{"success":true,"database":"eegdash","data":{"_id":"6953f4249276ef1ee07a332f","dataset_id":"ds004276","associated_paper_doi":null,"authors":["Phoebe Gaston","Christian Brodbeck","Colin Phillips","Ellen Lau"],"bids_version":"1.6.0","contact_info":["Christian Brodbeck","Phoebe Gaston"],"contributing_labs":null,"data_processed":false,"dataset_doi":"doi:10.18112/openneuro.ds004276.v1.0.0","datatypes":["meg"],"demographics":{"subjects_count":19,"ages":[21,19,21,19,20,30,18,20,19,20,19,20,23,24,20,20,22,21],"age_min":18,"age_max":30,"age_mean":20.88888888888889,"species":null,"sex_distribution":{"f":9,"m":9},"handedness_distribution":{"r":18}},"experimental_modalities":null,"external_links":{"source_url":"https://openneuro.org/datasets/ds004276","osf_url":null,"github_url":null,"paper_url":null},"funding":["NSF BCS-1749407"],"ingestion_fingerprint":"7a306d72cbb5b733a836926a2b2c720c9f51d42962b376c92e49ed32811e57bd","license":"CC0","n_contributing_labs":null,"name":"Auditory single word recognition in MEG","readme":"# Auditory single word recognition in MEG\nThis dataset is described in Gaston et al. (2022).\nStimuli and TextGrids are available from the Massive Auditory Lexical Decision database (Tucker et al., 2019).\nConverted to BIDS using MNE-BIDS (Appelhoff et al., 2019; Niso et al., 2018).\n# References\nAppelhoff, S., Sanderson, M., Brooks, T., Vliet, M., Quentin, R., Holdgraf, C., Chaumon, M., Mikulan, E., Tavabi, K., Höchenberger, R., Welke, D., Brunner, C., Rockhill, A., Larson, E., Gramfort, A. and Jas, M. (2019). MNE-BIDS: Organizing electrophysiological data into the BIDS format and facilitating their analysis. Journal of Open Source Software 4: (1896). https://doi.org/10.21105/joss.01896\nGaston, P., Brodbeck, C., Phillips, C., & Lau, E. (2022). Auditory word comprehension is less incremental in isolated words. Neurobiology of Language\nNiso, G., Gorgolewski, K. J., Bock, E., Brooks, T. L., Flandin, G., Gramfort, A., Henson, R. N., Jas, M., Litvak, V., Moreau, J., Oostenveld, R., Schoffelen, J., Tadel, F., Wexler, J., Baillet, S. (2018). MEG-BIDS, the brain imaging data structure extended to magnetoencephalography. Scientific Data, 5, 180110. https://doi.org/10.1038/sdata.2018.110\nTucker, B. V., Brenner, D., Danielson, D. K., Kelley, M. C., Nenadić, F., & Sims, M. (2019). The Massive Auditory Lexical Decision (MALD) database. Behavior Research Methods, 51(3), 1187–1204. https://doi.org/10.3758/s13428-018-1056-1","recording_modality":["meg"],"senior_author":"Ellen Lau","sessions":["20191007"],"size_bytes":12467037085,"source":"openneuro","study_design":null,"study_domain":null,"tasks":["noise","words"],"timestamps":{"digested_at":"2026-04-22T12:26:25.545736+00:00","dataset_created_at":"2022-09-23T14:41:43.515Z","dataset_modified_at":"2022-09-23T20:02:38.000Z"},"total_files":19,"storage":{"backend":"s3","base":"s3://openneuro.org/ds004276","raw_key":"dataset_description.json","dep_keys":["CHANGES","README","participants.json","participants.tsv"]},"tagger_meta":{"config_hash":"3557b68bca409f28","metadata_hash":"e2f7961ec8971a72","model":"openai/gpt-5.2","tagged_at":"2026-04-07T09:32:40.872789+00:00"},"tags":{"pathology":["Healthy"],"modality":["Auditory"],"type":["Perception"],"confidence":{"pathology":0.7,"modality":0.9,"type":0.8},"reasoning":{"few_shot_analysis":"Most similar few-shot by stimulus modality and general paradigm is the example titled \"Subcortical responses to music and speech are alike while cortical responses diverge\" (Healthy + Auditory + Perception). While that few-shot is about music/speech encoding rather than lexical access, it demonstrates the convention that passive/processing-focused auditory speech/listening paradigms map to Modality=Auditory and Type=Perception (not Motor/Attention). The digit span few-shot (Healthy + Auditory + Memory) shows that when explicit working-memory encoding/recall is central, Type becomes Memory; this contrast helps assign the current dataset (word comprehension/recognition) to Perception rather than Memory.","metadata_analysis":"Population: no clinical recruitment is described; demographics only: \"Subjects: 19\" and \"Age range: 18-30\".\nStimulus modality/task: the title is explicit: \"Auditory single word recognition in MEG\". The readme ties stimuli to an auditory word database: \"Massive Auditory Lexical Decision database\". Task labels include \"words\" and \"noise\" (\"tasks\": [\"noise\", \"words\"]).\nCognitive aim: readme cites the associated paper framing: \"Auditory word comprehension is less incremental in isolated words.\" Together with \"single word recognition\", this indicates an auditory language/word recognition (speech perception/lexical access) focus.","paper_abstract_analysis":"No useful paper information. (Only a citation is provided; no abstract text included in metadata.)","evidence_alignment_check":"Pathology:\n1) Metadata says: only demographics, e.g., \"Subjects: 19\" and \"Age range: 18-30\" (no patients/diagnoses mentioned).\n2) Few-shot pattern suggests: absent explicit diagnosis, label as Healthy.\n3) ALIGN (no conflict).\n\nModality:\n1) Metadata says: \"Auditory single word recognition\"; and stimuli from \"Massive Auditory Lexical Decision\"; tasks include \"words\" and \"noise\".\n2) Few-shot pattern suggests: auditory listening/word stimuli => Modality=Auditory.\n3) ALIGN.\n\nType:\n1) Metadata says: \"single word recognition\" and cited framing: \"Auditory word comprehension...\".\n2) Few-shot pattern suggests: language/speech recognition/listening maps to Perception (contrast with digit-span mapping to Memory when memorization/recall is central).\n3) ALIGN.","decision_summary":"Top-2 candidates per category:\n\nPathology:\n- Healthy (selected): No clinical population mentioned; only general demographics: \"Subjects: 19\"; \"Age range: 18-30\".\n- Unknown (runner-up): Because metadata never explicitly states \"healthy\"/\"controls\".\nAlignment: aligns with few-shot convention (no disorder stated => Healthy).\nConfidence basis: inference from absence of diagnosis + demographic-only participant description (no explicit healthy statement).\n\nModality:\n- Auditory (selected): Title: \"Auditory single word recognition\"; readme: \"Massive Auditory Lexical Decision\"; tasks: \"words\" and \"noise\".\n- Other (runner-up): If one treated \"noise\" as non-speech generic stimulus, but it is still auditory.\nAlignment: strong alignment with auditory few-shot conventions.\nConfidence basis: 3 explicit metadata indicators of auditory stimuli.\n\nType:\n- Perception (selected): \"single word recognition\" and \"Auditory word comprehension\" indicate auditory word/speech recognition/comprehension (perceptual/lexical processing).\n- Memory (runner-up): Word recognition can be loosely framed as recognition memory, but no encoding/recall load manipulation is described (unlike digit span).\nAlignment: aligns with few-shot contrast (speech/listening => Perception; explicit WM tasks => Memory).\nConfidence basis: 2 explicit language-perception/comprehension phrases + supportive few-shot analog."}},"nemar_citation_count":2,"computed_title":"Auditory single word recognition in MEG","nchans_counts":[{"val":193,"count":19}],"sfreq_counts":[{"val":1000.0,"count":19}],"stats_computed_at":"2026-04-21T23:17:03.729567+00:00","total_duration_s":18792.981,"canonical_name":null,"name_confidence":0.74,"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":"Gaston2022"}}