{"dataset":{"id":"61130","dataset_id":"on005863","name":"Cognitive Electrophysiology in Socioeconomic Context in Adulthood","description":"This dataset contains EEG recordings from 127 young adults (18-30 years) collected alongside measures of childhood and adulthood socioeconomic status (SES), including educational attainment, income, food security, and neighborhood characteristics. EEG tasks were drawn from or adapted from the ERP CORE resource, designed to elicit neural activity related to perception, cognition, and action. The dataset also includes an ADHD symptoms checklist, enabling investigation of relationships between SES, ADHD symptoms, and neural activity in a socioeconomically diverse adult sample.","owner_user_id":15,"status":"active","github_repo":"nemarDatasets/on005863","concept_doi":"10.82901/nemar.on005863","latest_version_doi":"10.82901/nemar.on005863.v1.0.0","created_at":"2026-06-28 02:31:06","updated_at":"2026-08-19 01:11:31","zenodo_concept_id":null,"is_sandbox":0,"visibility":"public","ezid_status":"public","enrichment_json":"{\n  \"version\": \"2.0\",\n  \"pipeline_stage\": \"enriched\",\n  \"title\": \"Cognitive Electrophysiology in Socioeconomic Context in Adulthood\",\n  \"description\": \"This dataset contains EEG recordings from 127 young adults (18-30 years) collected alongside measures of childhood and adulthood socioeconomic status (SES), including educational attainment, income, food security, and neighborhood characteristics. EEG tasks were drawn from or adapted from the ERP CORE resource, designed to elicit neural activity related to perception, cognition, and action. The dataset also includes an ADHD symptoms checklist, enabling investigation of relationships between SES, ADHD symptoms, and neural activity in a socioeconomically diverse adult sample.\",\n  \"methods_description\": \"EEG data were recorded using tasks directly acquired from or adapted from the ERP CORE battery, designed to capture neural correlates of perception, cognition, and action. Identifiable information (date of birth, race/ethnicity, zip code, languages spoken) was removed prior to sharing, and participant IDs and raw EEG files were renamed for BIDS compatibility.\",\n  \"license\": \"CC0\",\n  \"dataset_type\": \"raw\",\n  \"authors\": {\n    \"Elif Isbell\": {\n      \"orcid\": \"0000-0002-4928-2438\"\n    },\n    \"Amanda N. Peters\": {},\n    \"Dylan M. Richardson\": {},\n    \"Nancy E. R. De León\": {}\n  },\n  \"keywords\": [\n    {\n      \"term\": \"EEG\"\n    },\n    {\n      \"term\": \"event-related potentials\"\n    },\n    {\n      \"term\": \"Low Socioeconomic Status\",\n      \"subject_scheme\": \"MeSH\",\n      \"scheme_uri\": \"https://id.nlm.nih.gov/mesh/\",\n      \"value_uri\": \"http://id.nlm.nih.gov/mesh/D000092886\"\n    },\n    {\n      \"term\": \"attention-deficit/hyperactivity disorder\"\n    },\n    {\n      \"term\": \"Cognition\",\n      \"subject_scheme\": \"MeSH\",\n      \"value_uri\": \"http://id.nlm.nih.gov/mesh/D003071\"\n    },\n    {\n      \"term\": \"adulthood\"\n    },\n    {\n      \"term\": \"ERP CORE\"\n    },\n    {\n      \"term\": \"income\"\n    },\n    {\n      \"term\": \"food security\"\n    }\n  ],\n  \"related_identifiers\": [\n    {\n      \"identifier\": \"https://github.com/nemarDatasets/on005863\",\n      \"identifier_type\": \"URL\",\n      \"relation_type\": \"IsDescribedBy\"\n    },\n    {\n      \"identifier\": \"https://nemar.org/dataset/on005863\",\n      \"identifier_type\": \"URL\",\n      \"relation_type\": \"IsDescribedBy\"\n    },\n    {\n      \"identifier\": \"10.18112/openneuro.ds005863.v2.0.0\",\n      \"identifier_type\": \"DOI\",\n      \"relation_type\": \"IsDerivedFrom\"\n    }\n  ],\n  \"funding_references\": [\n    {\n      \"funder_name\": \"research start-up funds awarded to Elif Isbell by University of California Merced.\"\n    },\n    {\n      \"funder_name\": \"University of California Merced\",\n      \"award_title\": \"research start-up funds awarded to Elif Isbell\"\n    }\n  ],\n  \"resource_type_general\": \"Dataset\",\n  \"resource_type_specific\": \"EEG Dataset\",\n  \"modalities\": [\n    \"eeg\"\n  ],\n  \"sizes\": [\n    \"11.4 GB (1072 files)\"\n  ],\n  \"formats\": [\n    \".eeg\",\n    \".json\",\n    \".md\",\n    \".tsv\",\n    \".vhdr\",\n    \".vmrk\",\n    \".yml\"\n  ],\n  \"source_hash\": \"fa1d3c80aa58c4376608299c6b85192b96f6e8483b2deded0baa823eaac6a86e\"\n}","last_activity_at":"2026-06-28 02:31:06","source":"openneuro","source_id":"ds005863","subject_count":127,"modalities":"eeg","age_min":18.26,"age_max":30.07,"file_size":11371794005,"total_files":2151,"tasks":"auditoryoddball,flanker,visualoddball,visualsearch","metadata_columns_error":null,"staleness_warn_stage":null,"staleness_admin_notified_at":null,"authors":"Elif Isbell, Amanda N. Peters, Dylan M. Richardson, Nancy E. R. De León","license":"CC0","readme":"[![DOI](https://img.shields.io/badge/DOI-10.82901%2Fnemar.on005863-blue)](https://doi.org/10.82901/nemar.on005863)\n\n## The “Cognitive Electrophysiology in Socioeconomic Context in Adulthood” Dataset\n\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\n\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\n\n# Copyright and License\nThis dataset is licensed under CC0. \n\n\n# References\n\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.\n\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. 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