{"success":true,"database":"eegdash","data":{"_id":"6953f4239276ef1ee07a32e2","dataset_id":"ds003670","associated_paper_doi":null,"authors":["Nigel Gebodh","Zeinab Esmaeilpour","Abhishek Datta","Marom Bikson"],"bids_version":"1.1.1","contact_info":["Nigel Gebodh"],"contributing_labs":null,"data_processed":false,"dataset_doi":"10.18112/openneuro.ds003670.v1.1.0","datatypes":["eeg"],"demographics":{"subjects_count":25,"ages":[43,40,31,33,32,31,20,22,19,22,21,20,28,36,30,29,35,30,20,31,30,29,29,29,30,30],"age_min":19,"age_max":43,"age_mean":28.846153846153847,"species":null,"sex_distribution":{"m":18,"f":8},"handedness_distribution":{"r":19,"l":7}},"experimental_modalities":null,"external_links":{"source_url":"https://openneuro.org/datasets/ds003670","osf_url":null,"github_url":null,"paper_url":null},"funding":["X (formerly Google X)","NIH R01NS095123","NIH R01NS101362","NIH R01NS112996","NIH R01MH111896","NIH R01MH109289","NIH-G-RISE T32GM136499"],"ingestion_fingerprint":"27a4eb608c1d1423ac6178fac350093a7c30fe42f3cf097706e97cd54821572c","license":"CC0","n_contributing_labs":null,"name":"Dataset of Concurrent EEG, ECG, and Behavior with Multiple Doses of transcranial Electrical Stimulation - BIDS","readme":"**Synopsis**\nThis is the **GX dataset** formatted to comply with [BIDS](https://bids.neuroimaging.io/) standard format.\nThe tES/EEG/CTT/Vigilance experiment contains 19 unique participants (some repeated experiments).\nOver a 70 min period EEG/ECG/EOG were recorded concurrently with a [CTT](https://sccn.ucsd.edu/~scott/pdf/COMPTRACK.pdf)\nwhere participants maintained a ball at the center of the screen\nand were periodically stimulated (with low-intensity noninvasive brain stimulation) for 30 secs with combinations of 9 stimulation montages.\nFor the **raw data** please see: https://zenodo.org/record/4456079\nFor methodological details please see corresponding article titled:\n    **Dataset of concurrent EEG, ECG, and behavior with multiple doses of transcranial Electrical Stimulation**\n**Data Descriptor Abstract**\nWe present a dataset combining human-participant high-density electroencephalography (EEG) with physiological and continuous behavioral metrics during transcranial electrical stimulation (tES). Data include within participant application of nine High-Definition tES (HD-tES) types, targeting three cortical regions (frontal, motor, parietal) with three stimulation waveforms (DC, 5 Hz, 30 Hz); more than 783 total stimulation trials over 62 sessions with EEG, physiological (ECG, EOG), and continuous behavioral vigilance/alertness metrics. Experiment 1 and 2 consisted of participants performing a continuous vigilance/alertness task over three 70-minute and two 70.5-minute sessions, respectively. Demographic data were collected, as well as self-reported wellness questionnaires before and after each session. Participants received all 9 stimulation types in Experiment 1, with each session including three stimulation types, with 4 trials per type. Participants received 2 stimulation types in Experiment 2, with 20 trials of a given stimulation type per session. Within-participant reliability was tested by repeating select sessions. This unique dataset supports a range of hypothesis testing including interactions of tDCS/tACS location and frequency, brain-state, physiology, fatigue, and cognitive performance.\nFor more details please see the full data descriptor article.\nCode used to import and process this dataset can be found here:\n**GitHub** : https://github.com/ngebodh/GX_tES_EEG_Physio_Behavior\nFor downsampled data please see:\n**Experiment 1** : https://doi.org/10.5281/zenodo.3840615\n**Experiment 2** : https://doi.org/10.5281/zenodo.3840617\n- Nigel Gebodh (May 26th, 2021)","recording_modality":["eeg"],"senior_author":"Marom Bikson","sessions":["01","02","03","04","05","06"],"size_bytes":77549594582,"source":"openneuro","study_design":null,"study_domain":null,"tasks":["GXtESCTT"],"timestamps":{"digested_at":"2026-04-22T12:25:37.737570+00:00","dataset_created_at":"2021-05-29T22:23:51.732Z","dataset_modified_at":"2021-06-17T20:13:01.000Z"},"total_files":62,"storage":{"backend":"s3","base":"s3://openneuro.org/ds003670","raw_key":"dataset_description.json","dep_keys":["CHANGES","README","participants.json","participants.tsv"]},"nemar_citation_count":6,"computed_title":"Dataset of Concurrent EEG, ECG, and Behavior with Multiple Doses of transcranial Electrical Stimulation - BIDS","nchans_counts":[{"val":35,"count":62}],"sfreq_counts":[{"val":2000.0,"count":62}],"stats_computed_at":"2026-04-22T23:16:00.222339+00:00","tags":{"pathology":["Healthy"],"modality":["Visual"],"type":["Clinical/Intervention"],"confidence":{"pathology":0.7,"modality":0.8,"type":0.8},"reasoning":{"few_shot_analysis":"Closest few-shot by task/paradigm is the DPX continuous performance dataset (\"EEG: DPX Cog Ctl Task in Acute Mild TBI\"), which is labeled Modality=Visual and Type=Attention; this supports mapping sustained/continuous performance paradigms with on-screen cues/tracking demands to Visual input and an attention/vigilance construct. However, unlike the DPX example, the current dataset’s defining manipulation is transcranial electrical stimulation (tES) across montages/waveforms, which (by labeling convention) can shift the Type toward Clinical/Intervention even in non-clinical cohorts because the primary research purpose is effects of an intervention/stimulation. For Pathology, multiple few-shots show that when no disorder is used to recruit participants, Pathology=Healthy (e.g., \"EEG: Three armed bandit gambling task\", \"EEG Motor Movement/Imagery Dataset\").","metadata_analysis":"Key population/task/stimulus facts from metadata:\n1) Intervention/study design: \"participants ... were periodically stimulated (with low-intensity noninvasive brain stimulation) for 30 secs with combinations of 9 stimulation montages.\" And: \"within participant application of nine High-Definition tES (HD-tES) types\" with \"three stimulation waveforms (DC, 5 Hz, 30 Hz).\"\n2) Task/visual stimulus: \"Over a 70 min period EEG/ECG/EOG were recorded concurrently with a CTT where participants maintained a ball at the center of the screen\" (visual tracking/continuous task).\n3) Construct focus: \"performing a continuous vigilance/alertness task\" and dataset supports hypotheses including \"fatigue, and cognitive performance.\"\n4) Population: \"contains 19 unique participants\" and participants_overview lists only demographics: \"Age range: 19-43; Handedness...\" with no clinical diagnosis mentioned.","paper_abstract_analysis":"Useful information is embedded directly in the README as a \"Data Descriptor Abstract\": it emphasizes an intervention dataset: \"high-density electroencephalography (EEG) ... during transcranial electrical stimulation (tES)\" and highlights experimental manipulation across \"nine High-Definition tES (HD-tES) types\" and outcome as \"continuous behavioral vigilance/alertness metrics.\" This reinforces Type=Clinical/Intervention and the vigilance task context.","evidence_alignment_check":"Pathology:\n- Metadata says: no disorder recruitment is described; only \"19 unique participants\" and demographic-only \"Age range: 19-43\".\n- Few-shot pattern suggests: when no clinical condition is specified, label as Healthy.\n- Alignment: ALIGN (no explicit pathology; matches Healthy convention).\n\nModality:\n- Metadata says: visual display/task demand: \"maintained a ball at the center of the screen\".\n- Few-shot pattern suggests: continuous performance tasks with screen-based stimuli are Visual (DPX example labeled Visual).\n- Alignment: ALIGN.\n\nType:\n- Metadata says: primary manipulation is stimulation: \"during transcranial electrical stimulation (tES)\" with \"nine ... tES types\"; task described as \"continuous vigilance/alertness task\".\n- Few-shot pattern suggests: continuous performance/vigilance tasks can map to Attention (DPX example).\n- Alignment: PARTIAL CONFLICT (metadata strongly emphasizes intervention/stimulation as the core dataset purpose; few-shot task-based mapping points to Attention). Resolution: choose Clinical/Intervention because the dataset’s defining feature is multi-dose/parameter tES (intervention), with vigilance task serving as the behavioral probe.","decision_summary":"Top-2 candidates per category with head-to-head selection:\n\nPathology:\n1) Healthy (SELECTED) — Evidence: no diagnosis/clinical cohort stated; only demographics (\"19 unique participants\"; \"Age range: 19-43\"). Matches few-shot convention where non-clinical participants are labeled Healthy.\n2) Unknown — Would apply if population health status were unclear; but absence of any disorder framing plus standard adult demographics makes Healthy more consistent.\nConfidence basis: no explicit word \"healthy\" but strong absence-of-pathology evidence across multiple metadata lines.\n\nModality:\n1) Visual (SELECTED) — Evidence: \"maintained a ball at the center of the screen\"; task is a continuous tracking task on-screen.\n2) Other — Could be argued because electrical stimulation is applied, but modality is defined as sensory/input channel of stimuli, and the task’s input is visual.\nConfidence basis: two direct visual-task descriptions.\n\nType:\n1) Clinical/Intervention (SELECTED) — Evidence: \"during transcranial electrical stimulation (tES)\"; \"nine High-Definition tES (HD-tES) types\"; \"three stimulation waveforms\"; hypotheses about \"interactions of tDCS/tACS location and frequency\".\n2) Attention — Evidence: \"continuous vigilance/alertness task\" resembles few-shot continuous performance/attention paradigms.\nConfidence basis: multiple explicit intervention-focused quotes outweigh the attention-task framing, but attention remains a plausible runner-up."}},"total_duration_s":261979.43899999998,"tagger_meta":{"config_hash":"3557b68bca409f28","metadata_hash":"62049169399f776b","model":"openai/gpt-5.2","tagged_at":"2026-04-07T09:32:40.872789+00:00"},"canonical_name":null,"name_confidence":0.72,"name_meta":{"suggested_at":"2026-04-14T10:18:35.342Z","model":"openai/gpt-5.2 + openai/gpt-5.4-mini + deterministic_fallback"},"name_source":"author_year","author_year":"Gebodh2021"}}