{"success":true,"database":"eegdash","data":{"_id":"69d16e04897a7725c66f4c48","dataset_id":"ds007420","associated_paper_doi":null,"authors":["Gao, Yuanyuan","Rogers, De’Ja","von Lühmann, Alexander","Ortega-Martinez, Antonio","Boas, David","Yücel, Meryem"],"bids_version":"1.7.1","contact_info":["Shibo Zhou"],"contributing_labs":null,"data_processed":true,"dataset_doi":"doi:10.18112/openneuro.ds007420.v1.0.2","datatypes":["fnirs"],"demographics":{"subjects_count":12,"ages":[],"age_min":null,"age_max":null,"age_mean":null,"species":null,"sex_distribution":null,"handedness_distribution":null},"experimental_modalities":null,"external_links":{"source_url":"https://openneuro.org/datasets/ds007420","osf_url":null,"github_url":null,"paper_url":null},"funding":["NIH BRAIN Initiative (Grant No. 1U01EB029856-01)"],"ingestion_fingerprint":"00635c7895cb03023516c50fa5bbfe4e8d35ce3f44b8be55c11e12a53b4203b2","license":"CC0","n_contributing_labs":null,"name":"A Light Weight Multi-Distance fNIRS Dataset for Ball-Squeezing Task and Purposeful Motion Artifact Creation Task","readme":null,"recording_modality":["fnirs"],"senior_author":"Yücel, Meryem","sessions":["01","02","03"],"size_bytes":587945590,"source":"openneuro","storage":{"backend":"s3","base":"s3://openneuro.org/ds007420","raw_key":"dataset_description.json","dep_keys":["CHANGES","datacite.yml","participants.tsv"]},"study_design":null,"study_domain":null,"tasks":["BallSqueezing","Motion","Rest","Resting"],"timestamps":{"digested_at":"2026-04-22T12:30:16.399530+00:00","dataset_created_at":"2026-02-14T18:09:31.926Z","dataset_modified_at":"2026-03-26T14:39:52.000Z"},"total_files":60,"computed_title":"A Light Weight Multi-Distance fNIRS Dataset for Ball-Squeezing Task and Purposeful Motion Artifact Creation Task","nchans_counts":[{"val":200,"count":60}],"sfreq_counts":[{"val":8.719308035714286,"count":52},{"val":11.625744047619047,"count":4},{"val":8.719308035714288,"count":3},{"val":11.625744047619051,"count":1}],"stats_computed_at":"2026-04-22T23:16:00.312764+00:00","total_duration_s":null,"tagger_meta":{"config_hash":"3557b68bca409f28","metadata_hash":"eac2234d90d6e7d2","model":"openai/gpt-5.2","tagged_at":"2026-04-07T09:32:40.872789+00:00"},"tags":{"pathology":["Healthy"],"modality":["Motor"],"type":["Motor"],"confidence":{"pathology":0.8,"modality":0.7,"type":0.8},"reasoning":{"few_shot_analysis":"Most similar few-shot by task purpose is the “EEG Motor Movement/Imagery Dataset” example (labeled Type=Motor). That example shows the catalog convention that when the study is centered on movement execution/imagery, the Type should be “Motor” (even if cues may be visual). This guides selecting Type=Motor here because the dataset’s named task is “Ball-Squeezing”. Few-shot examples do not provide an fNIRS-specific modality mapping; thus Modality must be inferred primarily from this dataset’s task names.","metadata_analysis":"Key metadata facts:\n1) Title explicitly states the paradigm: \"Ball-Squeezing Task\" and \"Purposeful Motion Artifact Creation Task\".\n2) Tasks list includes motor and baseline conditions: tasks = [\"BallSqueezing\", \"Motion\", \"Rest\", \"Resting\"].\n3) Participants: \"Subjects: 12\" with no mention of any diagnosis or patient group.\nThese support: (a) a non-clinical cohort (no pathology specified), and (b) a motor-task-focused design with additional rest/motion-artifact runs.","paper_abstract_analysis":"No useful paper information.","evidence_alignment_check":"Pathology:\n- Metadata says: \"Subjects: 12\" with no clinical descriptors; title contains no disorder terms.\n- Few-shot pattern suggests: in absence of a named clinical population, label as Healthy.\n- Alignment: ALIGN.\n\nModality:\n- Metadata says: tasks include \"BallSqueezing\" and \"Motion\" (purposeful motion artifact), plus \"Rest/Resting\"; no explicit sensory stimulus channel (visual/auditory) is described.\n- Few-shot pattern suggests: motor-centric tasks generally map to Motor-related labeling (and Motor as a Type when movement is the focus). However, one motor example used Modality=Visual because targets were visually presented; that specific visual-cue fact is not present here.\n- Alignment: PARTIAL / UNCERTAIN (task is motor, but stimulus modality/cue channel is not specified).\n\nType:\n- Metadata says: title includes \"Ball-Squeezing Task\" and a \"Motion Artifact Creation Task\"; tasks list includes \"BallSqueezing\".\n- Few-shot pattern suggests: movement execution/imagery studies are labeled Type=Motor.\n- Alignment: ALIGN.","decision_summary":"Top-2 candidates and selection:\n\nPathology:\n- Candidate 1: Healthy — Evidence: no diagnosis mentioned anywhere (\"Subjects: 12\"; no patient/control grouping; title has no clinical terms).\n- Candidate 2: Unknown — Would apply if population were not characterizable, but here the absence of any clinical recruitment language most strongly fits a normative cohort.\n-> Final: Healthy. Confidence supported by multiple metadata absences plus explicit generic subject count.\n\nModality:\n- Candidate 1: Motor — Evidence: \"Ball-Squeezing Task\"; tasks include \"BallSqueezing\" and \"Motion\".\n- Candidate 2: Resting State — Evidence: tasks include \"Rest\" and \"Resting\".\nHead-to-head: The dataset title foregrounds the ball-squeezing and motion-artifact tasks, indicating the primary paradigm is movement-related rather than pure rest.\n-> Final: Motor. Confidence limited because the sensory cue modality (visual/auditory) is not described.\n\nType:\n- Candidate 1: Motor — Evidence: \"Ball-Squeezing Task\"; tasks include \"BallSqueezing\".\n- Candidate 2: Resting-state — Evidence: tasks include \"Rest\"/\"Resting\".\nHead-to-head: The main experimental construct is movement execution (ball squeezing) and motion artifact creation, so Motor is the stronger research-purpose label.\n-> Final: Motor. Confidence moderate due to clear task naming."}},"canonical_name":null,"name_confidence":0.66,"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":"Gao2026_Light_Weight_Multi"}}