{"success":true,"database":"eegdash","data":{"_id":"6953f4249276ef1ee07a3464","dataset_id":"ds006761","associated_paper_doi":null,"authors":["Moerel, Denise","Grootswagers, Tijl","Chin, Jessica L.L.","Ciardo, Francesca","Nijhuis, Patti","Quek, Genevieve L.","Smit, Sophie","Varlet, Manuel"],"bids_version":"1.0.2","contact_info":["Denise Moerel"],"contributing_labs":null,"data_processed":false,"dataset_doi":"doi:10.18112/openneuro.ds006761.v1.0.0","datatypes":["eeg"],"demographics":{"subjects_count":31,"ages":[],"age_min":null,"age_max":null,"age_mean":null,"species":null,"sex_distribution":null,"handedness_distribution":null},"experimental_modalities":null,"external_links":{"source_url":"https://openneuro.org/datasets/ds006761","osf_url":null,"github_url":null,"paper_url":null},"funding":["ARC DP220103047 (MV)","H2020 Marie Curie 893960 (FC)","ARC DE230100380 (TG)"],"ingestion_fingerprint":"7c548323adc0acc8a959837d198c8385bb6d7778ab8210b4e86cf9303978d989","license":"CC0","n_contributing_labs":null,"name":"Neural decoding of competitive decision-making in Rock-Paper-Scissors","readme":"Experiment Details\nParticipants played a computerised version of the competitive Rock-Paper-Scissors game (480 games). We recorded 64 channel EEG from 62 participants, grouped into 31 pairs.\nExperiment length: 1 hour\nMore information:\nhttps://doi.org/10.17605/OSF.IO/YJXKN (OSF repository with more information and analysis code)\nMoerel, D., Grootswagers, T., Chin, J. L., Ciardo, F., Nijhuis, P., Quek, G. L., Smit, S. & Varlet, M. (2025). Neural decoding of competitive decision-making in Rock-Paper-Scissors. Social Cognitive And Affective Neuroscience, nsaf101. doi: https://doi.org/10.1093/scan/nsaf101","recording_modality":["eeg"],"senior_author":"Varlet, Manuel","sessions":[],"size_bytes":83755152274,"source":"openneuro","study_design":null,"study_domain":null,"tasks":["RPS"],"timestamps":{"digested_at":"2026-04-22T12:29:35.691783+00:00","dataset_created_at":"2025-10-08T00:56:21.789Z","dataset_modified_at":"2025-10-08T06:16:05.000Z"},"total_files":31,"storage":{"backend":"s3","base":"s3://openneuro.org/ds006761","raw_key":"dataset_description.json","dep_keys":["CHANGES","README.txt","participants.json","participants.tsv"]},"tagger_meta":{"config_hash":"4a051be509a0e3d0","metadata_hash":"c9d46c582ca6c5fe","model":"openai/gpt-5.2","tagged_at":"2026-01-20T19:07:26.841462+00:00"},"tags":{"pathology":["Healthy"],"modality":["Visual"],"type":["Decision-making"],"confidence":{"pathology":0.6,"modality":0.6,"type":0.8},"reasoning":{"few_shot_analysis":"Most similar few-shot conventions: (1) \"EEG: Three armed bandit gambling task\" maps a game-like choice task to Type=Afffect (because reward/affect focus), but it demonstrates the convention that trial-based game/choice EEG is typically labeled as a higher-level cognitive construct rather than \"Perception\" or \"Motor\". (2) \"EEG: Reinforcement Learning in Parkinson's\" maps choice+feedback paradigms to Type=Decision-making. (3) \"Meta-rdk\" (visual discrimination + confidence report) shows that even when responses are motor (mouse), modality is assigned based on stimulus channel (Visual). These examples guide labeling Rock-Paper-Scissors as a decision/strategy task with stimulus modality inferred from a computerized game display.","metadata_analysis":"Key facts from provided README: (1) \"Participants played a computerised version of the competitive Rock-Paper-Scissors game (480 games).\" (2) \"We recorded 64 channel EEG from 62 participants, grouped into 31 pairs.\" (3) Citation/title embedded in README: \"Neural decoding of competitive decision-making in Rock-Paper-Scissors.\" No recruitment of a clinical group is described; task is an interactive competitive choice game. Stimulus modality is not explicitly stated (e.g., \"visual cues\"), but \"computerised\" strongly suggests on-screen presentation.","paper_abstract_analysis":"No useful paper information beyond the paper title/citation embedded in the README (no abstract text provided).","evidence_alignment_check":"Pathology: Metadata says nothing about a disorder/diagnosis (e.g., only \"62 participants\"); few-shot convention is to label non-clinical volunteer datasets as Healthy. ALIGN.\nModality: Metadata does not explicitly name the sensory modality (no \"visual\"/\"auditory\" terms). Few-shot convention (e.g., motor imagery dataset and visual discrimination task) assigns modality by stimulus channel; for a \"computerised\" game this suggests Visual. PARTIAL ALIGN but relies on inference.\nType: Metadata explicitly frames the construct as decision-making via the citation \"competitive decision-making\"; few-shot examples for choice/game paradigms support Type=Decision-making rather than Perception/Motor. ALIGN.","decision_summary":"Pathology top-2: (A) Healthy — supported by absence of any clinical recruitment info and generic \"62 participants\" in README; (B) Unknown — possible if participant health status is not stated. Winner: Healthy. Evidence alignment: aligns with few-shot convention for non-clinical samples. Confidence justified by only indirect evidence (no explicit \"healthy controls\" phrase).\nModality top-2: (A) Visual — inferred from \"computerised version\" of the game; (B) Unknown — modality not explicitly stated. Winner: Visual (weakly). Evidence alignment: few-shot convention supports stimulus-based modality assignment, but metadata is not explicit. Confidence low-moderate.\nType top-2: (A) Decision-making — directly supported by \"competitive decision-making\" in the embedded citation and the nature of Rock-Paper-Scissors as repeated choices; (B) Other — could be framed as social interaction/competition more broadly, but no dedicated label exists. Winner: Decision-making. Confidence supported by explicit phrase + strong few-shot analog (choice tasks)."}},"computed_title":"Neural decoding of competitive decision-making in Rock-Paper-Scissors","nchans_counts":[{"val":64,"count":31}],"sfreq_counts":[{"val":2048.0,"count":31}],"stats_computed_at":"2026-04-22T23:16:00.311929+00:00","total_duration_s":null,"author_year":"Moerel2025_Neural","canonical_name":null}}