Developmental Trajectory of Anticipation: Insights from Sequential Comparative Judgments

Area of Science:

• Cognitive Psychology
• Neuroscience
• Human Development

Background:

• Reaction time (RT) distribution provides insights into cognitive processes and task strategies.
• Previous research identified a bimodal RT distribution in sequential comparisons, suggesting reactive and anticipatory response strategies.
• The developmental trajectory and modifiability of these strategies remain less understood.

Purpose of the Study:

• To investigate if the bimodal RT distribution extends to various sequential comparative judgments.
• To examine the developmental evolution of fast (anticipatory) and slow (reactive) response strategies from childhood to adulthood.
• To determine if these strategies are linked to anticipation using computational modeling and if they are amenable to instructional modulation.

Main Methods:

• Distributional and theoretical analysis of RT data from 158 subjects across four sequential comparative judgment tasks (numerosity, phonological, multiplication, subtraction).
• Application of mixture models to confirm developmental trends and diffusion models to assess anticipatory processes.
• An online experiment with 236 participants involving numerosity comparisons before and after instructions favoring reactive or anticipatory responses.

Main Results:

• Group RT distributions were consistently bimodal across all tested tasks, with strategies differing in speed and accuracy.
• The fast, anticipatory strategy emerged and increased from childhood to adulthood, though less frequent in adolescents than adults.
• Computational models supported the distinction between reactive and anticipatory processes, and the online experiment showed that response strategy proportions could be modulated by instructions.

Conclusions:

• The bimodal RT distribution in sequential comparisons is a robust phenomenon across different tasks and ages.
• Cognitive strategies in sequential comparisons show clear developmental progression and are influenced by anticipatory processes.
• Individual RT distributions and computational modeling are valuable tools for assessing cognitive decision-making processes, with implications for understanding anticipation in cognition.