{"doi":"10.1038/s41597-020-00680-2","title":"A naturalistic neuroimaging database for understanding the brain using ecological stimuli","abstract":"Neuroimaging has advanced our understanding of human psychology using reductionist stimuli that often do not resemble information the brain naturally encounters. It has improved our understanding of the network organization of the brain mostly through analyses of 'resting-state' data for which the functions of networks cannot be verifiably labelled. We make a 'Naturalistic Neuroimaging Database' (NNDb v1.0) publically available to allow for a more complete understanding of the brain under more ecological conditions during which networks can be labelled. Eighty-six participants underwent behavioural testing and watched one of 10 full-length movies while functional magnetic resonance imaging was acquired. Resulting timeseries data are shown to be of high quality, with good signal-to-noise ratio, few outliers and low movement. Data-driven functional analyses provide further evidence of data quality. They also demonstrate accurate timeseries/movie alignment and how movie annotations might be used to label networks. The NNDb can be used to answer questions previously unaddressed with standard neuroimaging approaches, progressing our knowledge of how the brain works in the real world.","journal":"Scientific Data","year":2020,"id":118323,"datarank":2.57906779101699,"base_score":4.7535901911063645,"endowment":4.7535901911063645,"self_citation_contribution":0.7130385286659547,"citation_network_contribution":1.8660292623510353,"self_endowment_contribution":0.7130385286659547,"citer_contribution":1.8660292623510353,"corpus_percentile":91.56030014697919,"corpus_rank":1092,"citation_count":115,"citer_count":93,"citers_with_citation_signal":61,"citers_with_endowment":61,"datacite_reuse_total":0,"is_dataset":true,"is_dataset_confidence":0.953,"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":81.25,"fair_percentile":98.68541730357688,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":550298,"name":"Jiawen Huang","orcid":"0000-0003-1362-0412","position":1,"is_corresponding":false},{"id":551244,"name":"Florin Gheorghiu","orcid":null,"position":2,"is_corresponding":false},{"id":550299,"name":"Stefanie Meliß","orcid":"0000-0003-2408-3309","position":3,"is_corresponding":false},{"id":550300,"name":"Jeremy I Skipper","orcid":"0000-0002-5503-764X","position":4,"is_corresponding":false},{"id":550297,"name":"Sarah Aliko","orcid":"0000-0001-7269-5778","position":0,"is_corresponding":true}],"reference_count":132,"raw_metadata":null,"created_at":"2026-07-18T23:13:58.531532Z","pmid":"33051448","pmcid":"PMC7555491","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":75.0,"fair_i":40.0,"fair_r":62.5,"fair_zscore":1.8524,"fair_rationale":{"fair_score":81.25,"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/10.18112/openneuro.ds002837.v1.1.1","grounded":true,"rationale":"The paper provides a DOI for the dataset in the Data Records section. [majority verdict 'yes' (4/5 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":1.0,"verdict":"yes","evidence":"Resulting files are available from the OpenNeuro platform","grounded":true,"rationale":"OpenNeuro is a named data repository for neuroimaging data. [majority verdict 'yes' (3/5 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":0.5,"verdict":"partial","evidence":"Resulting files are available from the OpenNeuro platform for sharing fMRI (and other neuroimaging) data at https://doi.org/10.18112/openneuro.ds002837.v1.1.1 (dataset accession number ds002837).","grounded":false,"rationale":"The statement points to a repository record with a DOI and repository name. [downgraded to 'partial' — no verifiable quote from the paper] [majority verdict 'partial' (3/5 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":1.0,"verdict":"yes","evidence":"Data Records","grounded":true,"rationale":"The paper has a 'Data Records' section that itemises the files and their locations. [majority verdict 'yes' (4/5 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":1.0,"verdict":"yes","evidence":"Aliko, S. et al. Naturalistic Neuroimaging Database. OpenNeuro https://doi.org/10.18112/OPENNEURO.DS002837.V1.1.1 (2020).","grounded":true,"rationale":"The dataset appears as a reference-list entry (reference 100). 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[majority verdict 'no' (4/5 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":40.0,"criteria":[{"key":"i_open_nonproprietary_format","label":"Open file format","kind":"llm","weight":1.0,"fraction":1.0,"verdict":"yes","evidence":"comma-separated value (CSV) files","grounded":true,"rationale":"The paper names CSV and NIfTI, both open formats.","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":"No community standard for data or metadata (e.g., MIAME, BIDS) is explicitly named in the paper. [majority verdict 'no' (4/5 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 does not provide an identifier (accession, DOI, RRID) for any external resource that the data depend on or derive from. [majority verdict 'no' (3/5 passes agreed)]","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":62.5,"criteria":[{"key":"r_reuse_license","label":"Reuse licence","kind":"llm","weight":2.0,"fraction":0.0,"verdict":"no","evidence":null,"grounded":false,"rationale":"No license for the data is stated in the paper; the article's CC BY license does not apply to the data.","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":"Functional and anatomical images were acquired on a 1.5 T Siemens MAGNETOM Avanto with a 32 channel head coil","grounded":true,"rationale":"The paper names the specific scanner and sequence used to produce the data. [majority verdict 'yes' (4/5 passes agreed)]","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":1.0,"verdict":"yes","evidence":"A README file there provides a description of the available content.","grounded":true,"rationale":"A documentation object (README) is named as accompanying the data.","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":0.5,"verdict":"partial","evidence":"NNDb v1.0","grounded":false,"rationale":"The paper states a version token for the database in the abstract. [downgraded to 'partial' — no verifiable quote from the paper] [majority verdict 'partial' (3/5 passes agreed)]","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":1.0,"verdict":"yes","evidence":"Scripts used in this manuscript are available at https://github.com/lab-lab/nndb","grounded":true,"rationale":"A machine-resolvable code repository URL is given. [majority verdict 'yes' (4/5 passes agreed)]","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":1.0,"verdict":"yes","evidence":"EPSRC EP/M026965/1","grounded":true,"rationale":"Grant numbers are attached to named funders.","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":"No license for the data is stated in the paper; the article's CC BY license does not apply to the data.","gain":16.67,"priority":"essential","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":"partial","current":0.5,"evidence":"NNDb v1.0","why":"The paper states a version token for the database in the abstract. 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[majority verdict 'no' (4/5 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":"participants provided written informed consent to take part in the study and share their anonymised data.","why":"The data are from human subjects but no gatekeeper is named; the data are openly shared without access control.","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 does not provide an identifier (accession, DOI, RRID) for any external resource that the data depend on or derive from. [majority verdict 'no' (3/5 passes agreed)]","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":null,"why":"No sentence in the paper states how long the data will remain available or mentions a retention period. [majority verdict 'no' (4/5 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.","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.","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.","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.","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."],"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":"2026-07-20T11:02:25.296389Z","clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}