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Faculty Experts Directory
Richard Aslin
Director, Rochester Center For Brain Imaging
Arts, Sciences, and Engineering
Department of Brain And Cognitive Sciences
Areas of expertise: Brain development, how infants learn
Press contact:
Susan Hagen
susan.hagen@rochester.edu
585.276.4061
Related Links:
Richard Aslin Home Page
Rochester Baby Lab
In the News
Parents.com
Speech Development in Toddlers
March 02, 2013
Guam Pacific Daily News
'Marshmallow test' offers new view on delayed gratification
December 01, 2012
Inside Higher Education
Mad Scientists and Marshmallows
October 21, 2012
CBS News
New "marshmallow test" suggests trust matters
October 16, 2012
USA Today
Updated marshmallow test offers insight on kids delayed gratification
October 16, 2012
Rochester Democrat & Chronicle
University of Rochester adds new twist to 'marshmallow experiment'
October 15, 2012
IOL
Being a pushy parent has little effect on your child
June 25, 2012
Philadelphia Inquirer
Babies are born to learn
June 01, 2012
Brisbane Courier-Mail
a pushy parent has little effect
May 25, 2012
Slate Magazine
An Uh, Er, Um Essay
July 26, 2011
IOL
Some pauses are, um, kinda important
May 04, 2011
MSN.co.in
Parents' "um"s' and "uh"s' help kids learn new words
April 25, 2011
USA Today
Psychology Erases the Idea of Children as ‘Blank Slates’
February 18, 2007
News Releases
Scientists Watch As Listener's Brain Predicts Speaker's Words
September 11, 2008
Professor of Brain and Cognitive Sciences Named President of International Society on Infant Studies
April 14, 2008
Two Researchers Elected to the American Academy of Arts and Sciences
April 28, 2006
Cognition Scientist Named William R. Kenan, Jr. Professor
May 28, 2004
Biography
Aslin studies how infancts gather information about the external world without the benefit of an extensive base. His most recent work has been directed to the rapid statistical learning of events that occur simultaneously in time and space. This statistical learning enables adults, children, infants, and monkeys to group sounds and images based solely on the information contained within the sound stream or visual image. These examples of unsupervised statistical learning illustrate that it is likely to play an important role in many domains, with more specialized forms of learning building.