{"success":true,"database":"eegdash","data":{"_id":"6953f4249276ef1ee07a344e","dataset_id":"ds006459","associated_paper_doi":null,"authors":["Jessica E. Anderson","Laura Carlton","Sreekanth Kura","Walker J. O'Brien","De'Ja Rogers","Parisa Rahimi","Parya Y. Farzam","Muhammad H. Zaman","David A. Boas","Meryem A. Yücel"],"bids_version":"1.8.0","contact_info":["Jessica E Anderson"],"contributing_labs":null,"data_processed":false,"dataset_doi":"doi:10.18112/openneuro.ds006459.v1.0.0","datatypes":["fnirs"],"demographics":{"subjects_count":17,"ages":[24,26,24,27,23,31,21,19,23,22,36,23,29,23,30,30,27],"age_min":19,"age_max":36,"age_mean":25.764705882352942,"species":null,"sex_distribution":{"f":8,"m":9},"handedness_distribution":{"l":2,"r":14}},"experimental_modalities":null,"external_links":{"source_url":"https://openneuro.org/datasets/ds006459","osf_url":null,"github_url":null,"paper_url":null},"funding":["This project was supported by NIH NEW grant U01-EB 029856 and Boston University research funds."],"ingestion_fingerprint":"b6bd3b36bdca9936f2801be87ffa687ed56695cedae8e7f7ef67cf5025837750","license":"CC0","n_contributing_labs":null,"name":"High-DensityvSparsefNIRS_WordColorStroop_Sparse_Anderson_2025","readme":null,"recording_modality":["fnirs"],"senior_author":"Meryem A. Yücel","sessions":["1"],"size_bytes":176977615,"source":"openneuro","study_design":null,"study_domain":null,"tasks":["WordStroop"],"timestamps":{"digested_at":"2026-04-22T12:29:27.922696+00:00","dataset_created_at":"2025-07-08T17:17:42.985Z","dataset_modified_at":"2025-07-08T17:28:20.000Z"},"total_files":17,"storage":{"backend":"s3","base":"s3://openneuro.org/ds006459","raw_key":"dataset_description.json","dep_keys":["CHANGES","participants.json","participants.tsv"]},"tagger_meta":{"config_hash":"3557b68bca409f28","metadata_hash":"fd9a5f30348a383b","model":"openai/gpt-5.2","tagged_at":"2026-04-07T09:32:40.872789+00:00"},"tags":{"pathology":["Healthy"],"modality":["Visual"],"type":["Attention"],"confidence":{"pathology":0.6,"modality":0.7,"type":0.7},"reasoning":{"few_shot_analysis":"Most similar few-shot example by paradigm/construct is the DPX cognitive control task dataset (few-shot: \"EEG: DPX Cog Ctl Task in Acute Mild TBI\"), which is labeled Type=Attention because it targets cognitive control/attention demands. A Word-Color Stroop task is likewise a classic cognitive control/attention paradigm (incongruent vs congruent conditions). For Modality, the schizophrenia visual discrimination and multiple other few-shots show that when stimuli are screen-based visual items, Modality=Visual is used. None of the few-shot examples suggest re-labeling pathology without explicit clinical recruitment; they consistently rely on stated diagnoses.","metadata_analysis":"Key metadata facts available are sparse but include task name and paradigm in the title.\n- Title includes the paradigm: \"High-DensityvSparsefNIRS_WordColorStroop_Sparse_Anderson_2025\" (contains \"WordColorStroop\").\n- Tasks field: \"WordStroop\".\n- Participants overview provides demographics only: \"Subjects: 17\" and \"Age range: 19-36\" with no mention of any diagnosis or patient group.\nThese support: (a) no explicitly recruited clinical population; (b) Stroop (typically visual word/color stimuli) as the main task.","paper_abstract_analysis":"No useful paper information.","evidence_alignment_check":"Pathology:\n- Metadata says: only demographics are given (e.g., \"Subjects: 17\"; \"Age range: 19-36\"), with no diagnosis/condition stated.\n- Few-shot pattern suggests: when no clinical recruitment is described, label as Healthy.\n- Alignment: ALIGN (no conflict).\n\nModality:\n- Metadata says: paradigm is \"WordColorStroop\" / task \"WordStroop\".\n- Few-shot pattern suggests: screen-based discrimination/word tasks are Visual.\n- Alignment: ALIGN.\n\nType:\n- Metadata says: \"WordColorStroop\" / \"WordStroop\" indicates Stroop interference/cognitive control.\n- Few-shot pattern suggests: cognitive control/attention-demanding tasks (e.g., DPX) map to Type=Attention.\n- Alignment: ALIGN.","decision_summary":"Top-2 candidates per category with head-to-head selection:\n\nPathology:\n1) Healthy — Evidence: no clinical terms; only demographics (\"Subjects: 17\"; \"Age range: 19-36\"). Matches few-shot convention that non-clinical volunteer samples are Healthy.\n2) Unknown — Could be considered due to lack of explicit 'healthy' wording.\nDecision: Healthy (stronger because absence of any clinical recruitment language and typical Stroop sampling).\nConfidence basis: limited explicit text, but clear lack of diagnosis.\n\nModality:\n1) Visual — Evidence: \"WordColorStroop\" / \"WordStroop\" strongly implies visually presented words/colors.\n2) Other — Possible if auditory Stroop variant, but not indicated.\nDecision: Visual.\nConfidence basis: task name directly points to visual word/color stimuli.\n\nType:\n1) Attention — Evidence: Stroop is canonical selective attention/conflict monitoring/cognitive control paradigm; guided by few-shot DPX cognitive control labeled Attention.\n2) Decision-making — Could involve response selection, but primary construct is interference/attention control rather than value/choice policy.\nDecision: Attention.\nConfidence basis: task paradigm strongly indicates attention/cognitive control, but metadata lacks task description details."}},"computed_title":"High-DensityvSparsefNIRS_WordColorStroop_Sparse_Anderson_2025","nchans_counts":[{"val":120,"count":17}],"sfreq_counts":[{"val":24.414062499999996,"count":15},{"val":24.414062500000004,"count":1},{"val":24.414062499999993,"count":1}],"stats_computed_at":"2026-04-22T23:16:00.311602+00:00","total_duration_s":null,"canonical_name":null,"name_confidence":0.72,"name_meta":{"suggested_at":"2026-04-14T10:18:35.343Z","model":"openai/gpt-5.2 + openai/gpt-5.4-mini + deterministic_fallback"},"name_source":"author_year","author_year":"Anderson2025_Sparse"}}