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

Area of Science:

• Cognitive Neuroscience
• Neuroscience
• Psychology

Background:

• Deception research is crucial for understanding decision-making and social dynamics.
• Existing electroencephalography (EEG) methods for deception detection have limitations, including reliance on memory, vulnerability to countermeasures, and lack of real-world applicability.
• There is a need for more ecologically valid methods to study deception.

Purpose of the Study:

• To present a comprehensive dataset of EEG recordings from participants engaged in authentic deception within a controlled, competitive game environment.
• To establish a benchmark for future research on deception using game-based paradigms.
• To provide a resource for investigating cognitive processes underlying deception, decision-making, and social interactions.

Main Methods:

• Collected EEG data from 24 participants (12 pairs) in a two-player card game involving spontaneous and instructed truth-telling and lying.
• Controlled for participant demographics (age, gender) and risk-taking propensity.
• Applied standard event-related potential (ERP) and microstate analyses, alongside advanced decoding techniques.

Main Results:

• The game-based paradigm successfully elicited authentic deception behaviors.
• The dataset includes detailed event markers and annotations for various cognitive states.
• Demonstrated the feasibility of using advanced decoding approaches on the collected EEG data.

Conclusions:

• Game-based paradigms are effective for studying authentic deception in a controlled setting.
• The dataset provides a valuable resource for cognitive neuroscience, enabling research into deception, competitive behavior, and decision-making.
• This work facilitates the benchmarking of decoding frameworks for complex cognitive tasks.