{"success":true,"database":"eegdash","data":{"_id":"6953f4249276ef1ee07a341e","dataset_id":"ds005863","associated_paper_doi":null,"authors":["Elif Isbell","Amanda N. Peters","Dylan M. Richardson","Nancy E. R. De León"],"bids_version":"1.9.0","contact_info":["Elif Isbell"],"contributing_labs":null,"data_processed":false,"dataset_doi":"doi:10.18112/openneuro.ds005863.v2.0.0","datatypes":["eeg"],"demographics":{"subjects_count":127,"ages":[19,24,21,18,19,21,20,19,19,20,19,19,22,20,20,21,26,20,25,21,21,20,25,19,19,19,19,18,20,19,23,22,24,20,20,25,23,20,20,23,27,27,19,28,29,23,24,19,19,19,20,22,22,19,20,20,26,21,22,30,29,21,20,26,23,24,22,20,21,23,22,20,19,19,21,19,21,19,22,25,20,18,20,18,19,19,19,20,19,19,18,19,18,20,18,18,21,20,19,26,21,22,21,23,18,20,21,27,19,19,21,19,21,20,19,19,18,19,19,19,21,18,18,18,20,18,19],"age_min":18,"age_max":30,"age_mean":20.858267716535433,"species":null,"sex_distribution":{"f":73,"m":53,"o":1},"handedness_distribution":{"r":116,"l":7}},"experimental_modalities":null,"external_links":{"source_url":"https://openneuro.org/datasets/ds005863","osf_url":null,"github_url":null,"paper_url":null},"funding":["research start-up funds awarded to Elif Isbell by University of California Merced."],"ingestion_fingerprint":"3bc503c76463ebaf5368f0cfe90b07a8edaaabb7d47d54b28ace944015c47766","license":"CC0","n_contributing_labs":null,"name":"Cognitive Electrophysiology in Socioeconomic Context in Adulthood","readme":"## The “Cognitive Electrophysiology in Socioeconomic Context in Adulthood” Dataset\n# Data Description\nThis dataset comprises electroencephalogram (EEG) data collected from 127 young adults (18-30 years), along with retrospective objective and subjective indicators of childhood family socioeconomic status (SES), as well as SES indicators in adulthood, such as educational attainment, individual and household income, food security, and home and neighborhood characteristics. The EEG data were recorded with tasks directly acquired from the Event-Related Potentials Compendium of Open Resources and Experiments ERP CORE (Kappenman et al., 2021), or adapted from these tasks (Isbell et al., 2024). These tasks, which are publicly available, were optimized to capture neural activity manifest in perception, cognition, and action, in neurotypical young adults. Furthermore, the dataset includes a symptoms checklist, consisting of questions that were found to be predictive of symptoms consistent with attention-deficit/hyperactivity disorder (ADHD) in adulthood, which can be used to investigate the links between ADHD symptoms and neural activity in a socioeconomically diverse young adult sample.\n# Notes\nBefore the data were publicly shared, all identifiable information was removed, including date of birth, race/ethnicity, zip code, and names of the languages the participants reported to speaking and understanding fluently. Date of birth was used to compute age in years, which is included in the dataset. The dataset consists of participants recruited for studies on adult cognition in context. To provide the largest sample size, we included all participants who completed at least one of the EEG tasks of interest. Each participant completed each EEG task only once. The original participant IDs with which the EEG data were saved were recoded and the raw EEG files were renamed to make the dataset BIDS compatible.\n# Copyright and License\nThis dataset is licensed under CC0.\n# References\nIsbell, E., De León, N. E. R., & Richardson, D. M. (2024). Childhood family socioeconomic status is linked to adult brain electrophysiology. PloS One, 19(8), e0307406.\nKappenman, E. S., Farrens, J. L., Zhang, W., Stewart, A. X., & Luck, S. J. (2021). ERP CORE: An open resource for human event-related potential research. NeuroImage, 225, 117465.","recording_modality":["eeg"],"senior_author":"Nancy E. R. De León","sessions":[],"size_bytes":11371789699,"source":"openneuro","study_design":null,"study_domain":null,"tasks":["auditoryoddball","flanker","visualoddball","visualsearch"],"timestamps":{"digested_at":"2026-04-22T12:28:56.650930+00:00","dataset_created_at":"2025-01-20T00:07:59.536Z","dataset_modified_at":"2025-03-14T03:20:15.000Z"},"total_files":357,"storage":{"backend":"s3","base":"s3://openneuro.org/ds005863","raw_key":"dataset_description.json","dep_keys":["CHANGES","README","participants.json","participants.tsv"]},"tagger_meta":{"config_hash":"4a051be509a0e3d0","metadata_hash":"37b24953535255d4","model":"openai/gpt-5.2","tagged_at":"2026-01-20T18:40:52.654092+00:00"},"tags":{"pathology":["Healthy"],"modality":["Multisensory"],"type":["Other"],"confidence":{"pathology":0.8,"modality":0.6,"type":0.6},"reasoning":{"few_shot_analysis":"Relevant conventions from few-shot examples: (1) Datasets with explicitly clinical recruitment are labeled with that pathology and often get Type='Clinical/Intervention' (e.g., 'Cross-modal Oddball Task.' labeled Parkinson's + Clinical/Intervention). Here, no clinical recruitment is stated, so we follow the convention of labeling as Healthy when participants are described as neurotypical/healthy (e.g., multiple 'Healthy' examples). (2) For Modality, few-shot examples label based on the sensory channel of stimuli, not responses (e.g., 'Subcortical responses to music and speech...' -> Auditory; 'EEG Motor Movement/Imagery' -> Visual modality due to visual targets). This dataset includes tasks taken from ERP CORE, which spans multiple sensory paradigms, so the closest convention is to use Multisensory when the dataset includes multiple stimulus channels rather than a single dominant one (similar in spirit to the 'Cross-modal Oddball Task.' example using mixed sensory cues).","metadata_analysis":"Key metadata facts from the provided README: (1) Population: \"EEG data collected from 127 young adults (18-30 years)\" and tasks were \"optimized to capture neural activity ... in ... neurotypical young adults.\" (2) Study content/tasks: tasks were \"directly acquired from the Event-Related Potentials Compendium ... ERP CORE\" and were meant to capture \"perception, cognition, and action\"; additionally, \"the dataset includes a symptoms checklist ... predictive of symptoms consistent with ... ADHD\" but this is described as a measure for investigation rather than an explicit recruitment of an ADHD-diagnosed cohort.","paper_abstract_analysis":"No useful paper information.","evidence_alignment_check":"Pathology: Metadata says participants are \"127 young adults\" and explicitly \"neurotypical young adults\"; few-shot pattern suggests Healthy when no disorder-based recruitment is described. ALIGN.\nModality: Metadata says tasks are from \"ERP CORE\" and broadly span \"perception, cognition, and action\" but does not enumerate stimulus modalities; few-shot convention suggests labeling modality from stimulus channel, and when multiple channels are present across a dataset, Multisensory can be appropriate (cf. mixed-cue oddball example). PARTIAL ALIGN (requires inference due to missing explicit modality listing).\nType: Metadata frames the dataset around socioeconomic context effects on electrophysiology and includes multiple ERP CORE tasks capturing broad domains (\"perception, cognition, and action\") rather than a single construct; few-shot examples show assigning a focused Type when one paradigm dominates (e.g., Memory for digit span; Perception for discrimination). Here the broad/multi-paradigm aim fits best with Type='Other' rather than a single cognitive construct. ALIGN, but broadness reduces certainty.","decision_summary":"Pathology top-2: (A) Healthy — supported by \"neurotypical young adults\" and no disorder-based recruitment stated; (B) Development — plausible only because SES/childhood context is studied, but participants are adults and not a developmental clinical cohort. Winner: Healthy. Alignment: aligned with few-shot convention. Confidence 0.8 based on 2 explicit quotes about neurotypical young adults.\nModality top-2: (A) Multisensory — implied by using multiple ERP CORE paradigms (ERP CORE includes both auditory and visual tasks) and the README describing broad \"perception, cognition, and action\" tasks; (B) Visual — plausible if most ERP CORE tasks used were visual, but not stated. Winner: Multisensory due to multi-paradigm source, but inference-heavy. Confidence 0.6 (no direct explicit modality quote).\nType top-2: (A) Other — dataset aim is SES context + broad electrophysiology across multiple paradigms (\"perception, cognition, and action\"), not a single construct; (B) Attention — plausible given inclusion of ADHD symptom checklist and ERP CORE includes attention-related tasks, but ADHD is not the primary recruitment criterion and tasks span beyond attention. Winner: Other. Confidence 0.6 due to broad description and lack of a single stated primary construct."}},"computed_title":"Cognitive Electrophysiology in Socioeconomic Context in Adulthood","nchans_counts":[{"val":30,"count":357}],"sfreq_counts":[{"val":500.0,"count":357}],"stats_computed_at":"2026-04-22T23:16:00.310995+00:00","total_duration_s":null,"author_year":"Isbell2025_Cognitive","canonical_name":null}}