{"success":true,"database":"eegdash","data":{"_id":"6953f4249276ef1ee07a33e0","dataset_id":"ds005406","associated_paper_doi":null,"authors":["Silvia Formica","Anna Chaiken","Jan R. Wiersema","Emiel Cracco"],"bids_version":"1.7.0","contact_info":["Silvia Formica"],"contributing_labs":null,"data_processed":false,"dataset_doi":"doi:10.18112/openneuro.ds005406.v1.0.0","datatypes":["eeg"],"demographics":{"subjects_count":29,"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/ds005406","osf_url":null,"github_url":null,"paper_url":null},"funding":[],"ingestion_fingerprint":"c5e4ab277d3b900ee4d2e3d44c1e28f941ce4c66ed4b865be07253894f100878","license":"CC0","n_contributing_labs":null,"name":"EEG frequency tagging reveals the integration of dissimilar observed actions","readme":"References\n----------\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\nPernet, C. R., Appelhoff, S., Gorgolewski, K. J., Flandin, G., Phillips, C., Delorme, A., Oostenveld, R. (2019). EEG-BIDS, an extension to the brain imaging data structure for electroencephalography. Scientific Data, 6, 103.https://doi.org/10.1038/s41597-019-0104-8","recording_modality":["eeg"],"senior_author":"Emiel Cracco","sessions":[],"size_bytes":14241904586,"source":"openneuro","study_design":null,"study_domain":null,"tasks":["FTdiss"],"timestamps":{"digested_at":"2026-04-22T12:27:44.764912+00:00","dataset_created_at":"2024-08-09T14:41:21.877Z","dataset_modified_at":"2024-08-12T09:54:38.000Z"},"total_files":29,"storage":{"backend":"s3","base":"s3://openneuro.org/ds005406","raw_key":"dataset_description.json","dep_keys":["CHANGES","README","participants.json","participants.tsv"]},"tagger_meta":{"config_hash":"3557b68bca409f28","metadata_hash":"f404bebaae94e8b1","model":"openai/gpt-5.2","tagged_at":"2026-04-07T09:32:40.872789+00:00"},"tags":{"pathology":["Healthy"],"modality":["Visual"],"type":["Perception"],"confidence":{"pathology":0.6,"modality":0.6,"type":0.6},"reasoning":{"few_shot_analysis":"Most similar few-shot examples by stimulus channel are the Visual tasks (e.g., 'Meta-rdk: Preprocessed EEG data' labeled Visual/Perception). That example reflects the convention that when participants view visual stimuli and the goal is to measure stimulus-evoked processing/discrimination, the Modality is Visual and the Type is Perception. In contrast, the 'EEG Motor Movement/Imagery Dataset' (Visual/Motor) shows the convention that Type=Motor is reserved for movement execution/imagery as the research focus; the current dataset’s title indicates action *observation* (not execution/imagery), which fits Perception more than Motor under these conventions.","metadata_analysis":"Key metadata facts available are sparse. Relevant snippets:\n1) Title indicates paradigm/stimulus content: \"EEG frequency tagging reveals the integration of dissimilar observed actions\".\n2) Participants field provides only count, no diagnosis: \"Subjects: 29\".\n3) Task label is non-descriptive but suggests an experimental task rather than rest/sleep: \"tasks\": [\"FTdiss\"].\nNo metadata text mentions any patient group, disorder, intervention, or resting/sleep recording.","paper_abstract_analysis":"No useful paper information.","evidence_alignment_check":"Pathology: Metadata SAYS only \"Subjects: 29\" with no clinical descriptors; few-shot pattern SUGGESTS that typical cognitive EEG experiments without stated diagnoses are labeled Healthy. ALIGN (no conflict).\n\nModality: Metadata SAYS \"observed actions\" (in title) and mentions \"frequency tagging\"; few-shot pattern SUGGESTS frequency-tagging/action-observation studies are typically driven by visual stimulation, mapped to Visual modality. ALIGN (inference, no explicit contradiction).\n\nType: Metadata SAYS \"integration of dissimilar observed actions\" (action observation/integration). Few-shot pattern SUGGESTS Perception for stimulus-driven visual processing (as in the visual discrimination example) and Motor only for execution/imagery (as in the motor movement/imagery example). ALIGN; Perception better matches observation/integration than Motor.","decision_summary":"Top-2 candidates:\n\nPathology:\n1) Healthy — supported by absence of any recruitment diagnosis in available metadata (\"Subjects: 29\") and the dataset reading like a standard cognitive EEG experiment.\n2) Unknown — plausible because the participant health status is not explicitly stated.\nDecision: Healthy (alignment: no conflict; confidence limited due to lack of explicit statement).\n\nModality:\n1) Visual — supported by \"observed actions\" in the title and the typical use of EEG frequency tagging with periodic visual stimulation.\n2) Unknown — plausible because no stimulus modality is explicitly described in the provided readme.\nDecision: Visual (alignment: consistent with few-shot conventions; confidence moderate-low due to inference).\n\nType:\n1) Perception — supported by \"observed actions\" and \"integration\" framing (action perception/integration) rather than performing movements.\n2) Motor — plausible alternative because actions are the content, but rejected since they are observed, not executed/imagined.\nDecision: Perception (alignment: consistent with few-shot Perception vs Motor distinction; confidence moderate-low)."}},"nemar_citation_count":0,"computed_title":"EEG frequency tagging reveals the integration of dissimilar observed actions","nchans_counts":[{"val":64,"count":29}],"sfreq_counts":[{"val":1000.0,"count":29}],"stats_computed_at":"2026-04-22T23:16:00.309507+00:00","total_duration_s":55628.955,"canonical_name":null,"name_confidence":0.92,"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":"Formica2024"}}