Richard Aslin

Richard Aslin

Distinguished Research Scientist, Haskins Laboratory


Richard Aslin is a Distinguished Research Scientist at the Haskins Laboratories in New Haven CT.  Prior to joining Haskins in 2017 he was on the faculty at the University of Rochester for 33 years, where he established the Rochester BabyLab.  Aslin has published widely in several sub-areas of infant development, including perceptual and motor systems, language acquisition, and statistical learning.  His work on statistical learning with Jenny Saffran and Elissa Newport demonstrated the remarkable ability of infants to extract structure from rapid streams of speech by mere exposure.  Subsequent work with Jozsef Fiser expanded the scope of statistical learning to the visual domain.  And his work with Celeste Kidd and Steven Piantadosi documented that infants deploy their attention to auditory and visual sequences that have an intermediate (Goldilocks) level of complexity.

In the past decade, Aslin has focused on extending the statistical learning approach to grammatical category learning with Patricia Reeder and Elissa Newport, and on gathering neural measures of learning using fMRI, EEG, and fNIRS.  With Lizz Karuza he has explored the neural correlates of statistical learning in both visual and auditory domains using fMRI.  His fNIRS work with Lauren Emberson and Ben Zinszer has shown that the infant brain deploys predictive signals to encode expected events and that fNIRS has sufficient fidelity to “decode” stimulus conditions (e.g., word meanings) on a trial-by-trial basis.  With Elika Bergelson he has shown that infants’ earliest words are organized on the basis of semantic relatedness.

His interest in bilingualism has grown in the past few years as he deploys machine learning techniques to characterize the connectivity differences between bilingual and monolingual brains with Sara Sanchez-Alonso and Monica Rosenberg.  Aslin has been the recipient of several major awards, including the APA Distinguished Scientific Contributions Award (2014) and the APS Mentor Award for Lifetime Achievement (2015), and several honors, including election to the American Academy of Arts and Sciences (2006) and the National Academy of Sciences (2013).


  • Bergelson, E. & Aslin, R. N. (2018).  Semantic specificity in one-year-olds’ word comprehension.  Language Learning & Development. [doi: 10.1080/15475441.2017.1324308]
  • Piantadosi, S. T., Palmeri, H., & Aslin, R. N. (2018).  Limits on composition of conceptual operations in 9-month-olds.  Infancy, Early View [doi: 10.1111/infa.12225]
  • Aslin, R. N. (2017).  Statistical learning: A powerful mechanism that operates by mere exposure.  WIREs Cognitive Science, 8:e1373.  Special Issue on Development. [doi: 10.1002/wcs.1373]
  • Bergelson, E. & Aslin, R. N. (2017).  Nature and origins of the lexicon in 6-mo-olds. Proceedings of the National Academy of Sciences, 114, 12916-12921.
  • Emberson, L. L., Boldin, A., Riccio, J. E., Guillet, R., & Aslin, R. N. (2017).  Deficits in top-down, sensory prediction in infants at-risk due to premature birth.  Current Biology, 27, 431-436.
  • Emberson, L. L., Cannon, G., Palmeri, H., Richards, J. E., & Aslin, R. N. (2017).  Using fNIRS to examine occipital and temporal responses to stimulus repetition in young infants: Evidence of selective frontal cortex involvement.  Developmental Cognitive Neuroscience, 23, 26-38.
  • Emberson, L. L., Crosswhite, S. L., Richards, J. E., & Aslin, R. N. (2017).  The lateral occipital cortex (LOC) is selective for object shape, not texture/color, at 6 months.  Journal of Neuroscience, 37 (13), 3698-3703.
  • Emberson, L. L., Rizzieri, A., & Aslin, R. N. (2017).  How visual is visual prediction? Infancy, 22, 748-761.
  • Emberson, L. L., Zinszer, B. D., Raizada, R. D. S., & Aslin, R. N. (2017).  Decoding the Infant Mind: Multichannel Pattern Analysis (MCPA) using fNIRS.  PLoS ONE, April 20, 12(4):e0172500.
  • Karuza, E. A., Emberson, L. L., Roser, M. E., Cole, D., Fiser, J., & Aslin, R. N.  (2017). Neural signatures of spatial statistical learning: Characterizing the extraction of structure from complex visual scenes.  Journal of Cognitive Neuroscience, 29, 1963-1976.
  • Mulak, K. E., Cory D. Bonn, C. D., Chládková, K., Aslin, R. N., & Escudero, P. (2017).  Indexical and linguistic processing by 12-month-olds: Discrimination of speaker, accent and vowel differences.  PLoS ONE, 12(5): e0176762.
  • Reeder, P. A., Newport, E. L, & Aslin, R. N. (2017).  Distributional learning of subcategories in an artificial grammar: Category generalization and subcategory restrictions.  Journal of Memory and Language, 97, 17-29.
  • Schuler, K. D., Reeder, P. A., Newport, E. L., & Aslin, R. N. (2017). The effect of Zipfian frequency variations on category formation in adult artificial language learning.  Language Learning and Development, 13, 357-374.
  • Zinszer, B. D., Bayet, L., Emberson, L. L., Raizada, R. D. S., & Aslin, R.N. (2017).  Decoding semantic representations from fNIRS signals. Neurophotonics, 5(1), 011003.
  • Karuza, E. A., Li, P., Weiss, D. J., Bulgarelli, F., Zinszer, B., & Aslin, R. N.  (2016). Sampling over non-uniform distributions: A neural efficiency account of the primacy effect in statistical learning.  Journal of Cognitive Neuroscience, 28, 484-500.
  • Piantadosi, S. T. and Aslin, R. N. (2016).  Compositional reasoning in early childhood.  PLoS ONE 11(9): e0147734. [doi: 10.1371/journal.pone.0147734]
  • Aslin, R. N., Shukla, M., & Emberson, L. L. (2015).  Hemodynamic correlates of cognition in human infants.  Annual Review of Psychology, 66, 349–79.
  • Roser, M. E., Aslin, R. N., McKenzie, R., Zahra, D., & Fiser, J. (2015).  Enhanced visual statistical learning in adults with autism.  Neuropsychology, 29, 163-172.
  • Emberson, L. L., Richards, J. E., & 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. (2014).  Infant learning: Historical, conceptual, and methodological challenges. Infancy, 19, 2-27.
  • Kidd, C., Piantadosi, S. T. and Aslin, R. N. (2014).  The Goldilocks Effect in infant auditory attention. Child Development, 85, 1795–1804.
  • Piantadosi, S. T., Kidd, C., and Aslin, R. N. (2014).  Rich analysis and rational models: Inferring individual behavior from infant looking data.  Developmental Science, 17, 321-337.
  • Reeder, P. A., Newport, E. L, and Aslin, R. N. (2013).  From shared contexts to syntactic categories: The role of distributional information in learning linguistic form-classes. Cognitive Psychology, 66, 30-54.
  • Karuza, E. A., Newport, E. L., Aslin, R. N., Starling, S. J., Tivarus, M. E., and Bavelier, D.  (2013). The neural correlates of statistical learning in a word segmentation task: An fMRI study.  Brain and Language, 127, 46-54.
  • Aslin, R. N. and Newport, E. L. (2012). Statistical learning: From acquiring specific items to forming general rules.  Current Directions in Psychological Science, 21, 170-176.
  • Kidd, C., Piantadosi, S. T., and Aslin, R. N. (2012).  The Goldilocks effect: Human infants allocate attention to visual sequences that are neither too simple nor too complex.  PLoS ONE, 7(5): e36399. [doi:10.1371/journal.pone.0036399]
Richard Aslin