An EEG Dataset of Neural Signatures in a Competitive Two-Player Game Encouraging Deceptive Behavior

Yiyu Chen, Siamac Fazli, Christian Wallraven

    Research output: Contribution to journalArticlepeer-review

    1 Citation (Scopus)

    Abstract

    Studying deception is vital for understanding decision-making and social dynamics. Recent EEG research has deepened insights into the brain mechanisms behind deception. Standard methods in this field often rely on memory, are vulnerable to countermeasures, yield false positives, and lack real-world relevance. Here, we present a comprehensive dataset from an EEG-monitored competitive, two-player card game designed to elicit authentic deception behavior. Our extensive dataset contains EEG data from 12 pairs (N = 24 participants with role switching), controlled for age, gender, and risk-taking, with detailed labels and annotations. The dataset combines standard event-related potential and microstate analyses with state-of-the-art decoding approaches of four scenarios: spontaneous/instructed truth-telling and lying. This demonstrates game-based methods’ efficacy in studying deception and sets a benchmark for future research. Overall, our dataset represents a unique resource with applications in cognitive neuroscience and related fields for studying deception, competitive behavior, decision-making, inter-brain synchrony, and benchmarking of decoding frameworks in a difficult, high-level cognitive task.

    Original languageEnglish
    Article number389
    JournalScientific data
    Volume11
    Issue number1
    DOIs
    Publication statusPublished - 2024 Dec

    Bibliographical note

    Publisher Copyright:
    © The Author(s) 2024.

    ASJC Scopus subject areas

    • Statistics and Probability
    • Information Systems
    • Education
    • Computer Science Applications
    • Statistics, Probability and Uncertainty
    • Library and Information Sciences

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