{"success":true,"database":"eegdash","data":{"_id":"6953f4239276ef1ee07a32d8","dataset_id":"ds003568","associated_paper_doi":"10.1101/2021.03.04.433969","authors":["Lucrezia Liuzzi","Katharine Chang","Hanna Keren","Charles Zheng","Dipta Saha","Dylan Nielson","Argyris Stringaris"],"bids_version":"1.2.0","contact_info":null,"contributing_labs":null,"data_processed":false,"dataset_doi":"10.18112/openneuro.ds003568.v1.0.2","datatypes":["meg"],"demographics":{"subjects_count":51,"ages":[],"age_min":null,"age_max":null,"age_mean":null,"species":null,"sex_distribution":{"m":19,"f":32},"handedness_distribution":null},"experimental_modalities":null,"external_links":{"paper_url":"https://www.biorxiv.org/content/biorxiv/early/2021/03/16/2021.03.04.433969.full.pdf"},"funding":["Intramural Research Program of the National Institute of Mental Health National Institutes of Health (NIH) (Grant No. ZIA-MH002957-01 [to AS])"],"ingestion_fingerprint":"7622ba5f61525e1989795c78834ef6e4515fc17291c614f7bf207fa0ddf01713","license":"CC0","n_contributing_labs":null,"name":"Mood induction in MDD and healthy adolescents","readme":"This dataset contains the MEG and structural MRI data from the \"Electrophysiological correlates of mood and reward dynamics in human adolescents\" pre-registered analysis (https://www.biorxiv.org/content/10.1101/2021.03.04.433969v1).\nThe task-mmi3 data corresponds to the monetary gambling mood induction task described in the paper. Task-mmi3 data has been pre-processed marking bad channels and bad segments (motion > 5mm or/and noise artifacts).\nTask-rest data is unprocessed 10 minutes resting state scan acquired during the same scanning session.\nAnatomical MRIs have been defaced and co-registered fiducial coordinates are available in the anatomical json files.\nData from four confirmatory subjects are not made available because of missing data sharing consent.\nsub-22658 and sub-24247 do not have an available structural scan.","recording_modality":["meg"],"senior_author":null,"sessions":[],"size_bytes":132521905066,"source":"openneuro","study_design":null,"study_domain":null,"tasks":["mmi3","rest"],"timestamps":{"digested_at":"2026-05-31T16:12:51.680268+00:00","dataset_created_at":null,"dataset_modified_at":null},"total_files":118,"storage":{"backend":"s3","base":"s3://openneuro.org/ds003568","raw_key":"dataset_description.json","dep_keys":["CHANGES","README","participants.tsv"]},"tagger_meta":{"config_hash":"4a051be509a0e3d0","metadata_hash":"6c7c3403d4d17c92","model":"openai/gpt-5.2","tagged_at":"2026-01-20T10:16:53.457778+00:00"},"tags":{"pathology":["Healthy"],"modality":["Visual"],"type":["Affect"],"confidence":{"pathology":0.7,"modality":0.6,"type":0.7},"reasoning":{"few_shot_analysis":"Most similar few-shot example by task paradigm and domain is the labeled dataset \"EEG: Three armed bandit gambling task\" (Healthy / Visual / Affect). It shares a gambling/reward paradigm and an explicit focus on reward processing dynamics, which in EEGDash conventions maps the study purpose to Affect (mood/reward/valence processing) rather than purely Decision-making. This convention guides mapping the present dataset’s \"monetary gambling mood induction\" to Affect, with likely Visual stimulus presentation.","metadata_analysis":"Key extracted facts from the provided README include: (1) population age group: \"Electrophysiological correlates of mood and reward dynamics in human adolescents\"; (2) task: \"task-mmi3 data corresponds to the monetary gambling mood induction task\"; (3) additional recording condition: \"Task-rest data is unprocessed 10 minutes resting state scan\"; (4) modality recorded is MEG (but Modality label here refers to stimulus/input channel, not recording technique): \"This dataset contains the MEG and structural MRI data\".","paper_abstract_analysis":"No useful paper information. (Only a link to a preregistered biorxiv analysis is provided; no abstract text is included in the metadata snippet.)","evidence_alignment_check":"Pathology: Metadata says participants are \"human adolescents\" but does not state a disorder/diagnosis; few-shot conventions treat non-clinical cohorts as Healthy. ALIGN (no clinical recruitment stated).\nModality: Metadata does not explicitly state stimulus channel (visual/auditory/etc.); few-shot gambling examples are typically Visual, but this is an inference. PARTIAL CONFLICT/UNCERTAINTY (few-shot suggests Visual; metadata is silent), so inference is used with lower confidence.\nType: Metadata explicitly highlights \"mood and reward dynamics\" and a \"mood induction\" gambling task; few-shot gambling example maps similar reward-focused paradigms to Affect. ALIGN (both indicate affective/reward focus).","decision_summary":"Pathology top-2: (1) Healthy — supported by absence of any diagnosis and general-population phrasing \"human adolescents\" (no clinical recruitment); (2) Development — plausible because cohort is adolescents, but Pathology is defined as clinical condition used to recruit participants, which is not stated. Winner: Healthy. Confidence: 0.7 (1 explicit quote about adolescents, plus absence-of-diagnosis inference).\nModality top-2: (1) Visual — inferred from \"monetary gambling mood induction task\" consistent with common visually-presented gambling tasks and supported by close few-shot analog (three-armed bandit labeled Visual); (2) Unknown — because metadata snippet never states stimulus channel. Winner: Visual. Confidence: 0.6 (contextual inference + few-shot analog, no direct quote).\nType top-2: (1) Affect — supported by explicit \"mood and reward dynamics\" and \"mood induction\" wording; (2) Decision-making — plausible due to \"monetary gambling\" framing. Winner: Affect, consistent with few-shot gambling convention. Confidence: 0.7 (2 explicit mood-related quotes, but task details are brief)."}},"nemar_citation_count":4,"computed_title":"Mood induction in MDD and healthy adolescents","nchans_counts":[{"val":340,"count":48},{"val":339,"count":29},{"val":335,"count":11},{"val":336,"count":6},{"val":343,"count":5},{"val":342,"count":5},{"val":338,"count":3},{"val":312,"count":3},{"val":309,"count":3},{"val":305,"count":2},{"val":313,"count":1},{"val":310,"count":1},{"val":348,"count":1}],"sfreq_counts":[{"val":1200.0,"count":118}],"stats_computed_at":"2026-05-31T19:34:32.517876+00:00","total_duration_s":81150.0,"author_year":"Liuzzi2021","canonical_name":null,"bad_channels_info":null,"acknowledgements":"This research was supported by the Intramural Research Program of the National Institute of Mental Health National Institutes of Health (NIH). This work used the computational resources of the NIH HPC (high-performance computing) Biowulf cluster (http://hpc.nih.gov).","ethics_approvals":["NIH Institutional Review Board"],"how_to_acknowledge":"Please cite: Lucrezia Liuzzi, Katharine Chang, Hanna Keren, Charles Zheng, Dipta Saha,Dylan Nielson and Argyris Stringaris, Electrophysiological correlates of mood and reward dynamics in human adolescents, BioRxiv 2021","references_and_links":["https://www.biorxiv.org/content/10.1101/2021.03.04.433969v1"],"associated_paper_meta":{"channel":"text/normalized-doi","confidence":"high","author_overlap":0,"is_oa":true,"oa_status":"green","source":"paper_resolver","method":"normalization"}}}