Perceptual Decision-Making in Children: Age-Related Differences and EEG Correlates

Area of Science:

• Cognitive Neuroscience
• Developmental Psychology
• Computational Neuroscience

Background:

• Children's decision-making accuracy and speed improve with age.
• The specific cognitive processes underlying these age-related improvements remain unclear.

Purpose of the Study:

• To investigate age-related changes in perceptual decision-making components using hierarchical Bayesian diffusion models.
• To link these cognitive components to neural data (EEG) in children.

Main Methods:

• Collected behavioral and electroencephalography (EEG) data from 96 children (6-12 years) and 20 adults performing a motion discrimination task.
• Applied hierarchical Bayesian diffusion models to decompose decision performance into drift rate, boundary separation, and non-decision time.
• Identified and analyzed two response-locked EEG components with ramping activity.

Main Results:

• Younger children exhibited lower drift rates (reduced sensitivity) and wider boundary separation (increased caution) compared to older children and adults.
• Model comparisons indicated age effects primarily on drift rate and boundary separation, not non-decision time.
• The slope of centro-parietal EEG activity positively correlated with drift rate, suggesting a neural basis for decision sensitivity.

Conclusions:

• Hierarchical Bayesian diffusion models effectively decompose age-related differences in perceptual decision-making.
• Neural activity in centro-parietal regions is associated with decision sensitivity in children.
• This approach can reveal processing differences in children, including those with developmental conditions, not apparent from accuracy and reaction time alone.