{"success":true,"database":"eegdash","data":{"_id":"6953f4249276ef1ee07a3368","dataset_id":"ds004582","associated_paper_doi":null,"authors":["Makowski, Dominique","Te, An-Shu","Kirk, Stephanie","Ngoi, Zi Liang"],"bids_version":"1.6.0","contact_info":null,"contributing_labs":null,"data_processed":false,"dataset_doi":"doi:10.18112/openneuro.ds004582.v1.0.0","datatypes":["eeg"],"demographics":{"subjects_count":73,"ages":[40,21,21,29,21,23,21,24,29,40,26,25,37,27,29,23,25,23,24,24,27,23,30,23,40,26,25,22,33,30,26,29,35,24,26,27,27,27,23,22,35,37,24,31,21,37,25,30,23,24,28,23,21,23,25,25,23,24,22,24,22,22,30,24,24,23,30,23,22,24,35,26,27,23,21,22],"age_min":21,"age_max":40,"age_mean":26.31578947368421,"species":null,"sex_distribution":{"m":37,"f":39},"handedness_distribution":null},"experimental_modalities":null,"external_links":{"source_url":"https://openneuro.org/datasets/ds004582","osf_url":null,"github_url":null,"paper_url":null},"funding":[],"ingestion_fingerprint":"5c02c53533fce64ae82272e766d02185116b2f86072e4d4ca6ff8855de7c58c5","license":"CC0","n_contributing_labs":null,"name":"FakeFaceEmo_data","readme":"# Overview\nThis dataset was collected in 2023 and comprises electroencephalography, physiological and behavioural data acquired from 73 healthy individuals (ages: 21-45). The task was administered as part of a larger study.\n# Task Description\n## Fake Face (FF)\nThe objective of the study was to investigate if emotional arousal would affect people's perceived realness of others' faces, given ambiguous information. To manipulate participants' emotional arousal, images of angry (high emotionality) and neutral (low emotionality) faces (selected based on the their rated intensity from the NimStim Set of Facial Expressions (Tottenham et al., 2009)), were used as subliminal primes and facial images from the Multi-Racial Mega-Resolution database (Strohminger et al., 2016) were used as target stimuli. Blank screens were flashed prior to the target presentation in control trials. Forward and backward masks, generated by scrambling the primes, were implemented to prevent the primes from breaking awareness.\nEach participant underwent a total of 222 trials, comprising of a forward mask,followed by the prime and backward mask, before the presentation of the target stimuli. The primes and targets were presented in a randomized order and trials were administered over a course of 3 blocks, between which participants were given a break to rest before proceeding to the next block of trials. During the presentation of the target stimulus, participants were instructed to indicate whether they thought the target was real or fake in a limited span of time (750ms), after which participants rated their confidence in their response using a sliding scale (0-100).\n# Data acquisition\n## EEG data acquisition\nEEG signals were recorded using the EasyCap 64-channel and BrainVision Recording system. Electrodes were placed on the EEG cap according to the standard 10-5 system of electrode placement (Oostenveld & Praamsrta, 2001) and impedance was kept below 12 kOhm for each subject. The ground electrode was placed on the forehead the Cz was used as the reference channel. During recording, the sampling rate was 10000Hz. Note that channels Tp9 and Tp10 were placed near the outer canthi of each eye, and POz as well as Oz were fixed above and below one of the eyes to measure the E0G.\n## Physiological data acquisition\nParticipants' physiological signals, that is their electrocardiogram (*ECG*), photoplethysmograph (PPG) and respiration signals (*RSP*), were obtained at a sampling frequency of 1000Hz. All physiological signals were recorded via the PLUX OpenSignals software and BITalino Toolkit.\nECG was collected using three ECG electrodes placed according to a modified Lead II configuration, and RSP was acquired using a respiration belt tightened over participants' upper abdomen. PPG sensors, which record changes in blood volume, were clipped on the tip of the index finger of participants' non-dominant hand to meaure heart rate and oxygen saturation.\nReferences\n----------\nAppelhoff, S., Sanderson, M., Brooks, T., Vliet, M., Quentin, R., Holdgraf, C., Chaumon, M., Mikulan, E., Tavabi, K., Höchenberger, R., Welke, D., Brunner, C., Rockhill, A., Larson, E., Gramfort, A. and Jas, M. (2019). MNE-BIDS: Organizing electrophysiological data into the BIDS format and facilitating their analysis. Journal of Open Source Software 4: (1896). https://doi.org/10.21105/joss.01896\nPernet, C. R., Appelhoff, S., Gorgolewski, K. J., Flandin, G., Phillips, C., Delorme, A., Oostenveld, R. (2019). EEG-BIDS, an extension to the brain imaging data structure for electroencephalography. Scientific Data, 6, 103. https://doi.org/10.1038/s41597-019-0104-8","recording_modality":["eeg"],"senior_author":null,"sessions":["01"],"size_bytes":315920201900,"source":"openneuro","study_design":null,"study_domain":null,"tasks":["FF"],"timestamps":{"digested_at":"2026-05-31T16:15:31.567154+00:00","dataset_created_at":null,"dataset_modified_at":null},"total_files":73,"storage":{"backend":"s3","base":"s3://openneuro.org/ds004582","raw_key":"dataset_description.json","dep_keys":["CHANGES","README","participants.json","participants.tsv"]},"nemar_citation_count":0,"computed_title":"FakeFaceEmo_data","nchans_counts":[{"val":64,"count":73}],"sfreq_counts":[{"val":10000.0,"count":73}],"stats_computed_at":"2026-05-31T19:34:32.599458+00:00","tags":{"pathology":["Healthy"],"modality":["Visual"],"type":["Perception","Affect"],"confidence":{"pathology":0.8,"modality":0.9,"type":0.8},"reasoning":{"few_shot_analysis":"The Meta-rdk example is the closest task match: participants make visual judgments and report confidence, and its type is Perception rather than Decision-making. The healthy three-armed-bandit example reserves Decision-making for choices about reward, unlike the face-realness judgment here.","metadata_analysis":"The readme identifies \"73 healthy individuals\". It says the study investigated whether \"emotional arousal would affect people's perceived realness of others' faces\". Participants saw \"images of angry ... and neutral ... faces\" as primes and facial images as \"target stimuli\", then indicated \"whether they thought the target was real or fake\" and rated confidence.","paper_abstract_analysis":"No useful paper information.","evidence_alignment_check":"Pathology: Metadata says \"73 healthy individuals\"; healthy-cohort few-shot examples suggest Healthy. ALIGN. Modality: Metadata describes face \"images\" as primes and \"target stimuli\"; the visual-discrimination few-shot suggests Visual. ALIGN. Type: Metadata specifies perceived face realness, a real-or-fake judgment, and an emotional-arousal manipulation. The Meta-rdk pattern suggests Perception despite a choice response and confidence rating. ALIGN for Perception; the explicit arousal aim additionally supports Affect, rather than replacing the perceptual aim with Decision-making.","decision_summary":"Pathology—Healthy versus Unknown: \"73 healthy individuals\" directly supports Healthy, with no recruited clinical condition; select Healthy (0.8: one explicit quote and strong healthy-cohort analog). Modality—Visual versus Multisensory: face \"images\", visual primes, and facial \"target stimuli\" support Visual; no second sensory stimulus channel is described; select Visual (0.9: three explicit features and a clear visual-task analog). Type—Perception versus Affect: the \"perceived realness\" aim and \"real or fake\" judgments support Perception, while the explicit aim to test \"emotional arousal\" and angry-versus-neutral primes independently support Affect. Select both as genuine linked aims (0.8: multiple explicit features and a strong perceptual-judgment analog). Decision-making is less apt because the response reports perceived authenticity, not choice policy or value."}},"total_duration_s":123277.6,"author_year":"Makowski2023_FakeFaceEmo","canonical_name":null,"bad_channels_info":null,"ethics_approvals":["NTU-IRB-2022-187"],"tagger_meta":{"model":"gpt-6-sol","taxonomy":"v2","config_hash":"39931253008fe2df","tagged_at":"2026-10-06T13:13:11Z","source":"eegdash-llm-tagger"}}}