{"doi":"10.1038/s41597-021-01092-6","title":"Comprehensive diffusion MRI dataset for in vivo human brain microstructure mapping using 300 mT/m gradients","abstract":"Strong gradient systems can improve the signal-to-noise ratio of diffusion MRI measurements and enable a wider range of acquisition parameters that are beneficial for microstructural imaging. We present a comprehensive diffusion MRI dataset of 26 healthy participants acquired on the MGH-USC 3 T Connectome scanner equipped with 300 mT/m maximum gradient strength and a custom-built 64-channel head coil. For each participant, the one-hour long acquisition systematically sampled the accessible diffusion measurement space, including two diffusion times (19 and 49 ms), eight gradient strengths linearly spaced between 30 mT/m and 290 mT/m for each diffusion time, and 32 or 64 uniformly distributed directions. The diffusion MRI data were preprocessed to correct for gradient nonlinearity, eddy currents, and susceptibility induced distortions. In addition, scan/rescan data from a subset of seven individuals were also acquired and provided. The MGH Connectome Diffusion Microstructure Dataset (CDMD) may serve as a test bed for the development of new data analysis methods, such as fiber orientation estimation, tractography and microstructural modelling.","journal":"Scientific Data","year":2022,"id":296373,"datarank":0.9653505879769235,"base_score":4.060443010546419,"endowment":4.060443010546419,"self_citation_contribution":0.6090664515819629,"citation_network_contribution":0.3562841363949606,"self_endowment_contribution":0.6090664515819629,"citer_contribution":0.3562841363949606,"corpus_percentile":79.04386168484567,"corpus_rank":2710,"citation_count":57,"citer_count":34,"citers_with_citation_signal":17,"citers_with_endowment":17,"datacite_reuse_total":0,"is_dataset":true,"is_dataset_confidence":0.9317,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2022-01-01","fair_score":62.5,"fair_percentile":81.0149801284011,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":263264,"name":"Qiuyun Fan","orcid":"0000-0001-9053-6279","position":1,"is_corresponding":false},{"id":263268,"name":"Thomas Witzel","orcid":"0000-0002-5806-4897","position":2,"is_corresponding":false},{"id":245952,"name":"Maya N. Polackal","orcid":"0000-0001-9236-5039","position":3,"is_corresponding":false},{"id":253266,"name":"Ned A. Ohringer","orcid":null,"position":4,"is_corresponding":false},{"id":263266,"name":"Chanon Ngamsombat","orcid":"0000-0001-5055-0711","position":5,"is_corresponding":false},{"id":502992,"name":"Andrew W. Russo","orcid":"0000-0002-8456-8757","position":6,"is_corresponding":false},{"id":502993,"name":"Natalya Machado","orcid":"0000-0002-3896-496X","position":7,"is_corresponding":false},{"id":823073,"name":"Kristina Brewer","orcid":null,"position":8,"is_corresponding":false},{"id":561869,"name":"Fuyixue Wang","orcid":"0000-0001-8975-2775","position":9,"is_corresponding":false},{"id":263269,"name":"Kawin Setsompop","orcid":"0000-0003-0455-7634","position":10,"is_corresponding":false},{"id":30837,"name":"Jon̈athan R. Polimeni","orcid":"0000-0002-1348-1179","position":11,"is_corresponding":false},{"id":492626,"name":"Boris Keil","orcid":"0000-0003-0805-8330","position":12,"is_corresponding":false},{"id":241418,"name":"Lawrence L. Wald","orcid":"0000-0001-8278-6307","position":13,"is_corresponding":false},{"id":63233,"name":"Bruce R. Rosen","orcid":"0000-0002-8576-0839","position":14,"is_corresponding":false},{"id":297461,"name":"Eric C. Klawiter","orcid":"0000-0002-3429-2633","position":15,"is_corresponding":false},{"id":297460,"name":"Aapo Nummenmaa","orcid":"0000-0002-6452-7958","position":16,"is_corresponding":false},{"id":263270,"name":"Susie Y. Huang","orcid":"0000-0003-2950-7254","position":17,"is_corresponding":false},{"id":251970,"name":"Qiyuan Tian","orcid":"0000-0002-8350-5295","position":0,"is_corresponding":true}],"reference_count":92,"raw_metadata":null,"created_at":"2026-07-19T00:31:16.555318Z","pmid":"35042861","pmcid":"PMC8766594","fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":88.8889,"fair_a":50.0,"fair_i":20.0,"fair_r":41.6667,"fair_zscore":1.1103,"fair_rationale":{"fair_score":62.5,"has_llm":true,"taxonomy_version":"fair_taxonomy_v5","dimensions":{"F":{"name":"Findable","score":88.89,"criteria":[{"key":"f_dataset_pid","label":"Persistent identifier for the data","kind":"llm","weight":2.0,"fraction":1.0,"verdict":"yes","evidence":"https://doi.org/10.6084/m9.figshare.c.5315474","grounded":true,"rationale":"The dataset has a DOI as its persistent identifier, given in the reference list. 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For neuroimaging data, deposit in OpenNeuro or NeuroVault.","anchors":["yes","partial","no"],"verdict":"partial","current":0.5,"evidence":"The preprocessed diffusion MRI data and the T1-weighted MRI data of 26 healthy participants and the preprocessed rescan diffusion MRI data and the T1-weighted MRI data from seven of the 26 participants are publicly available through the figshare repository 93.","why":"The sentence states the data are publicly available with no precondition. [downgraded to 'partial' — no verifiable quote from the paper] [majority verdict 'partial' (4/5 passes agreed)]","gain":8.33,"priority":"essential","scored":true},{"key":"i_open_nonproprietary_format","dimension":"I","label":"Open file format","action":"Release the data in an open, community-standard format (CSV/TSV, JSON, HDF5, NetCDF, FASTQ, VCF, NIfTI…) instead of — or alongside — any proprietary or instrument-native format, and name the format in the paper. A dataset that needs a €2,000 licence to open is not reusable. Prefer open neuroimaging formats such as NIfTI or BIDS.","anchors":["yes","partial","no"],"verdict":"no","current":0.0,"evidence":null,"why":"The paper does not specify any file format for the released data.","gain":8.33,"priority":"important","scored":true},{"key":"r_versioning","dimension":"R","label":"Snapshot identified","action":"Version the deposit and cite the exact version analysed (a version-specific DOI, or an accession with its version suffix). A reader reproducing your work against 'the current release' is reproducing it against a different dataset.","anchors":["yes","partial","no"],"verdict":"no","current":0.0,"evidence":null,"why":"The paper does not provide a version token or date to identify a specific snapshot of the data.","gain":4.17,"priority":"useful","scored":true},{"key":"f_data_availability_statement","dimension":"F","label":"Data-availability statement","action":"Replace the statement with the repository template: name the repository and give the accession or DOI (Colavizza category 3). This is the only DAS class associated with a measured citation advantage; 'available on reasonable request' and 'within the article' are not.","anchors":["yes","partial","no"],"verdict":"partial","current":0.5,"evidence":"The preprocessed diffusion MRI data and the T1-weighted MRI data of 26 healthy participants and the preprocessed rescan diffusion MRI data and the T1-weighted MRI data from seven of the 26 participants are publicly available through the figshare repository 93.","why":"The Data Records section serves as the data availability statement and points to the figshare repository with a DOI (reference 93). [downgraded to 'partial' — no verifiable quote from the paper]","gain":0.0,"priority":"essential","scored":false},{"key":"i_community_standard_vocabulary","dimension":"I","label":"Community standard / vocabulary","action":"Adopt and NAME your domain's data standard — the minimum-information checklist, metadata schema, or ontology your community uses (MIAME/MINSEQE, ISA-Tab, BIDS, an OBO ontology, HL7 FHIR/OMOP) — and say which one you followed. A reporting checklist standardises your paper; it does nothing for your data. In neuroimaging, describe the data with BIDS, NIfTI or DICOM.","anchors":["yes","partial","no"],"verdict":"no","current":0.0,"evidence":null,"why":"The paper does not name a community data standard, checklist, or ontology; it only mentions software tools.","gain":0.0,"priority":"important","scored":false},{"key":"r_documentation_codebook","dimension":"R","label":"Documentation / codebook","action":"Ship a README and a data dictionary IN the deposit — every file, every variable, its units, its allowed values, its missing-value codes. 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