{"success":true,"database":"eegdash","data":{"_id":"6953f4249276ef1ee07a3412","dataset_id":"ds005697","associated_paper_doi":null,"authors":["Weilong Li","Hua Fan"],"bids_version":"1.8.0","contact_info":["Anonymous User"],"contributing_labs":null,"data_processed":false,"dataset_doi":"doi:10.18112/openneuro.ds005697.v1.0.2","datatypes":["eeg"],"demographics":{"subjects_count":51,"ages":[25,23,23,25,30,26,25,24,24,24,24,28,28,26,28,24,25,25,25,24,27,26,24,24,24,26,26,28,25,22,24,24,25,27,25,25,23,23,24,27,24,24,24,24,24,23,27,26,26,24],"age_min":22,"age_max":30,"age_mean":25.02,"species":null,"sex_distribution":{"m":25,"f":25},"handedness_distribution":null},"experimental_modalities":null,"external_links":{"source_url":"https://openneuro.org/datasets/ds005697","osf_url":null,"github_url":null,"paper_url":null},"funding":[],"ingestion_fingerprint":"7d506b61b77d11d2a6e216f032d80675e55024f35b930e5c6ca7ff72ab7d3db0","license":"CC0","n_contributing_labs":null,"name":"PerceiveImagine","readme":"This dataset consists of electroencephalogram (EEG) signals collected by the 64 channel EEG device SynAmps2.\n###Participants and Conversations\nThis experiment included 54 participants. 2 participants gave up the experiment midway due to physical reasons, and 6 participants had poor signal collection results during the first collection and underwent a second collection. All participants met the experimental requirements\n###Task\nThis experiment requires participants to watch the image for 6 seconds according to the requirements, and then imagine the image they see for 6 seconds. The total dataset contains 340 images\n###Dataset version\nThe provided dataset consists of the original dataset\n###contact\nIf you have any questions, please contact:yingxmbio@foxmail.com","recording_modality":["eeg"],"senior_author":"Hua Fan","sessions":[],"size_bytes":71461601517,"source":"openneuro","study_design":null,"study_domain":null,"tasks":["PerceiveImagine"],"timestamps":{"digested_at":"2026-04-22T12:28:41.884094+00:00","dataset_created_at":"2024-12-05T11:51:54.134Z","dataset_modified_at":"2024-12-10T01:53:24.000Z"},"total_files":51,"storage":{"backend":"s3","base":"s3://openneuro.org/ds005697","raw_key":"dataset_description.json","dep_keys":["CHANGES","README","participants.json","participants.tsv","task-PerceiveImagine_events.json"]},"tagger_meta":{"config_hash":"4a051be509a0e3d0","metadata_hash":"e49385dcce9677ce","model":"openai/gpt-5.2","tagged_at":"2026-01-20T18:36:33.704375+00:00"},"tags":{"pathology":["Healthy"],"modality":["Visual"],"type":["Memory"],"confidence":{"pathology":0.7,"modality":0.8,"type":0.65},"reasoning":{"few_shot_analysis":"Most similar conventions in the few-shot set:\n1) \"EEG, pupillometry... digit span task\" (Healthy / Auditory / Memory): shows that when the core manipulation is maintaining/mentally handling recently presented stimuli (\"memorized... sequences\"), the Type is labeled as Memory rather than Perception.\n2) \"EEG Motor Movement/Imagery Dataset\" (Healthy / Visual / Motor): demonstrates a convention that *imagery* tasks are labeled by the underlying construct being engaged (motor imagery -> Motor type), not merely by the fact that there is a stimulus screen.\nApplied here: the dataset explicitly includes an imagery phase (\"imagine the image\"), suggesting a memory/mental imagery construct analogous to working-memory/maintenance rather than purely perceptual discrimination.","metadata_analysis":"Key metadata facts from the provided README:\n- Recording/participants: \"This experiment included 54 participants.\" and \"64 channel EEG device SynAmps2.\"\n- Task structure: \"participants to watch the image for 6 seconds\" followed by \"then imagine the image they see for 6 seconds.\" \n- Stimulus set: \"The total dataset contains 340 images\".\nNo mention of any diagnosis/clinical recruitment criteria was provided.","paper_abstract_analysis":"No useful paper information.","evidence_alignment_check":"Pathology:\n- Metadata says: no disorder/diagnosis is mentioned; only \"included 54 participants\".\n- Few-shot pattern suggests: when no clinical group is described (e.g., several \"Healthy\" examples), label as Healthy.\n- Alignment: ALIGN (metadata lacks any clinical recruitment facts; default to Healthy).\n\nModality:\n- Metadata says: \"watch the image\" and dataset contains \"340 images\".\n- Few-shot pattern suggests: image/screen-based paradigms map to Visual modality.\n- Alignment: ALIGN.\n\nType:\n- Metadata says: perception + imagery/maintenance: \"watch the image for 6 seconds\" then \"imagine the image... for 6 seconds\".\n- Few-shot pattern suggests: (a) maintenance/mental handling of stimuli maps to Memory (digit span example), while (b) purely stimulus discrimination/detection maps to Perception.\n- Alignment: PARTIAL (metadata does not explicitly say 'memory' or 'working memory', but the imagery phase is consistent with memory/mental imagery conventions).","decision_summary":"Top-2 candidates per category and final choice:\n\nPathology:\n1) Healthy — Evidence: no diagnosis or patient group described; only \"54 participants\".\n2) Unknown — Considered because recruitment details are sparse.\nDecision: Healthy (default normative cohort when no clinical recruitment is stated). Confidence reflects lack of explicit 'healthy' wording.\n\nModality:\n1) Visual — Evidence: \"watch the image\"; \"340 images\".\n2) Other — only if images were incidental, but they are central.\nDecision: Visual. High confidence due to explicit image stimuli.\n\nType:\n1) Memory — Evidence: explicit imagery/mental re-presentation: \"imagine the image... for 6 seconds\"; guided by digit-span few-shot convention that maintaining/mentally handling presented stimuli is Memory.\n2) Perception — Evidence: explicit viewing phase: \"watch the image for 6 seconds\".\nDecision: Memory because the task includes a dedicated imagery period after viewing, implying maintenance/mental imagery rather than purely perceptual discrimination. Confidence is moderate since metadata never explicitly uses 'memory/imagery' constructs beyond the single instruction."}},"nemar_citation_count":3,"computed_title":"PerceiveImagine","nchans_counts":[{"val":65,"count":45},{"val":69,"count":6}],"sfreq_counts":[{"val":1000.0,"count":50}],"stats_computed_at":"2026-04-22T23:16:00.310829+00:00","source_url":"https://openneuro.org/datasets/ds005697","total_duration_s":279681.3,"canonical_name":null,"name_confidence":0.95,"name_meta":{"suggested_at":"2026-04-14T10:18:35.343Z","model":"openai/gpt-5.2 + openai/gpt-5.4-mini + deterministic_fallback"},"name_source":"canonical","author_year":"Li2024_PerceiveImagine"}}