Richard Aslin, Ph.D.

Richard Aslin's picture
Senior Scientist, Haskins Laboratories
Haskins Laboratories



Richard Aslin joined Haskins Laboratories in 2017 as a senior scientist.  Along with David Lewkowicz, he has re-established the BabyLab to carry on the outstanding tradition of developmental research at Haskins, complementing the on-going studies of older infants and young children by other Haskins scientists.

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 two decades, 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 and EEG 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 table-top eye-trackers, while others use a head-camera or 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, EEG, and optical imaging (functional near-infrared spectroscopy, fNIRS). We have shown that activations in LIFG are correlated with statistical learning and that functional connectivity in a network of brain regions changes as new statistical patterns are available in the input.  We are also exploring whole-brain functional connectivity using Connectome-based Predictive Modeling to characterize individual differences and age-related changes.  EEG studies are directed to studies of spoken word-recognition using neural decoding techniques.  And fNIRS is being utilized to study infant and adult patterns of activation using whole-head coverage with both NirX and Shimadzu fNIRS systems.

Grant Support

NIH (HD-037081), “Statistical approaches to linguistic pattern learning,”  E. Newport, PI, R. Aslin, MPI (with subcontract from Georgetown University)

NIH Grant (DC-017596), “Decoding the neural time-course of spoken word recognition”, R. Aslin, PI, B. McMurray MPI (University of Iowa), 2018-2020
Gates Foundation (INV-005792), “Early predictors of neurodevelopmental outcomes (fNIRS)”,
 R. Aslin PI, 2020-2022

Students and Staff

Rebecca Canale, research associate (Haskins Laboratories)

Aditya Chander, PhD student (Yale Music)

Caleb Cohen, Senior Thesis student (Yale Psychology)

Claire Kabdebon, postdoctoral fellow (Haskins Laboratories)

Sara Sanchez-Alonso, postdoctoral fellow (Haskins Laboratories)

Lena Skalaban, PhD student (Yale Psychology)

Alice Wang, research associate (Haskins Laboratories)

Lab Alumni

Maria Arredondo, former postdoc, Assistant Professor, University of Texas at Austin

Alexis Black, former postdoc, Assistant Professor, University of British Columbia

Elizabeth Simmons, former UConn PhD student, Assistant Professor, Sacred Heart University 

Recent Publications

Bayet, L., Zinszer, B., Reilly, E., Cataldo, J., Cataldo, J. K. Pruitt, Z., Cichy, R. M., Nelson, C. A., & Aslin, R. N. (2020). Temporal dynamics of visual representations in the infant brain.  Developmental Cognitive Neuroscience, 45, 100860

Emberson, L. L., Boldin, A., Robertson, C., Cannon, G., & Aslin, R. N. (2019).  Expectation affects neural repetition suppression in infancy.  Developmental Cognitive Neuroscience, 37, 100597 []

Wu, R., Qian, T., & Aslin, R. N. (2019).  Extraction of abstract structure does not disrupt learning of novel events for 8- to 11-month-olds.  Frontiers in Psychology, 10, 498.

Bejjanki, V. R., Randrup, E. R., & Aslin, R. N. (2019).  Task complexity, not computational deficiency, prevents statistically deficient inference in young children.  Developmental Science, 23 (3) (

Bergelson, E. and Aslin, R. N. (2018).  Semantic specificity in one-year-olds’ word comprehension.  Language Learning & Development. [doi: 10.1080/15475441.2017.1324308]

Bankieris, K. R., Qian, T., & Aslin, R. N. (in press, 2018).  Synesthetes perseverate in implicit learning: Evidence from a non-stationary statistical learning task.  Quarterly Journal of Experimental Psychology. [DOI: 10.1177/1747021818816285]

Piantadosi, S.T., Palmeri, H. & Aslin, R. N. (2018). Limits on composition of conceptual operations in 9-month-olds. Infancy, 23, 310-324. DOI: 10.1111/infa.12225.

Wu, R. McGee, B. Rubenstein, M. Pruitt, Z. Cheung, O.S., & Aslin, R. N. (2018).  Emergence of the costs and benefits of grouping for visual search. Psychophysiology, 55:el3087. DOI: 10.1111/psyp.13087.

Starling, S. J. Reeder, P. R., & Aslin, R. N. (2018). Probability learning in an uncertain world: How children adjust to changing contingencies. Cognitive Development, 48, 105-116.

Bayet, L. Zinzser, B.D., Pruitt, Z., Aslin, R.N. & Wu, R.  (2018). Dynamics of neural representations when searching for exemplars and categories of human and non-human faces. Scientific Reports, 8:13277. DOI: 10.1038/s41598-018-31526-y.

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. 

Bankieris, K. R. & Aslin, R. N. (2017).  Implicit associative learning in synesthetes and non-synesthetes.  Psychonomic Bulletin & Review, 24, 935-943. 

Bankieris, K. R., Bejjanki, V. R., & Aslin, R. N.  (2017).  Cue integration for continuous and categorical dimensions by synesthetes.  Multisensory Research, 30, 207-234.

Bankieris, K. R., Bejjanki, V. R., & Aslin, R. N. (2017).  Sensory cue-combination in the context of newly learned categories.  Scientific Reports, 7,10890. 

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.

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. (1846)

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

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. 

Bergelson, E. and Aslin, R. N. (Published online 6/30/2017).  Semantic specificity in one-year-olds’ word comprehension.  Language Learning & Development.  DOI:10.1080/15475441.2017.1324308

Emberson, L. L., Zinszer, B. D., Raizada, R. D. S., and Aslin, R. N. (2017).  Decoding the Infant Mind: Multichannel Pattern Analysis (MCPA) using fNIRS.  PLoS ONE, April 20, 12(4):e0172500. 

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., Richard, 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. 

Karuza, E. A., Li, P., Weiss, D. J., Bulgarelli, F., Zinszer, B., and 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.

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. 

Aslin, R. N. (2014).  Phonetic category learning and its influence on speech production.  Ecological Psychology, 26, 4-15. 

Aslin, R. N. and Newport, E. L. (2014).  Distributional language learning: Mechanisms and models of category formation.  Language Learning, 64: Cognitive Neuroscience Supplement 2, 86–105.  

Kidd, C., Piantadosi, S. T. and Aslin, R. N. (2014).  The Goldilocks Effect in infant auditory attention.  Child Development, 85, 1795–1804 

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.

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.

Aslin, R. N. (2012).  Questioning the questions that have been asked about the infant brain using NIRS.  Cognitive Neuropsychology, 29, 7-33.

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. 

Bejjanki, V. R., Clayards, M., Knill, D. C. and Aslin, R. N. (2011).  Cue integration in categorical tasks: Insights from audio-visual speech perception.  PLoS One, 6, e19812. 

Shukla, M., White, K. S., and Aslin, R. N. (2011).  Prosody guides the rapid mapping of auditory word forms onto visual objects in 6-mo-old infants.  Proceedings of the National Academy of Sciences, 108, 6038-6043.

White, K. S. and Aslin, R. N. (2011).  Adaptation to novel accents in toddlers.  Developmental Science, 14, 372-384.