Using drift diffusion modeling to understand inattentive behavior in preterm and term-born children.

Area of Science:

• Cognitive Neuroscience
• Developmental Psychology
• Clinical Psychology

Background:

• Children born very preterm (VP) face higher risks of inattention.
• Cognitive processes underlying inattention in VP children may differ from term-born peers.
• Standard reaction time (RT) measures may not fully capture inattention mechanisms.

Purpose of the Study:

• To compare cognitive processes related to inattention in VP and term-born children using drift diffusion modeling (DDM).
• To assess if DDM provides better characterization of inattention than standard RT measures.
• To determine if mechanisms of inattention differ between VP and term-born children.

Main Methods:

• Compared performance on a cued continuous performance task in 33 VP (≤32 weeks gestation) and 32 term-born children (8-11 years).
• Utilized standard measures (RT, variability, accuracy) and DDM to analyze task performance.
• Employed hierarchical regression to link standard and DDM measures to parent-rated inattention.

Main Results:

• No significant group differences were found in standard or DDM task performance measures.
• Parent-rated inattention correlated with hit rate, RT variability, and drift rate (DDM processing efficiency).
• Drift rate emerged as the strongest predictor of parent-rated inattention, with similar relationships across groups.

Conclusions:

• Less efficient information processing is a shared mechanism for inattention in both VP and term-born children.
• DDM offers valuable insights into atypical cognitive processing in clinical populations.
• Findings highlight the utility of DDM for understanding inattention across developmental groups.