Richard N. Aslin

Richard N. Aslin

PhD, University of Minnesota, 1975
William R. Kenan Professor, Brain & Cognitive Sciences and Center for Visual Science
Director, Rochester Center for Brain Imaging

Contact Information

  • Meliora 316
  • Brain & Cognitive Sciences
  • University of Rochester
  • Rochester, NY 14627-0268
  • (585) 275-8687 (office)
  • (585) 275-4621 (lab)
  • (585) 442-9216 (fax)

Office Hours

By appointment.

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Research Overview

During the course of development, human infants gather information about the external world without the benefit of an extensive base of knowledge that adults automatically bring to bear on perceptual, motor, cognitive, and language tasks. What mechanisms allow infants to acquire this initial level of information and how does that information guide subsequent learning? Clearly, most learning that occurs in infancy, and a substantial amount of learning in adulthood, is performed without instruction—it is implicit and based on an analysis of the distributional properties of environmental stimulation.

For over a decade, my research has been directed at exploring and understanding these implicit learning mechanisms, which are typically referred to as "statistical learning". Although initially studied in the task of word segmentation from fluent speech, statistical learning has been extended to other domains, such as musical tones, phonetic categories, sequences of visual shapes, sequences of motor responses, and combinations of objects (or object parts) in complex visual scenes. An important goal of these studies is to reveal the computational constraints that enable statistical learning to be tractable given the complexity of the input and the infinite number of statistical computations that are possible over any set of inputs. Initial computational models of statistical learning focused on bi-gram statistics and conditional probabilities, but more recent work has broadened to include Bayesian ideal learning models. Empirical studies of statistical learning have also evolved to explore order effects in learning multiple structures and to understand how statistical patterns trigger the formation of categories.

A related line of research focuses on spoken word recognition in both infants, toddlers, and adults using eye-tracking methods. Once an auditory word-form has been extracted from fluent speech, how does the infant map that sequence of sounds onto meaning? Recent and on-going studies have examined how infants and toddlers recognize the meaning of the unfolding speech signal, for both previously known and recently learned words, as well as for mispronounced words or words preceded by a disfluency. Most of these studies employ one of three Tobii eye-trackers, while others that are just beginning use a novel head-mounted eye-tracker in combination with a LENA audio-recording and analysis system. Studies of adults employ an artificial lexicon paradigm and the visual world eye-tracking paradigm to carefully control variables such as word frequency and acoustic similarity (neighborhood structure).

In the past few years, my research has moved toward studies of brain function in adults and infants using fMRI and optical imaging, respectively. A new 3T magnet facility (http://www.rcbi.rochester.edu) has enabled us to measure activations in a targeted brain area, such as MT/MST, to novel words that have been linked during a lexical learning task to referents which have the property of motion. This allows us to determine if similar sounding words also activate MT/MST even if they do not have the referential property of motion, thereby serving as a measure of lexical competition. An optical imaging system (Hitachi ETG-4000) provides a 48-channel measure of hemodynamic activity in the superficial layers of cortex while infants are being presented with controlled stimulation. This system enables us to assess activations in various regions of the infant brain, thereby revealing the neural correlates of behavioral measures such as looking time. We are particularly interested in how these optical signals change over time as a way of understanding aspects of habituation and statistical learning.

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Selected Publications

 

2009-2010 PUBLICATIONS

STATISTICAL LEARNING (auditory)

STATISTICAL LEARNING (visual)

SPOKEN WORD RECOGNITION

INFANT SPEECH PERCEPTION

INFANT VISUAL PERCEPTION

INFANCY METHODS

PERCEPTUAL ADAPTATION

CHAPTERS AND COMMENTARIES

  • Aslin, R. N. (2008). Headed in the right direction: A commentary on Yoshida and Smith.  Infancy, 13,  275-278.
  • Aslin, R. N. (2006). Processes of change in brain and cognitive development: The final word. In M. Johnson & Y. Munakata (Eds.), Attention and Performance XXI: Processes of change in brain and cognitive development. Cambridge, MA: MIT Press.
  • Aslin, R. N. and Schlagger, B. L. (2006). Is myelination the precipitating neural event for language development in infants and toddlers?  Neurology, 66, 304-305.
  • Aslin, R.N., & Hunt, R.H. (2001). Development, plasticity, and learning in the auditory system. In C. A. Nelson & M. Luciana (Eds.), Handbook of Developmental Cognitive Neuroscience. Cambridge, MA: MIT Press, pp. 205-220.
  • Aslin, R.N. (2000). Why take the cog out of infant cognition? Infancy, 1, 463-470.
  • Aslin, R.N., Jusczyk, P.W., & Pisoni, D.B. (1998). Speech and auditory processing during infancy: Constraints on and precursors to language. In D. Kuhn & R. Siegler (Eds.), Handbook of Child Psychology, Fifth edition. Volume 2: Cognition, Perception and Language (W. Damon, series editor). New York: Wiley, pp. 147-198.

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Research Collaborators

  • Daphne Bavelier, Associate Professor, Department of Brain and Cognitive Sciences, University of Rochester
  • Andrew Berger, Assistant Professor, Institute of Optics, University of Rochester
  • József Fiser, Assistant Professor, Department of Psychology, Brandeis University
  • Robert A. Jacobs, Professor, Department of Brain & Cognitive Sciences, University of Rochester
  • David Knill, Professor, Department of Brain and Cognitive Sciences, University of Rochester
  • Elissa L. Newport, George Eastman Professor, Department of Brain and Cognitive Sciences, University of Rochester
  • Michael Tanenhaus, Professor, Department of Brain & Cognitive Sciences, University of Rochester

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Research Support

  • "Statistical approaches to linguistic pattern learning", NIH Grant (HD-37082), co-PI Elissa Newport, 2009-2014.
  • "Program grant to develop Near-infrared Spectroscopy in combination with ERPs and fMRI to assess cognitive development in human infants and young children," McDonnell Foundation (220020096), 2007-2010.
  • "Complex learning and skill transfer with video games", ONR-MURI grant, PI Daphne Bavelier, 2007-2010.
  • "Time course of spoken word recognition," NIH grant (DC-05071), PI Michael K. Tanenhaus, 2007-2012.

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Courses

Undergraduate

Graduate

  • BCS 561: Speech Perception and Recognition
  • BCS 562: Statistical Learning
  • BCS 565: Language and the Brain

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Current Graduate Students & Postdocs

Mohinish Shukla
Postdoc, Ph.D. 2006, SISSA, Trieste, Italy, statistical learning, phonological development, near-infrared spectroscopy
Neil Bardhan
Grad student, B.A. 2004, Johns Hopkins University, speech perception, phonological learning and lexical processing, eye-tracking
Sarah Davis
Grad student, B.A. 2005, Amherst College, probability learning in infants, neural correlates of stastistical learning, brain plasticity in hemispherectomy patients
Austin Frank
Grad student, B.A. 2004, Columbia University, speech production, phonological and lexical adaptation, computational models of language production
Celeste Kidd
Grad student, B.A. 2007, University of Southern California, speech perception and lexical development in infants, computational models of language processing
Jennifer Merickel
Grad student, B.A. 2008, University of Iowa, lexical and semantic constraints on word learning, speech perception, neural correlates of lexical learning and reorganization
Patricia Reeder
Grad student, B.A. 2004, Cornell University, category learning, artificial grammar learning, computational models of statistical learning

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Alumni

  • Meghan Clayards, Postdoctoral Fellow, McGill University
  • Jeffry Coady, Assistant Professor, Department of Communication Disorders, Boston University
  • Sarah Creel, Assistant Professor, Cognitive Science, University of California, San Diego
  • Andrea Rommel, Senior Research Administrator, RIT
  • Scott P. Johnson, Associate Professor, Department of Psychology, New York University
  • Jim Magnuson, Associate Professor, Department of Psychology, University of Connecticut
  • Jessica Maye, Assistant Professor, Department of Communication Sciences and Disorders, Northwestern University
  • Bob McMurray, Assistant Professor, Department of Psychology, University of Iowa
  • Toby Mintz, Associate Professor, Psychology & Linguistics, University of Southern California
  • Kate Pirog Revill, Postdoctoral Fellow, School of Psychology, Georgia Tech University
  • Vik Rao, Postdoctoral Fellow, University of Minnesota
  • Jenny Saffran, Professor, Department of Psychology, University of Wisconsin-Madison
  • Daniel Swingley, Assistant Professor, Department of Psychology, University of Pennsylvania
  • Daniel Weiss, Associate Professor, Department of Psychology & Linguistics, Pennsylvania State University
  • Katherine White, Assistant Professor, Department of Psychology, University of Waterloo
b) add Meghan Clayards (McGill) e) add Vik Rao (Univ of Minnesota)

Former Lab Managers

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© 2010, University of Rochester, The College, Brain & Cognitive Sciences
Last modified: 01/26/2010
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