Statistical learning and brain plasticity

25th Symposium: June 1-3, 2006

Perceptual and Motor Learning
Chair: David Williams

Mario Svirsky, Indiana University
Learning to understand frequency-shifted, spectrally degraded speech

Jason Gold, Indiana University
Signal and noise in perceptual learning

Reza Shadmehr, Johns Hopkins University
Internal models, adaptation, and uncertainty

Alexandre Pouget, University of Rochester
Neural basis of perceptual learning: haven't we solved this issue already?

Learning: Role of Priors and Attention
Chair: Robbie Jacobs

David Knill, University of Rochester
Learning Bayesian priors for depth perception

Marvin Chun, Yale University
Attentional control of perceptual memory

Nick Chater, University College London
Simplicity, probability and perception

Josh Tenenbaum, Massachusetts Institute of Technology
Statistical learning of abstract knowledge

Constraints on Pattern Learning
Chair: Michael Weliky

Lori Holt, Carnegie Mellon University
Auditory categorization and tuning in speech perception

Daniel Margoliash, University of Chicago
Pattern perception in songbirds

Richard Aslin, University of Rochester
Statistical learning of visual patterns: Helmholtz, Bayes, and Dr. Spock

Toby Mintz, University of Southern California
Learning syntactic categories from patterns in linguistic input

Neural Mechanisms of Learning
Chair: Lizabeth Romanski

Takao Hensch, Riken Institute
Distinct adult perceptual learning and critical period plasticity in visual cortex

Anthony Zador, Cold Spring Harbor Laboratory
How many synapses must change to form a memory?

Nathaniel Daw, University College London, Gatsby
Reward & exploration in human decision making

Leo Sugrue, Stanford University
Choosing the greater of two goods: a combined behavioral, modeling, and physiological approach to value based decision making.

Maturation and Plasticity
Chair: Daphne Bavelier

Daphne Maurer, McMaster University
Missed sights: consequences for visual development

Brian Wandell, Stanford University
Maps and reading development in visual cortex

Elissa Newport, University of Rochester
Statistical language learning: computational and maturational constraints

Randy Gallistel, Rutgers University
Is mutual information the learning-relevant parameter of conditioning protocols?

Sponsored by the Office for Naval Research

Organizing Committee:
Richard Aslin
Daphne Bavelier
Alexandre Pouget