University of Rochester

Richard N. Aslin


Emberson, L. L., Richards, J. E., and Aslin, R. N. (2015). Top-down modulation in the infant brain: Learning-induced expectations rapidly affect the sensory cortex at 6 months.Proceedings of the National Academy of Sciences, 112, 9585-9590.


Aslin, R. N., Shukla, M, & Emberson, L. L. (2015).  Hemodynamic correlates of cognition in human infants.  Annual Review of Psychology, 66, 349–79.


Aslin, R. N. (2014). Infant learning: Historical, conceptual, and methodological challenges. Infancy, 19, 2-27.

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 ( 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.

Selected Publications

In Press



















Research Collaborators

Daphne Bavelier, Professor, Psychology Department, University of Geneva
Elika Bergelson, Research Assistant Professor, Brain and Cognitive Sciences, University of Rochester
Andrew Berger, Associate Professor, Institute of Optics, University of Rochester
Lauren Emberson, Assistant Professor of Psychology, Princeton University
József Fiser, Associate Professor, Cognitive Science Department, Central European University
T. Florian Jaeger, Associate Professor of Brain and Cognitive Sciences and Computer Science, University of Rochester
Elisabeth Karuza, Postdoctoral Fellow, Department of Psychology, University of Pennsylvania
Celeste Kidd, Assistant Professor of Brain and Cognitive Sciences and Center for Visual Science, University of Rochester
Ping Li, Professor of Psychology, Penn State University
Charles Nelson, Professor of Pediatrics, Children's Hospital Boston, Harvard Medical School
Elissa L. Newport, Professor, Neurology Department, Georgetown University
Steven Piantadosi, Assistant Professor of Brain and Cognitive Sciences, University of Rochester
Ting Qian, Research Data Scientist, Children’s Hospital of Philadelphia Research Institute
Raj Raizaida, Assistant Professor of Brain and Cognitive Sciences, University of Rochester
Vik Rao Bejjanki, Postdoctoral Fellow, Department of Psychology, Princeton University
Patricia Reeder, Assistant Professor, Department of Psychology, Gustavus Adolphus College
Matthew Roser, Lecturer, Psychology Department, Plymouth University
Gaia Scerif, Professor of Experimental Psychology, University of Oxford (UK)
Michael Tanenhaus, Professor, Department of Brain & Cognitive Sciences, University of Rochester
Daniel Weiss, Associate Professor of Psychology, Penn State University
Rachel Wu, Assistant Professor of Psychology, UC-Riverside

Research Support

"Statistical learning of multiple patterns in infants, adults, and monkeys", NIH grant (HD-067250), PI Daniel Weiss, co-PI Richard Aslin, 2011-2016.
"Time course of spoken word recognition," NIH grant (HD-073890), PI Michael K. Tanenhaus, 2012-2016.
“Developmental mechanisms of perception and language in the infant brain”, NSF EAGER grant (BCS-1514351), R. Aslin PI, C. Nelson co-PI, 2015-2017.
“Laboratory for Interactional Dynamics: Using Real-Time Avatars to Manipulate Social Cues”, University of Rochester Research Award, M. Sturge-Apple PI, R. Aslin and W. Heinzelman, co-PIs, 2015-2016.
"Probabilistic computation in the cortex of the developing human brain", NIH grant (HD-088731), R. Aslin PI, J. Fiser co-PI, pending Council approval, 2016-2018.



BCS 172: Development of Mind and Brain, syllabus

BCS 205: Lab in Development


BCS 599: Professional Development and Career Planning

Current Graduate Students & Postdocs

Katie Bankieris, Grad student, B.S. 2010, Emory University, M.A. 2011 University of Edinbrough, sensory integration and synesthesia

Laurie Bayet, Postdoc (joint with Chuck Nelson), Ph.D. 2015, University of Grenoble (France), face perception and early learning in infancy, EEG and fNIRS measures of visual and auditory perception in infants

Keturah Bixby, Graduate student, B.S. 2007, University of Illinois, interactions between perception and motor control, learning, music cognition

Ben Zinszer, Postdoc (joint with Raj Razaida), Ph.D. 2014, Penn State University, semantic representation in the human brain using fMRI in adults and fNIRS in infants, neural correlates of bilingualism


Vik Rao Bejjanki, Assistant Professor of Psychology, Hamilton College

Cory Bonn, Postdoctoral Fellow, University Paris Descartes

Meghan Clayards, Assistant Professor, Departments of Linguistics and Communication Sciences, McGill University

Jeff Coady, Associate Professor, Speech, Language & Hearing Sciences, University of Colorado-Boulder

Sarah Creel, Assistant Professor, Cognitive Science, University of California, San Diego

Lauren Emberson, Assistant Professor of Psychology, Princeton University

Scott P. Johnson, Professor, Developmental Psychology, UCLA

Jim Magnuson, Associate Professor, Department of Psychology, University of Connecticut

Jessica Maye, Adjunct Professor, Department of Communication Sciences and Disorders, Northwestern University

Bob McMurray, Associate Professor, Department of Psychology, University of Iowa

Jennifer Merickel, Postdoctoral Fellow in Neurology, University of Nebraska Medical Center

Toby Mintz, Associate Professor, Psychology & Linguistics, University of Southern California

Kate Pirog Revill, Research Assistant Professor, MRI Center, Emory University

Andrea Rommel, Senior Research Administrator, RIT

Jenny Saffran, Professor, Department of Psychology, University of Wisconsin-Madison

Mohinish Shukla, Assistant Professor, Department of Psychology, University of Massachusetts-Boston

Daniel Swingley, Associate 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

Rachel Wu, Assistant Professor of Psychology, UC-Riverside

Former Lab Managers

Suzanne Horwitz, Graduate student, Department of Psychology, Yale University

Julie Markant, Assistant Professor of Psychology, Tulane University

Koleen McCrink, Assistant Professor, Department of Psychology, Barnard College

Alyssa Thatcher, Department of Psychiatry, University of Rochester

Rachel White, Assistant Professor of Psychology, Hamilton College