{"success":true,"database":"eegdash","data":{"_id":"6953f4239276ef1ee07a32e6","dataset_id":"ds003694","associated_paper_doi":"10.1101/2020.01.22.915330","authors":["Benjamin J. Griffiths","María Carmen Martín-Buro","Bernhard Staresina","Simon Hanslmayr"],"bids_version":"1.0.2","contact_info":null,"contributing_labs":null,"data_processed":false,"dataset_doi":"10.18112/openneuro.ds003694.v1.0.0","datatypes":["meg"],"demographics":{"subjects_count":28,"ages":[],"age_min":null,"age_max":null,"age_mean":null,"species":null,"sex_distribution":null,"handedness_distribution":null},"experimental_modalities":null,"external_links":{"paper_url":"https://www.biorxiv.org/content/biorxiv/early/2021/04/21/2020.01.22.915330.full.pdf"},"funding":[],"ingestion_fingerprint":"98372048a7cd782018b4bb6e219f1f5f3dce7c00c9ae8f87660acf1d6a33ff27","license":"CC0","n_contributing_labs":null,"name":"MEGMEM","readme":null,"recording_modality":["meg"],"senior_author":null,"sessions":[],"size_bytes":234582593978,"source":"openneuro","study_design":null,"study_domain":null,"tasks":["MEM"],"timestamps":{"digested_at":"2026-05-31T16:13:02.887752+00:00","dataset_created_at":null,"dataset_modified_at":null},"total_files":132,"storage":{"backend":"s3","base":"s3://openneuro.org/ds003694","raw_key":"dataset_description.json","dep_keys":["CHANGES","participants.tsv"]},"tagger_meta":{"model":"openai/gpt-4o","tagged_at":"2026-06-10T08:19:41Z","source":"eegdash-llm-tagger"},"tags":{"pathology":["Healthy"],"modality":["Visual"],"type":["Memory"],"confidence":{"pathology":0.8,"modality":0.8,"type":0.8},"reasoning":{"few_shot_analysis":"The dataset exhibits similarity to few-shot examples with memory tasks, notably the 'EEG, pupillometry, ECG and photoplethysmography, and behavioral data in the digit span task and rest', which involved tasks focused on memory through auditory sequences and serial recall. Both datasets aim to study memory, suggesting 'Memory' as a suitable label for Type. Like 'EEG Motor Movement/Imagery Dataset', which involves cognitive processes linked to imagination, object presentation, and button responses indicate tasks fostering 'Memory' processes.","metadata_analysis":"The dataset title and authors suggest a focus on memory: 'MEGMEM' and 'Benjamin J. Griffiths, María Carmen Martín-Buro, Bernhard Staresina, Simon Hanslmayr', known for memory research. Event types 'feat_pres', 'imagery', and 'object_pres' suggest focus on presenting features and objects, invoking cognitive processes linked with memory.","paper_abstract_analysis":"No useful paper information.","evidence_alignment_check":"1. Pathology: Metadata names no specific clinical condition, aligning with Healthy few-shot examples suggesting memory tasks as generally involving healthy subjects. \n2. Modality: Event names suggest visual components like 'object_pres', 'scene_pres', connecting with visual tasks in examples. Few-shot examples imply similar tasks classified as 'Visual'. \n3. Type: Metadata focus on memory-related processes is consistent with the 'Memory' label in several few-shot examples with memory-related tasks.","decision_summary":"Pathology: 'Healthy' is inferred since dataset does not specify clinical populations, task type memory aligns with typical population. Modality: 'Visual' due to events indicating 'object_pres' and 'scene_pres', consistent with object-based presentations. Type: 'Memory', as dataset explicitly centers on memory ('MEGMEM'), with task events supporting cognitive processes. High confidence based on metadata and paradigm alignment with few-shot patterns."}},"nemar_citation_count":1,"computed_title":"MEGMEM","nchans_counts":[{"val":327,"count":109},{"val":319,"count":19},{"val":336,"count":4}],"sfreq_counts":[{"val":1000.0,"count":132}],"stats_computed_at":"2026-05-31T19:34:32.518045+00:00","total_duration_s":null,"canonical_name":null,"name_confidence":0.72,"name_meta":{"suggested_at":"2026-04-14T10:18:35.342Z","model":"openai/gpt-5.2 + openai/gpt-5.4-mini + deterministic_fallback"},"name_source":"canonical","author_year":"Griffiths2021","how_to_acknowledge":"When making use of this data, please cite the associated publication [https://www.biorxiv.org/content/10.1101/2020.01.22.915330v3]","bad_channels_info":null,"associated_paper_meta":{"channel":"text/normalized-doi","confidence":"high","author_overlap":0,"is_oa":true,"oa_status":"green","source":"paper_resolver","method":"normalization"}}}