{"success":true,"database":"eegdash","data":{"_id":"6953f4249276ef1ee07a3354","dataset_id":"ds004502","associated_paper_doi":"10.1016/j.neuroimage.2023.119960","authors":["Jose M. G. Penalver","David Lopez-Garcia","Blanca Aguado-Lopez","Carlos Gonzalez-Garcia","Maria Ruz"],"bids_version":"1.2","contact_info":null,"contributing_labs":null,"data_processed":false,"dataset_doi":"doi:10.18112/openneuro.ds004502.v1.0.1","datatypes":["eeg"],"demographics":{"subjects_count":48,"ages":[25,20,21,27,26,18,18,19,19,20,18,25,22,23,18,19,19,23,23,18,25,18,23,26,21,27,19,19,28,22,23,25,20,24,25,21,25,18],"age_min":18,"age_max":28,"age_mean":21.842105263157894,"species":null,"sex_distribution":{"m":16,"f":21,"o":1},"handedness_distribution":null},"experimental_modalities":null,"external_links":{"paper_url":"https://doi.org/10.1016/j.neuroimage.2023.119960"},"funding":[],"ingestion_fingerprint":"b43c9b5e73e67dc0ec1b1664978e8b3fb8d8034f7c038fc18232697442f5a2a5","license":"CC0","n_contributing_labs":null,"name":"Anticipatory differences between Attention and Expectation","readme":null,"recording_modality":["eeg"],"senior_author":null,"sessions":[],"size_bytes":63830259549,"source":"openneuro","study_design":null,"study_domain":null,"tasks":["attexp"],"timestamps":{"digested_at":"2026-05-31T16:15:09.847182+00:00","dataset_created_at":null,"dataset_modified_at":null},"total_files":48,"storage":{"backend":"s3","base":"s3://openneuro.org/ds004502","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":["Attention"],"confidence":{"pathology":0.8,"modality":0.7,"type":0.8},"reasoning":{"few_shot_analysis":"Reviewing the few-shot examples helps infer the type of research focus as well as pathology categorization. Example 1 'Meta-rdk' involves a visual task with perception-type classification albeit a clinical population, which guides towards the type labeling about anticipatory processes involved in attention. No specific pathology akin to 'Schizophrenia/Psychosis' indicated directly in this dataset. Example 6 categorizes a healthy young participant set engaged in a learning/perception task without signaling clinical pathology.","metadata_analysis":"The title 'Anticipatory differences between Attention and Expectation' suggests it involves anticipatory cognitive mechanisms, likely aligning with attention-type tasks. It doesn't imply a specific pathological condition, aligning with a healthy participant profile. Participant age range ‘18-28’ is noted, typical of healthy cognitive function studies.","paper_abstract_analysis":"No useful paper information available as the abstract was not provided in the dataset entry.","evidence_alignment_check":{"pathology":{"metadata":"Age and participant demographics (18-28) suggest normal, healthy populations without explicit clinical terminology.","few_shot_pattern":"Similar age and cognitive processing task studies also labeled as 'Healthy'.","alignment":"ALIGN - Metadata backs up the pattern for Healthy labeling."},"modality":{"metadata":"The dataset title and lack of explicit sensory modality descriptions suggest 'Visual' since it's often the default in cognitive tasks absent specific sensory indicators.","few_shot_pattern":"Attention and anticipatory task-related few-shot examples predominantly lean towards a visual modality.","alignment":"ALIGN - Sticking to few-shot influence where visual processing is usually central."},"type":{"metadata":"The task emphasizing 'Attention and Expectation' is suggestive of attention processes.","few_shot_pattern":"Few-shots with intentional or attentional tasks matched to 'Attention'.","alignment":"ALIGN - Both sources firmly imply attention-driven task classification."}},"decision_summary":"Top-2 candidates involved aligning metadata with 'Pathology: Healthy' and 'Modality: Visual' where cognitive processes inferred pertain to anticipatory attention mechanisms. Providing 'Type: Attention' more closely fits task thematic emphasis. Confidence in these decisions reflects strong pattern support and absence of counter-indicators."}},"nemar_citation_count":3,"computed_title":"Anticipatory differences between Attention and Expectation","nchans_counts":[{"val":63,"count":44},{"val":65,"count":4}],"sfreq_counts":[{"val":1000.0,"count":44},{"val":500.0,"count":4}],"stats_computed_at":"2026-05-31T19:34:32.599180+00:00","total_duration_s":333443.5,"canonical_name":null,"name_confidence":0.54,"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":"Penalver2023","bad_channels_info":null,"associated_paper_meta":{"channel":"web_search","confidence":"high","author_overlap":4,"is_oa":true,"oa_status":"gold","source":"paper_resolver","method":"web_search","match_evidence":"Penalver; Lopez-Garcia; Gonzalez-Garcia; Aguado-Lopez"}}}