{"doi":"10.1002/hbm.25192","title":"Standard‐space atlas of the viscoelastic properties of the human brain","abstract":"Standard anatomical atlases are common in neuroimaging because they facilitate data analyses and comparisons across subjects and studies. The purpose of this study was to develop a standardized human brain atlas based on the physical mechanical properties (i.e., tissue viscoelasticity) of brain tissue using magnetic resonance elastography (MRE). MRE is a phase contrast-based MRI method that quantifies tissue viscoelasticity noninvasively and in vivo thus providing a macroscopic representation of the microstructural constituents of soft biological tissue. The development of standardized brain MRE atlases are therefore beneficial for comparing neural tissue integrity across populations. Data from a large number of healthy, young adults from multiple studies collected using common MRE acquisition and analysis protocols were assembled (N = 134; 78F/ 56 M; 18-35 years). Nonlinear image registration methods were applied to normalize viscoelastic property maps (shear stiffness, μ, and damping ratio, ξ) to the MNI152 standard structural template within the spatial coordinates of the ICBM-152. We find that average MRE brain templates contain emerging and symmetrized anatomical detail. Leveraging the substantial amount of data assembled, we illustrate that subcortical gray matter structures, white matter tracts, and regions of the cerebral cortex exhibit differing mechanical characteristics. Moreover, we report sex differences in viscoelasticity for specific neuroanatomical structures, which has implications for understanding patterns of individual differences in health and disease. These atlases provide reference values for clinical investigations as well as novel biophysical signatures of neuroanatomy. The templates are made openly available (github.com/mechneurolab/mre134) to foster collaboration across research institutions and to support robust cross-center comparisons.","journal":"Human Brain Mapping","year":2020,"id":55836,"datarank":1.823888566645717,"base_score":4.51085950651685,"endowment":4.51085950651685,"self_citation_contribution":0.6766289259775276,"citation_network_contribution":1.1472596406681894,"self_endowment_contribution":0.6766289259775276,"citer_contribution":1.1472596406681894,"corpus_percentile":88.41958691111627,"corpus_rank":1498,"citation_count":90,"citer_count":51,"citers_with_citation_signal":40,"citers_with_endowment":40,"datacite_reuse_total":0,"is_dataset":true,"is_dataset_confidence":0.8294,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2020-01-01","fair_score":31.25,"fair_percentile":47.04983185570162,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":289291,"name":"Matthew McGarry","orcid":"0000-0001-8430-800X","position":1,"is_corresponding":false},{"id":289292,"name":"Hillary Schwarb","orcid":"0000-0002-9454-2614","position":2,"is_corresponding":false},{"id":289293,"name":"Elijah Van Houten","orcid":"0000-0001-6565-8469","position":3,"is_corresponding":false},{"id":289294,"name":"Ryan T. Pohlig","orcid":"0000-0002-8385-8218","position":4,"is_corresponding":false},{"id":289295,"name":"Neil Roberts","orcid":"0000-0001-5538-8653","position":5,"is_corresponding":false},{"id":289296,"name":"Graham Huesmann","orcid":"0000-0002-9120-9867","position":6,"is_corresponding":false},{"id":290467,"name":"Agnieszka Z. Burzynska","orcid":null,"position":7,"is_corresponding":false},{"id":289297,"name":"Bradley P. Sutton","orcid":"0000-0002-8443-0408","position":8,"is_corresponding":false},{"id":225313,"name":"Charles H. Hillman","orcid":"0000-0002-3722-5612","position":9,"is_corresponding":false},{"id":289298,"name":"Arthur F. Kramer","orcid":"0000-0001-5870-2724","position":10,"is_corresponding":false},{"id":289299,"name":"Neal J. Cohen","orcid":"0000-0001-5556-0417","position":11,"is_corresponding":false},{"id":289300,"name":"Aron K. Barbey","orcid":"0000-0002-6092-0912","position":12,"is_corresponding":false},{"id":289301,"name":"Keith D. Paulsen","orcid":"0000-0002-6692-3196","position":13,"is_corresponding":false},{"id":289302,"name":"Curtis L. Johnson","orcid":"0000-0002-7760-131X","position":14,"is_corresponding":false},{"id":289290,"name":"Lucy V. Hiscox","orcid":"0000-0001-6296-7442","position":0,"is_corresponding":true}],"reference_count":94,"raw_metadata":null,"created_at":"2026-07-18T21:05:29.672878Z","pmid":"32931076","pmcid":"PMC7670638","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":27.7778,"fair_a":50.0,"fair_i":0.0,"fair_r":20.8333,"fair_zscore":-0.1266,"fair_rationale":{"fair_score":31.25,"has_llm":true,"taxonomy_version":"fair_taxonomy_v5","dimensions":{"F":{"name":"Findable","score":27.78,"criteria":[{"key":"f_dataset_pid","label":"Persistent identifier for the data","kind":"llm","weight":2.0,"fraction":0.5,"verdict":"partial","evidence":"github.com/mechneurolab/mre134","grounded":true,"rationale":"The paper gives a GitHub URL for the data, which is a web address not a persistent identifier scheme (DOI, Handle, ARK, etc.). [majority verdict 'partial' (3/4 passes agreed)]","anchors":["RDA-F1-01D — FAIR Data Maturity Model: 'Data is identified by a persistent identifier' (priorit","RDA-F1-02D — FAIR Data Maturity Model: 'Data is identified by a globally unique identifier'","FsF-F1-02D — F-UJI/FAIRsFAIR: 'Data is assigned a persistent identifier'"],"scored":true,"signal":null},{"key":"f_repository_named","label":"Named repository","kind":"llm","weight":2.0,"fraction":0.5,"verdict":"partial","evidence":"github.com/mechneurolab/mre134","grounded":true,"rationale":"The data are hosted on GitHub, a code repository platform that is not a dedicated data repository listed in re3data/FAIRsharing. [majority verdict 'partial' (3/4 passes agreed)]","anchors":["RDA-F4-01M — FAIR Data Maturity Model: metadata is offered so it can be harvested and indexed (","NIH DMS Policy Element 4 (NOT-OD-21-014) — name the repository where data will be archived","NSTC Desirable Characteristics of Data Repositories (2022) — 'Long-Term Sustainability', 'Reten"],"scored":true,"signal":null},{"key":"f_data_availability_statement","label":"Data-availability statement","kind":"llm","weight":2.0,"fraction":0.0,"verdict":"no","evidence":"The MRE templates are made openly available (github.com/mechneurolab/mre134) to foster collaboration across research institutions and to support robust cross-center comparisons.","grounded":false,"rationale":"The statement points to a GitHub repository URL, which is a public repository but not a repository record with a persistent identifier or accession. [downgraded to 'no' — no verifiable quote from the paper] [majority verdict 'no' (3/4 passes agreed)]","anchors":["Colavizza, Hrynaszkiewicz, Staden, Whitaker & McGillivray (2020), 'The citation advantage of li","Springer Nature research data policy — Data Availability Statements: standard statement templat","RDA-F3-01M — metadata clearly and explicitly includes the identifier of the data it describes"],"scored":false,"signal":null},{"key":"f_discovery_metadata","label":"Description of the dataset as an object","kind":"llm","weight":2.0,"fraction":0.0,"verdict":"no","evidence":"Dimensions of the normalized MRE templates were 91 × 109 × 91 voxels, and the final voxel-size was 2 mm × 2 mm × 2 mm.","grounded":false,"rationale":"The dataset extent is described in running prose, not as an itemised inventory. [downgraded to 'no' — no verifiable quote from the paper] [majority verdict 'no' (2/4 passes agreed)]","anchors":["RDA-F2-01M — 'Rich metadata is provided to allow discovery' (priority Essential)","FsF-F2-01M — F-UJI: 'Metadata includes descriptive core elements to support data findability'","FsF-R1-01MD — F-UJI: 'Metadata specifies the content of the data'"],"scored":false,"signal":null},{"key":"f_dataset_cited","label":"Dataset formally cited","kind":"llm","weight":1.0,"fraction":0.5,"verdict":"partial","evidence":"The templates are made openly available (github.com/mechneurolab/mre134)","grounded":true,"rationale":"The dataset's URL appears only in the body text (abstract and data availability statement), not in the reference list. [majority verdict 'partial' (3/4 passes agreed)]","anchors":["FORCE11 Joint Declaration of Data Citation Principles (2014) — data should be cited as a first-","RDA-F3-01M — metadata clearly and explicitly includes the identifier of the data it describes","FsF-F3-01M — F-UJI: 'Metadata includes the identifier of the data it describes'"],"scored":true,"signal":null}]},"A":{"name":"Accessible","score":50.0,"criteria":[{"key":"a_data_openly_accessible","label":"Access route free of preconditions","kind":"llm","weight":2.0,"fraction":0.5,"verdict":"partial","evidence":"The MRE templates are made openly available (github.com/mechneurolab/mre134)","grounded":false,"rationale":"The text gives a direct GitHub URL with no stated precondition such as registration, embargo, or request. [downgraded to 'partial' — no verifiable quote from the paper]","anchors":["RDA-A1.1-01D — 'Data is accessible through a free access protocol'","FsF-A1-01M — F-UJI: 'Metadata contains access level and access conditions of the data'","NSTC Desirable Characteristics of Data Repositories (2022) — 'Free and Easy Access'"],"scored":true,"signal":null},{"key":"a_access_conditions_stated","label":"Access level labelled","kind":"llm","weight":1.0,"fraction":1.0,"verdict":"yes","evidence":"The MRE templates are made openly available","grounded":true,"rationale":"The paper explicitly labels the data as 'openly available', which is a natural-language equivalent of the access level 'open access'.","anchors":["FsF-A1-01M — F-UJI: 'Metadata contains access level and access conditions of the data'","RDA-A1-01M — metadata contains information to enable the user to get access to the data","COAR Controlled Vocabularies — Access Rights v1.0 (open / embargoed / restricted / metadata-onl"],"scored":false,"signal":null},{"key":"a_controlled_access_for_sensitive","label":"Gatekeeper for sensitive data","kind":"llm","weight":0.5,"fraction":0.0,"verdict":"no","evidence":null,"grounded":false,"rationale":"The data are openly available and the paper does not name any gatekeeper, institutional or personal, for access.","anchors":["NIH Genomic Data Sharing Policy (NOT-OD-14-124) — controlled-access via a Data Access Committee","RDA-A1.2-01D — 'Data is accessible through an access protocol that supports authentication and ","NIH DMS Policy Element 5 (NOT-OD-21-014) — Access, Distribution, or Reuse Considerations (conse"],"scored":false,"signal":null},{"key":"a_timeline_retention","label":"Availability timing & retention","kind":"llm","weight":0.5,"fraction":0.0,"verdict":"no","evidence":"The MRE templates are made openly available (github.com/mechneurolab/mre134)","grounded":false,"rationale":"The paper states the data are available now but gives no persistence commitment. [downgraded to 'no' — no verifiable quote from the paper] [majority verdict 'no' (3/4 passes agreed)]","anchors":["NIH DMS Plan Element 4 (NOT-OD-21-014) — Data Preservation, Access, and Associated Timelines","NSTC Desirable Characteristics (2022), Organizational Infrastructure: 'Retention Policy'","RDA-A2-01M — 'Metadata is guaranteed to remain available after data is no longer available'"],"scored":false,"signal":null}]},"I":{"name":"Interoperable","score":0.0,"criteria":[{"key":"i_open_nonproprietary_format","label":"Open file format","kind":"llm","weight":1.0,"fraction":0.0,"verdict":"no","evidence":null,"grounded":false,"rationale":"No file format token for the released data is mentioned anywhere in the text.","anchors":["FsF-R1.3-02D — F-UJI: 'Data is available in a file format recommended by the target research co","RDA-R1.3-02D — data is expressed in a machine-understandable community standard","RDA-I1-01D — data uses a knowledge representation expressed in a standardised format"],"scored":true,"signal":null},{"key":"i_community_standard_vocabulary","label":"Community standard / vocabulary","kind":"llm","weight":1.0,"fraction":0.0,"verdict":"no","evidence":null,"grounded":false,"rationale":"The paper uses standard templates (MNI152, ICBM) but does not name a data/metadata community standard (checklist, ontology, schema) from FAIRsharing, nor a manuscript reporting guideline. [majority verdict 'no' (2/4 passes agreed)]","anchors":["RDA-R1.3-01M — 'Metadata complies with a community standard' (priority Essential)","RDA-R1.3-01D — 'Data complies with a community standard'","RDA-I2-01M — '(Meta)data use vocabularies that follow FAIR principles'"],"scored":false,"signal":null},{"key":"i_qualified_references","label":"Identifiers for the resources the data depend on","kind":"llm","weight":0.5,"fraction":0.0,"verdict":"no","evidence":null,"grounded":false,"rationale":"The paper names external resources (MNI template, atlases) but does not provide any identifier (DOI, accession, RRID) for them.","anchors":["RDA-I3-01M — '(meta)data include references to other (meta)data'","RDA-I3-03M — 'metadata includes qualified references to other metadata'","FsF-I3-01M — F-UJI: 'Metadata includes links between the data and its related entities'"],"scored":false,"signal":null}]},"R":{"name":"Reusable","score":20.83,"criteria":[{"key":"r_reuse_license","label":"Reuse licence","kind":"llm","weight":2.0,"fraction":0.0,"verdict":"no","evidence":null,"grounded":false,"rationale":"The paper does not state any license or reuse terms for the data; the CC-BY license applies only to the article.","anchors":["RDA-R1.1-01M — 'Metadata includes information about the licence under which the data can be reu","RDA-R1.1-02M — 'Metadata refers to a standard reuse licence'","RDA-R1.1-03M — 'Metadata refers to a machine-understandable reuse licence'"],"scored":true,"signal":null},{"key":"r_provenance_methods","label":"Provenance of the data","kind":"llm","weight":1.0,"fraction":1.0,"verdict":"yes","evidence":"Freesurfer v6.0; (Fischl et al., 2002)","grounded":true,"rationale":"The paper names specific software versions and tools used to produce the data (Freesurfer v6.0, ANTS, SPM12 v7487).","anchors":["RDA-R1.2-01M — 'Metadata includes provenance information according to community- specific standa","FsF-R1.2-01M — F-UJI: 'Metadata includes provenance information about data creation or generati","W3C PROV-O (W3C Recommendation, 2013) — the entity/activity/agent model of provenance"],"scored":false,"signal":null},{"key":"r_documentation_codebook","label":"Documentation / codebook","kind":"llm","weight":1.0,"fraction":0.0,"verdict":"no","evidence":null,"grounded":false,"rationale":"No documentation object (README, codebook) is named, and no variable-definition table exists in the article. [majority verdict 'no' (2/4 passes agreed)]","anchors":["RDA-R1-01M — '(Meta)data are richly described with a plurality of accurate and relevant attribu","FsF-R1-01MD — F-UJI: 'Metadata specifies the content of the data'","NIH DMS Policy Element 3 (NOT-OD-21-014) — Standards (documentation and metadata to accompany t"],"scored":false,"signal":null},{"key":"r_versioning","label":"Snapshot identified","kind":"llm","weight":0.5,"fraction":0.0,"verdict":"no","evidence":null,"grounded":false,"rationale":"No version token or date is given for the data snapshot.","anchors":["DataCite Metadata Schema 4.6 — the 'Version' property","RDA-R1.2-01M — provenance information (which version was used is provenance)","NSTC Desirable Characteristics of Data Repositories (2022) — 'Provenance', 'Retention Policy'"],"scored":true,"signal":null},{"key":"x_code_availability","label":"Analysis code available","kind":"llm","weight":1.0,"fraction":0.0,"verdict":"no","evidence":null,"grounded":false,"rationale":"The paper does not provide any locator for the study's own code; only third-party tools are named.","anchors":["NIH DMS Policy Element 2 (NOT-OD-21-014) — 'Related Tools, Software and/or Code'","FAIR4RS Principles v1.0 (Chue Hong et al., 2022; RDA/FORCE11/ReSA) — FAIR Principles for Resear","FORCE11 Software Citation Principles (Smith, Katz & Niemeyer, 2016, PeerJ CS 2:e86)"],"scored":true,"signal":null},{"key":"x_funding_attribution","label":"Funder and award number","kind":"llm","weight":0.5,"fraction":0.5,"verdict":"partial","evidence":"R01-AG058853, R01-EB027577, U01-NS112120, R01-MH062500, R01-EB001981, MR/K026992/1","grounded":false,"rationale":"The paper lists multiple grant numbers associated with named funders. [downgraded to 'partial' — no verifiable quote from the paper] [majority verdict 'partial' (2/4 passes agreed)]","anchors":["DataCite Metadata Schema 4.6 — 'FundingReference' property (funderName, funderIdentifier, award","Crossref Funder Registry — canonical funder identifiers for funding metadata","RDA-F2-01M — rich metadata provided to allow discovery (funding is part of the descriptive reco"],"scored":true,"signal":null}]}},"actions":[{"key":"r_reuse_license","dimension":"R","label":"Reuse licence","action":"Attach a standard, machine-readable open licence to the deposit — CC0 or CC BY, which is what Horizon Europe and most funders expect — and print the licence identifier in the paper. 'Free to use' is not a licence: it grants nothing a reuser's institution can rely on.","anchors":["yes","partial","no"],"verdict":"no","current":0.0,"evidence":null,"why":"The paper does not state any license or reuse terms for the data; the CC-BY license applies only to the article.","gain":16.67,"priority":"essential","scored":true},{"key":"f_dataset_pid","dimension":"F","label":"Persistent identifier for the data","action":"Mint or cite a persistent identifier for the dataset — a repository DOI or an accession from a registered repository — and print it in the paper. A bare URL is not persistent: it is the single most common cause of a dead data link five years after publication. For neuroimaging data, deposit in OpenNeuro or NeuroVault.","anchors":["yes","partial","no"],"verdict":"partial","current":0.5,"evidence":"github.com/mechneurolab/mre134","why":"The paper gives a GitHub URL for the data, which is a web address not a persistent identifier scheme (DOI, Handle, ARK, etc.). [majority verdict 'partial' (3/4 passes agreed)]","gain":8.33,"priority":"essential","scored":true},{"key":"f_repository_named","dimension":"F","label":"Named repository","action":"Deposit the data in a repository registered in re3data/FAIRsharing (a domain repository such as GEO, SRA, dbGaP, PRIDE, or a generalist such as Zenodo, Dryad, Dataverse) and name it explicitly in the paper. A lab website is not an archive: it has no retention commitment and no accession. For neuroimaging data, deposit in OpenNeuro or NeuroVault.","anchors":["yes","partial","no"],"verdict":"partial","current":0.5,"evidence":"github.com/mechneurolab/mre134","why":"The data are hosted on GitHub, a code repository platform that is not a dedicated data repository listed in re3data/FAIRsharing. [majority verdict 'partial' (3/4 passes agreed)]","gain":8.33,"priority":"essential","scored":true},{"key":"a_data_openly_accessible","dimension":"A","label":"Access route free of preconditions","action":"Remove the precondition or justify it. Release the data at publication with no embargo, no registration wall, and no approval step — NIH's zero-embargo public- access rule (NOT-OD-25-101) has already made 'available at publication' the federal baseline for the article; the data should not lag behind it. For neuroimaging data, deposit in OpenNeuro or NeuroVault.","anchors":["yes","partial","no"],"verdict":"partial","current":0.5,"evidence":"The MRE templates are made openly available (github.com/mechneurolab/mre134)","why":"The text gives a direct GitHub URL with no stated precondition such as registration, embargo, or request. [downgraded to 'partial' — no verifiable quote from the paper]","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":"No file format token for the released data is mentioned anywhere in the text.","gain":8.33,"priority":"important","scored":true},{"key":"x_code_availability","dimension":"R","label":"Analysis code available","action":"Publish the analysis code in a public forge, archive a tagged release with a DOI (Zenodo/Software Heritage), and cite that DOI in the paper. NIH DMS Element 2 asks for the tools and code, not only the data — and 'available on request' is not a locator. Archive the analysis code in a versioned repository (GitHub + a Zenodo release DOI).","anchors":["yes","partial","no"],"verdict":"no","current":0.0,"evidence":null,"why":"The paper does not provide any locator for the study's own code; only third-party tools are named.","gain":8.33,"priority":"important","scored":true},{"key":"f_dataset_cited","dimension":"F","label":"Dataset formally cited","action":"Cite the dataset in the reference list like a publication — creator, year, title, repository, DOI/accession — and cite it in-text where it is used. Only a reference- list entry is machine-readable to Crossref/DataCite, and only a citation lets the data earn credit. Cite the neuroimaging repository accession (e.g. from OpenNeuro or NeuroVault) in the reference list.","anchors":["yes","partial","no"],"verdict":"partial","current":0.5,"evidence":"The templates are made openly available (github.com/mechneurolab/mre134)","why":"The dataset's URL appears only in the body text (abstract and data availability statement), not in the reference list. [majority verdict 'partial' (3/4 passes agreed)]","gain":4.17,"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":"No version token or date is given for the data snapshot.","gain":4.17,"priority":"useful","scored":true},{"key":"x_funding_attribution","dimension":"R","label":"Funder and award number","action":"State the funder AND the award number in the paper, and put them in the dataset's FundingReference metadata. A funder name alone cannot be linked back to the award, so the funding provenance of the data is lost the moment the paper is indexed.","anchors":["yes","partial","no"],"verdict":"partial","current":0.5,"evidence":"R01-AG058853, R01-EB027577, U01-NS112120, R01-MH062500, R01-EB001981, MR/K026992/1","why":"The paper lists multiple grant numbers associated with named funders. [downgraded to 'partial' — no verifiable quote from the paper] [majority verdict 'partial' (2/4 passes agreed)]","gain":2.08,"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":"no","current":0.0,"evidence":"The MRE templates are made openly available (github.com/mechneurolab/mre134) to foster collaboration across research institutions and to support robust cross-center comparisons.","why":"The statement points to a GitHub repository URL, which is a public repository but not a repository record with a persistent identifier or accession. [downgraded to 'no' — no verifiable quote from the paper] [majority verdict 'no' (3/4 passes agreed)]","gain":0.0,"priority":"essential","scored":false},{"key":"f_discovery_metadata","dimension":"F","label":"Description of the dataset as an object","action":"Add a 'Data Records' section: itemise every file in the deposit and every variable or sample it holds, with counts and units. Describe the dataset as an object in its own right, not as a by-product of the findings — this is what makes it discoverable to someone who is not looking for your paper.","anchors":["yes","partial","no"],"verdict":"no","current":0.0,"evidence":"Dimensions of the normalized MRE templates were 91 × 109 × 91 voxels, and the final voxel-size was 2 mm × 2 mm × 2 mm.","why":"The dataset extent is described in running prose, not as an itemised inventory. [downgraded to 'no' — no verifiable quote from the paper] [majority verdict 'no' (2/4 passes agreed)]","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 uses standard templates (MNI152, ICBM) but does not name a data/metadata community standard (checklist, ontology, schema) from FAIRsharing, nor a manuscript reporting guideline. [majority verdict 'no' (2/4 passes agreed)]","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. It is the cheapest single thing that makes a dataset usable by someone who was not in the lab, and a table buried in the article does not travel with the data.","anchors":["yes","partial","no"],"verdict":"no","current":0.0,"evidence":null,"why":"No documentation object (README, codebook) is named, and no variable-definition table exists in the article. [majority verdict 'no' (2/4 passes agreed)]","gain":0.0,"priority":"important","scored":false},{"key":"a_controlled_access_for_sensitive","dimension":"A","label":"Gatekeeper for sensitive data","action":"Route sensitive data through an institutional gatekeeper — deposit in a controlled- access repository (dbGaP, EGA) with a Data Access Committee and a published DUA — rather than through the corresponding author's inbox. An author-gated dataset dies with the author's email address, and 'on reasonable request' has been shown repeatedly not to yield data.","anchors":["yes","partial","no"],"verdict":"no","current":0.0,"evidence":null,"why":"The data are openly available and the paper does not name any gatekeeper, institutional or personal, for access.","gain":0.0,"priority":"useful","scored":false},{"key":"i_qualified_references","dimension":"I","label":"Identifiers for the resources the data depend on","action":"Cite by identifier every resource the data depend on — the source datasets' accessions, the reference build (GRCh38 / GCA_000001405.28), the cohort application number, the code DOI — and register those relations on the dataset record (IsDerivedFrom, IsSupplementTo). A name is not a link: it cannot be resolved, versioned, or followed by a machine.","anchors":["yes","partial","no"],"verdict":"no","current":0.0,"evidence":null,"why":"The paper names external resources (MNI template, atlases) but does not provide any identifier (DOI, accession, RRID) for them.","gain":0.0,"priority":"useful","scored":false},{"key":"a_timeline_retention","dimension":"A","label":"Availability timing & retention","action":"State when the data become available AND how long they will be retained — cite the repository's preservation policy. NIH DMS Element 4 asks for both; most papers give neither.","anchors":["yes","partial","no"],"verdict":"no","current":0.0,"evidence":"The MRE templates are made openly available (github.com/mechneurolab/mre134)","why":"The paper states the data are available now but gives no persistence commitment. [downgraded to 'no' — no verifiable quote from the paper] [majority verdict 'no' (3/4 passes agreed)]","gain":0.0,"priority":"useful","scored":false}],"suggestions":["Attach a standard, machine-readable open licence to the deposit — CC0 or CC BY, which is what Horizon Europe and most funders expect — and print the licence identifier in the paper. 'Free to use' is not a licence: it grants nothing a reuser's institution can rely on.","Mint or cite a persistent identifier for the dataset — a repository DOI or an accession from a registered repository — and print it in the paper. A bare URL is not persistent: it is the single most common cause of a dead data link five years after publication. For neuroimaging data, deposit in OpenNeuro or NeuroVault.","Deposit the data in a repository registered in re3data/FAIRsharing (a domain repository such as GEO, SRA, dbGaP, PRIDE, or a generalist such as Zenodo, Dryad, Dataverse) and name it explicitly in the paper. A lab website is not an archive: it has no retention commitment and no accession. For neuroimaging data, deposit in OpenNeuro or NeuroVault.","Remove the precondition or justify it. Release the data at publication with no embargo, no registration wall, and no approval step — NIH's zero-embargo public- access rule (NOT-OD-25-101) has already made 'available at publication' the federal baseline for the article; the data should not lag behind it. For neuroimaging data, deposit in OpenNeuro or NeuroVault.","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."],"model":"deepseek/deepseek-v4-flash","agent_version":"fair_agent_v8","fulltext_source":"unpaywall_pdf"},"fair_model":"deepseek/deepseek-v4-flash","fair_agent_version":"fair_agent_v8","fair_fulltext_source":"unpaywall_pdf","fair_has_llm":true,"fair_computed_at":"2026-07-20T11:07:27.483972Z","clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}