Brain Processes While Struggling With Evidence Accumulation During Facial Emotion Recognition: An ERP Study

Area of Science:

• Cognitive Neuroscience
• Neuroscience
• Psychology

Background:

• Human brain excels at recognizing emotional facial expressions in upright faces.
• Contributions of featural, configural, and holistic processing to emotion recognition decision-making are not fully understood.

Purpose of the Study:

• Investigate the role of early face-sensitive processes in emotion recognition.
• Determine how experimental conditions affect neuroelectric reflections and evidence accumulation using a diffusion decision model (DDM).

Main Methods:

• Examined effects of stimulus orientation (upright vs. inverted) and type (photographs vs. sketches) on behavior and event-related potentials (ERPs).
• Explored shared variance between ERPs and DDM parameters.
• Utilized a diffusion decision model (DDM) to analyze decision-making processes.

Main Results:

• N170 latency is affected by stimulus inversion and simplification.
• Increased N170 activity is necessary to overcome negative impacts of face inversion on decision-making speed (drift rate) and stimulus encoding.
• Emotion recognition is possible with degraded stimuli but incurs a neurocognitive cost.

Conclusions:

• P100 provides holistic facial reference via categorical encoding.
• N170 maintains facial expression configural information through coordinate encoding.
• P250 normalizes facial features against internal representations of emotions.