{"success":true,"database":"eegdash","data":{"_id":"69de6d29897a7725c6702346","dataset_id":"nm000103","associated_paper_doi":"10.1038/sdata.2017.181","authors":["Seyed Yahya Shirazi","Alexandre Franco","Maurício Scopel Hoffmann","Nathalia B. Esper","Dung Truong","Arnaud Delorme","Michael Milham","Scott Makeig"],"bids_version":"1.9.0","canonical_name":null,"contact_info":null,"contributing_labs":null,"data_processed":false,"dataset_doi":"10.82901/nemar.nm000103","datatypes":["eeg"],"demographics":{"subjects_count":447,"ages":[6,5,7,16,6,8,10,8,15,16,14,11,16,7,11,15,10,10,6,13,14,8,11,12,10,17,16,6,12,6,11,8,14,10,5,15,13,6,18,13,8,8,8,16,16,13,8,5,11,6,7,7,13,9,7,6,10,6,9,9,17,9,9,16,8,21,15,6,17,7,8,7,17,6,6,9,9,9,14,14,6,8,7,6,7,9,14,7,7,7,20,13,15,12,12,7,7,11,9,7,11,8,12,10,5,8,12,9,10,15,9,7,10,12,15,7,11,9,10,8,5,13,9,7,5,10,8,16,5,19,13,12,16,6,8,8,7,8,5,12,11,8,10,9,12,10,17,16,9,11,6,5,5,15,13,11,11,7,8,7,11,7,9,7,7,6,10,14,10,7,15,5,14,8,5,6,6,8,7,12,6,14,6,14,7,9,8,8,10,7,14,8,5,8,10,20,7,14,9,7,12,8,10,8,15,7,17,13,15,12,9,6,15,10,10,10,10,15,10,5,8,12,7,21,8,5,13,12,18,9,13,12,7,9,9,8,14,20,15,10,15,9,9,14,8,12,5,12,9,10,12,9,13,13,16,16,8,13,5,11,14,12,12,8,13,7,17,10,5,7,9,10,8,10,8,15,10,10,21,8,19,10,11,9,12,11,8,8,16,14,5,8,7,12,14,8,10,9,7,9,8,16,9,14,9,10,8,11,15,5,19,5,9,9,12,6,11,16,15,7,7,7,17,10,9,7,10,7,12,15,10,11,7,12,14,14,5,7,10,10,12,6,15,11,6,15,10,16,17,9,6,11,16,5,6,11,7,5,8,13,13,16,10,7,11,13,15,9,7,12,8,7,15,11,17,8,8,8,5,7,7,6,7,12,7,17,21,6,9,10,7,9,15,17,12,16,12,17,10,9,5,15,9,8,13,8,6,10,12,16,7,14,10,5,5,14,8,7,12,6,20,10,16,12,17,15,12,8,10,9,8,7,9,10,7,11,20,13,17,10,6,8,8,10,5,7,6],"age_min":5,"age_max":21,"age_mean":10.31096196868009,"species":null,"sex_distribution":{"f":189,"m":258},"handedness_distribution":null},"experimental_modalities":null,"external_links":{"paper_url":"https://www.nature.com/articles/sdata2017181.pdf"},"funding":["See https://childmind.org/science/global-open-science/healthy-brain-network/#donors","NIH/NIMH R01MH125934 for BIDS data preparation"],"ingestion_fingerprint":"c917f4984e20c456f30f7bfc1a35eff3ca50fb09c905dcb34b181d408f0c2874","license":"CC-BY-NC-SA 4.0","n_contributing_labs":null,"name":"Healthy Brain Network EEG - Not for Commercial Use","readme":"## Overview\nThis is **NOT for Commercial-Use Release** of HBN-EEG, the EEG and (soon-released) Eye-Tracking Section of the Child Mind Network Healthy Brain Network (HBN) Project, curated into the Brain Imaging Data Structure (BIDS) format. This dataset is part of a larger initiative to advance the understanding of child and adolescent mental health through collecting and analyzing neuroimaging, behavioral, and genetic data (Alexander et al., Sci Data 2017).\n## Data Description\nThis dataset comprises electroencephalogram (EEG) data and behavioral responses collected during EEG experiments from participants involved in the HBN project.\n### Contents\n* **EEG Data:** High-resolution EEG recordings capture a wide range of neural activity during various tasks.\n* **Behavioral Responses:** Participant responses during EEG tasks, including reaction times and accuracy. This data was originally recorded within the behavior directory of the HBN data. This data is now included with the EEG data within the_events. tsv` files.\n### Special Features\n* **Hierarchical Event Descriptors (HED):** Events, including the original EEG events and the included behavioral events, have clear explanations, including proper HED annotation suitable for systematic meta and mega analysis of the data.\n* **P-Factor, Attention, Internalization and Externalization:** Derived from behavioral questionnaires, these factors provide valuable insights into the internalizing and externalizing behaviors of participants, adding a rich layer of psychological interpretation to the EEG and behavioral data.\n* **Data quality and availability:** We performed minimal quality control to ensure that the data was not corrupted, each task had its necessary events, and was ready for preprocessing. The results of this quality control are available in the `participants.tsv` file.\n## Copyright and License\nThis dataset is licensed under the non-commercial version of the Creative Common Attributions version 4.0 license (CC BY NC SA 4.0) based on the participant's consent. Subjects (or their legal gurdians) did NOT provide consent for their data to be used for any commercial pourposes.\n## Acknowledgments\nWe would like to express our gratitude to all participants and their families, whose contributions have made this project possible. We also thank our dedicated team of researchers and clinicians for their efforts in collecting, processing, and curating this data.","recording_modality":["eeg"],"senior_author":null,"sessions":[],"size_bytes":268707751160,"source":"nemar","storage":{"backend":"nemar","base":"s3://nemar/nm000103","raw_key":"dataset_description.json","dep_keys":["README.md","participants.json","participants.tsv","task-DespicableMe_eeg.json","task-DespicableMe_events.json","task-DiaryOfAWimpyKid_eeg.json","task-DiaryOfAWimpyKid_events.json","task-FunwithFractals_eeg.json","task-FunwithFractals_events.json","task-RestingState_eeg.json","task-RestingState_events.json","task-ThePresent_eeg.json","task-ThePresent_events.json","task-contrastChangeDetection_eeg.json","task-contrastChangeDetection_events.json","task-seqLearning6target_eeg.json","task-seqLearning6target_events.json","task-seqLearning8target_eeg.json","task-seqLearning8target_events.json","task-surroundSupp_eeg.json","task-surroundSupp_events.json","task-symbolSearch_eeg.json","task-symbolSearch_events.json"]},"study_design":null,"study_domain":null,"tasks":["DespicableMe","DiaryOfAWimpyKid","FunwithFractals","RestingState","ThePresent","contrastChangeDetection","seqLearning6target","seqLearning8target","surroundSupp","symbolSearch"],"timestamps":{"digested_at":"2026-05-31T16:34:43.474422+00:00","dataset_created_at":null,"dataset_modified_at":null},"total_files":3522,"author_year":"Shirazi2017","name_source":"canonical","nchans_counts":[{"val":129,"count":3522}],"sfreq_counts":[{"val":500.0,"count":3522}],"computed_title":"Healthy Brain Network EEG - Not for Commercial Use","stats_computed_at":"2026-05-31T19:34:32.604007+00:00","total_duration_s":1026054.228,"bad_channels_info":null,"acknowledgements":"We thank the participants and their families for their time and effort. We also thank the NeuroScience Gateway team for providing computational resources.","ethics_approvals":["Chesapeake Institutional Review Board"],"generated_by":[{"Name":"bids-matlab-tools","Version":"9.1"}],"how_to_acknowledge":"Please cite the following papers when using this dataset: https://dx.doi.org/10.1038/sdata.2017.181, https://dx.doi.org/10.1038/sdata.2017.40","references_and_links":["https://dx.doi.org/10.1038/sdata.2017.181","https://dx.doi.org/10.1038/sdata.2017.40","add_BIDS_sdata_DOI_here"],"associated_paper_meta":{"channel":"text/how_to_acknowledge","confidence":"high","author_overlap":1,"is_oa":true,"oa_status":"gold","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"},"tags":{"pathology":["Psychiatric (transdiagnostic)"],"modality":["Visual"],"type":["Clinical"],"confidence":{"pathology":0.9,"modality":0.8,"type":0.8},"reasoning":{"few_shot_analysis":"The Parkinson's cross-modal oddball and TBI auditory oddball examples show that a clinical population takes precedence over controls or a task-based label, and that Clinical can describe a study's health-related aim. The dementia example shows that Clinical may stand alone when the condition is the overarching focus. Unlike those examples, this dataset spans several tasks and mental-health concerns rather than one named diagnosis.","metadata_analysis":"The readme identifies the dataset as part of the Healthy Brain Network and says it aims to advance understanding of \"child and adolescent mental health.\" It also lists \"P-Factor, Attention, Internalization and Externalization\" measures. The tasks include \"RestingState,\" \"contrastChangeDetection,\" \"surroundSupp,\" \"seqLearning6target,\" and \"symbolSearch,\" alongside titles suggestive of naturalistic viewing. These indicate a heterogeneous task battery; several task names point to visual stimuli, but the metadata does not explicitly say whether the viewing tasks include sound.","paper_abstract_analysis":"The abstract describes a biobank intended to capture \"a broad range of commonly encountered clinical psychopathology\" and data about \"psychiatric, behavioral, cognitive, and lifestyle phenotypes.\" This supports a transdiagnostic mental-health focus rather than a healthy normative cohort or one specific diagnosis. Its mention of \"naturalistic viewing\" supports visual stimulation but does not establish whether audio was presented in the EEG tasks.","evidence_alignment_check":"Pathology: Metadata says \"child and adolescent mental health\" and the abstract says \"a broad range of commonly encountered clinical psychopathology\"; the clinical-cohort few-shot pattern suggests labeling by the recruited population. ALIGN: use Psychiatric (transdiagnostic), not Healthy despite the project's name. Modality: Task names include \"contrastChangeDetection\" and \"surroundSupp\"; visual-task examples suggest Visual. ALIGN provisionally, though audio in the viewing tasks is not documented and Multisensory remains possible. Type: Metadata describes mental-health measures including \"P-Factor, Attention, Internalization and Externalization\" across varied tasks; clinical-dataset examples suggest Clinical. ALIGN: no single task construct adequately represents the whole dataset. No metadata fact is overridden by a few-shot pattern.","decision_summary":"Pathology top two: Psychiatric (transdiagnostic) versus Healthy. Mental-health focus, the P-factor/internalizing/externalizing measures, and the abstract's broad clinical-psychopathology description favor Psychiatric (transdiagnostic); the title alone is insufficient evidence for Healthy. Confidence 0.9, supported by those three quoted features and the clinical-cohort examples. Modality top two: Visual versus Multisensory. \"contrastChangeDetection,\" \"surroundSupp,\" \"symbolSearch,\" and naturalistic-viewing context favor Visual; possible audio in viewing tasks is unconfirmed. Confidence 0.8, supported by multiple task names but limited by missing stimulus descriptions. Type top two: Clinical versus Perception. The quoted mental-health aims and psychopathology focus favor Clinical; perceptual tasks form only part of a broader battery. Confidence 0.8, supported by the readme and abstract. Evidence aligns with the selected labels; no metadata fact was overridden."}}}}