EEG and EMG Signals for Emotion-Antecedent Appraisal Checks

Electroencephalography (EEG) and facial electromyography (EMG) signals were collected in a study by van Peer, Grandjean and Scherer (2014). The data were used to investigate the sequential unfolding of novelty and intrinsic pleasantness appraisals using an oddball paradigm with affective pictures. The dataset was made public by Coutinho, Gentsch, van Peer, Scherer and Schuller for their subsequent analysis.

Use Cases

• Analyzing temporal patterns of cognitive processing based on EEG signals mentioned in the description
• Investigating efferent motor responses to emotional stimuli based on facial EMG data
• Testing models of appraisal sequence and independence based on the experimental manipulation of novelty and pleasantness
• Developing multimodal emotion recognition algorithms based on combined EEG and EMG time-series

Strengths

• Data originates from a published peer-reviewed study (van Peer et al., 2014) in the journal Emotion
• Pre-processing steps were revised to improve artifact detection compared to the original study
• Includes both EEG (cognitive) and facial EMG (efferent) measurements for a multimodal perspective

Limitations

• Column-level documentation is absent; field semantics must be inferred after download
• Row count and file size are unknown, which may limit suitability assessment
• Last update date is unknown; freshness unverified

Provenance

Source

Radboud University Nijmegen, based on a study by Jacobien M. van Peer and colleagues.

Collection Method

Collected using an oddball paradigm with affective pictures to manipulate novelty and pleasantness appraisals.