Biography

Scott P. Johnson is a Professor of Psychology and a Professor of Psychiatry & Biobehavioral Sciences at UCLA, and he directs research at the UCLA Baby Lab. He earned his PhD from Arizona State University and conducted postdoctoral research at the Center for Visual Science at the University of Rochester. His work has been supported since 1995 by grants from the ESRC, NSF, and NIH, and he has provided editorial service to several journals (e.g., Child Development, Cognition, Developmental Psychology, Infancy) and national and international granting agencies. Johnson's research examines perceptual, cognitive, motor, social, and cortical development in typically-developing infants and infants at elevated risk for autism. Current research interests focus on social cognition, visual attention, and learning mechanisms in infancy.

2-100 - Constraints on Statistical Learning in Infancy

Session Type: Invited Address

Integrative Statement

Statistical learning is the process of identifying patterns of probabilistic co-occurrence among stimulus features, essential to our ability to perceive the world as predictable and stable. Research on auditory statistical learning has revealed that infants use statistical properties of linguistic input to discover structure--including sound patterns, words, and the beginnings of grammar--that may facilitate language acquisition. Previous research on visual statistical learning revealed abilities to discriminate probabilities in visual sequences, leading to claims of a domain-general learning device that is available early in life, perhaps at birth. In this talk, I will present new research on visual statistical learning, rule learning, finite state grammar learning, and causal structure learning from infants, adults, and computational models. This research challenges claims of domain-generality and works toward the twin goals of understanding perceptual and memory constraints on learning and providing a mechanistic explanation of the computations underlying performance in statistical learning tasks.

Sub Unit

• SRCD Biennial Meeting

Chair

• Amanda Woodward, University of Chicago

Speaker

• Scott P Johnson, University of California, Los Angeles