{"success":true,"database":"eegdash","data":{"_id":"6953f4249276ef1ee07a3381","dataset_id":"ds004771","associated_paper_doi":"10.21203/rs.3.rs-3396298/v1","authors":["Chu-Hsuan Kuo","Chantel S. Prat"],"bids_version":"1.8.0","contact_info":null,"contributing_labs":null,"data_processed":false,"dataset_doi":"doi:10.18112/openneuro.ds004771.v1.0.0","datatypes":["eeg"],"demographics":{"subjects_count":61,"ages":[33,22,27,18,20,22,20,22,22,22,23,21,24,23,22,25,25,28,19,28,22,19,28,24,24,25,25,32,26,24,24,28,24,23,23,20,20,23,24,23,18,23,25,19,19,22,18,23,21,18,21,21,20,20,21,18,20,20,19,20,21],"age_min":18,"age_max":33,"age_mean":22.524590163934427,"species":null,"sex_distribution":{"f":33,"m":27,"o":1},"handedness_distribution":null},"experimental_modalities":null,"external_links":{"paper_url":"https://doi.org/10.21203/rs.3.rs-3396298/v1"},"funding":["Office of Naval Research, Cognitive Science of Learning program (N00014-20-1-2393)"],"ingestion_fingerprint":"c835c54ca8c455005b9b62c6e6d964ed9e84ad8231107a7d0e661d5dc62e5389","license":"CC0","n_contributing_labs":null,"name":"EEG/ERP data from a Python Reading Task","readme":"EEG data for the Python reading task (acceptability judgments) described in [Kuo, C-H. and Prat, C.S. Programmers show distinct, language-like brain responses to violations in form and meaning when reading code], pending submission to Nature Communications.\nThis study recruited 62 total subjects. 1 subject did not complete the EEG session and was removed from all analyses and is not included in this dataset. The remaining 61 individuals' EEG data are included. The participants info file contains information regarding which individuals were included in the final analyses (per artifact rejection criteria detailed in the article).\nThe stimuli for this study was administered in Presentation; as such, the files are in the formats compatible with this program.\nThe provided code was used for processing the EEG data. All statistics were run in Jamovi, an R-based open source software; feel free to reach out for the original files if you are interested.","recording_modality":["eeg"],"senior_author":null,"sessions":[],"size_bytes":1462559440,"source":"openneuro","study_design":null,"study_domain":null,"tasks":["PY"],"timestamps":{"digested_at":"2026-05-31T16:15:54.113143+00:00","dataset_created_at":null,"dataset_modified_at":null},"total_files":61,"storage":{"backend":"s3","base":"s3://openneuro.org/ds004771","raw_key":"dataset_description.json","dep_keys":["CHANGES","README","participants.json","participants.tsv","task-PY_events.json"]},"nemar_citation_count":1,"computed_title":"EEG/ERP data from a Python Reading Task","nchans_counts":[{"val":34,"count":61}],"sfreq_counts":[{"val":256.0,"count":61}],"stats_computed_at":"2026-05-31T19:34:32.599786+00:00","tags":{"pathology":["Healthy"],"modality":["Visual"],"type":["Language"],"confidence":{"pathology":0.7,"modality":0.8,"type":0.8},"reasoning":{"few_shot_analysis":"The visual discrimination example labels a task by its main cognitive construct rather than its response: Perception, not Decision-making. The auditory digit-span example likewise labels the primary aim, Memory, rather than the stimulus content. These conventions support labeling this reading-and-comprehension study Language despite its acceptability judgments. The healthy-volunteer motor example provides a population convention, though no few-shot example closely matches code reading.","metadata_analysis":"The title is \"EEG/ERP data from a Python Reading Task.\" The README describes \"Python reading task (acceptability judgments)\" and \"language-like brain responses to violations in form and meaning when reading code.\" It reports \"61 individuals' EEG data\" without identifying a recruited clinical condition. Reading code supports visually presented stimuli and a language-comprehension aim.","paper_abstract_analysis":"The abstract says \"Python programmers with varying skill levels read lines of code with semantic and syntactic congruency manipulations\" and concludes that \"computer code comprehension is incremental, relying jointly on form and meaning.\" This strengthens Language over Perception or Learning. Varying programming skill is not a clinical diagnosis.","evidence_alignment_check":"Pathology: Metadata says \"61 individuals' EEG data\" and the abstract identifies \"Python programmers with varying skill levels,\" with no clinical diagnosis. The healthy-volunteer few-shot pattern suggests Healthy; they align, although health is inferred rather than explicitly stated. Modality: Metadata says \"Python Reading Task\" and \"reading code.\" Few-shot examples assign modality from presented stimuli, not responses; this aligns with Visual, though the README does not explicitly name a screen. Type: Metadata says \"acceptability judgments\" and \"language-like brain responses to violations in form and meaning when reading code.\" Few-shot examples assign the primary construct rather than response mechanics; this aligns with Language. There are no metadata–example conflicts or overridden metadata facts.","decision_summary":"Pathology—Healthy versus Unknown: a cohort of \"Python programmers with varying skill levels\" and \"61 individuals' EEG data\" is described without clinical recruitment, favoring Healthy; confidence 0.7 because health is inferred. Modality—Visual versus Unknown: \"Python Reading Task\" and \"reading code\" favor Visual, although presentation hardware is not specified; confidence 0.8 based on two reading descriptions and the stimulus-based few-shot convention. Type—Language versus Perception: \"acceptability judgments,\" \"violations in form and meaning when reading code,\" and the abstract's \"semantic and syntactic congruency manipulations\" favor comprehension over sensory discrimination; confidence 0.8 because the evidence is strong but there is no close language-task few-shot match."}},"total_duration_s":38104.703125,"author_year":"Kuo2023","canonical_name":null,"bad_channels_info":null,"acknowledgements":"Thank you to Mark Pettet for assistance with data analysis and the conversion of data to BIDS format.","ethics_approvals":["All experimental procedures were approved by the University of Washington Institutional Review Board"],"references_and_links":["See manuscript"],"associated_paper_meta":{"channel":"search","confidence":"high","author_overlap":2,"is_oa":true,"oa_status":"preprint","source":"paper_resolver"},"tagger_meta":{"model":"gpt-6-sol","taxonomy":"v2","config_hash":"39931253008fe2df","tagged_at":"2026-10-06T13:13:11Z","source":"eegdash-llm-tagger"}}}