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Area of Science:

  • Cognitive neuroscience
  • Developmental psychology
  • Computational psychiatry

Background:

  • Autism spectrum disorder (ASD) research often uses reaction time (RT) and accuracy, which may conflate processing efficiency with response caution.
  • Distinguishing these components is crucial for a nuanced understanding of cognitive differences in ASD.

Purpose of the Study:

  • To investigate if computational models of decision-making can isolate processing efficiency and caution in adolescents with ASD.
  • To compare model parameters between adolescents with ASD and neurotypical controls using face-processing tasks.

Main Methods:

  • Utilized data from face recognition and eye-gaze discrimination tasks in adolescents with ASD and a matched comparison group.
  • Applied computational models to estimate parameters for processing efficiency, caution, and perceptual/motor speed.

Main Results:

  • Adolescents with ASD exhibited reduced processing efficiency and caution compared to controls.
  • Model parameters offered superior discrimination between ASD and control groups versus traditional RT and accuracy measures.
  • A correlation between ADHD symptoms and lower processing efficiency was observed in autistic adolescents.

Conclusions:

  • Decision-making models offer enhanced discriminability for identifying ASD.
  • These models provide a more specific understanding of the cognitive mechanisms underlying differences in ASD.