses were also performed.ResultsA total of 32 patients met the inclusion criteria, and 24 (75%) presented CCD. Univariate analyses revealed more frequent arterial occlusions, higher diffusion-weighted imaging (DWI) lesion volumes and higher initial NIHSS and mRS scores in the CCD-positive group compared with the CCD-negative group (all p < .05). The presence of arterial occlusion and the initial mRS scores were related with the AI (all p < .05). Multivariate analyses revealed that arterial occlusion and the initial mRS scores were significantly associated with CCD and AI.ConclusionASL imaging could detect CCD in 75% of patients with hyperacute infarction. We found that CCD was more prevalent in patients with arterial occlusion, larger ischemic brain volumes, and higher initial NIHSS and mRS scores. In particular, vessel occlusion and initial mRS score appeared to be significantly related with CCD pathophysiology in the hyperacute stage.