Christopher Conway
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641-269-9525
Curriculum Vitae
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Christopher Conway

Associate Professor
Offices, Departments, or Centers: Psychology ,

I study the neurocognitive mechanisms of learning and memory, specifically a form of implicit learning referred to as “statistical learning”, and how such mechanisms are used in the service of language development across diverse experiences. My work relies on a combination of cognitive and cognitive neuroscience methodology, with a variety of different participant populations (human adults and children with or without deafness or hearing loss, dyslexia, autism spectrum disorder, and ADHD, as well as non-human primates). 

 

Education and Degrees

Associate Professor in Psychology 

B.S.E Duke University

M.A Southern Illinois University

Ph.D (2005) Cornell University

Selected Publications

Milne, A.E., Chait, M., & Conway, C.M. (2025). Probing sensitivity to statistical structure in rapid sound sequences using deviant detection tasks. Journal of Experimental Psychology: Learning, Memory, & Cognition. Advance online publication. https://dx.doi.org/10.1037/xlm0001492

Li, X., Conway, C.M., Yin, S., Zhaou, X., Bai, X., & Shi, W. (2025). Learning in the face of failure: The benefit of autistic traits. British Journal of Psychology, 1-13. DOI: 10.1111/bjop.12786

Ren, J., Wang, M., & Conway, C.M. (2024). Can explicit instruction boost statistical learning? A meta-analytical review. Journal of Educational Psychology. 116(7), 1215–1237. https://doi.org/10.1037/edu0000897

Emerson, S.N. & Conway, C.M. (2023). Chunking versus transitional probabilities: Differentiating between theories of statistical learning. Cognitive Science, 47(5), e13284. https://doi.org/10.1111/cogs.13284. NIHMSID1885866

Li, X., Bai, X., Conway, C.M., Shi, W., & Wang, X. (2022). Statistical learning for non-social and socially-meaningful stimuli in individuals with high and low levels of autistic traits. Current Psychology. https://doi.org/10.1007/s12144-022-02703-0

Singh, S. & Conway, C.M. (2021). Unraveling the interconnections between statistical learning and dyslexia: A review of recent empirical studies. Frontiers in Human Neuroscience, 15: 734179. doi: 10.3389/fnhum.2021.734179

Englund, M., Whitham, W., Conway, C.M., Beran, M., & Washburn, D. (2021). Nonhuman primates learn adjacent dependencies but fail to learn nonadjacent dependencies in a statistical learning signal detection task. Learning and Behavior. https://doi.org/10.3758/s13420-021-00485-2

Terhune-Cotter, B.P., Conway, C.M., & Dye, M.W.G. (2021). Visual sequence repetition learning is not impaired in signing DHH children. Journal of Deaf Studies and Deaf Education. enab007, https://doi.org/10.1093/deafed/enab007

Eghbalzad, L., Deocampo, J.A., & Conway, C.M. (2021). How statistical learning interacts with the socioeconomic environment to shape children’s language development. PLOS One, 16(1), e0244954. https://doi.org/10.1371/journal.pone.0244954

Conway, C.M. (2020). How does the brain learn environmental structure? Ten core principles for understanding the neurocognitive mechanisms of statistical learning. Neuroscience and Biobehavioral Reviews, 112, 279-299. 10.1016/j.neubiorev.2020.01.032

Conway, C.M., Eghbalzad, L., Deocampo, J.A., Smith, G.N.L., Na, S., &. King, T. (2020). Distinct neural networks active for detecting violations of adjacent versus nonadjacent sequential dependencies: An fMRI study. Neurobiology of Learning and Memory, 169. 10.1016/j.nlm.2020.107175

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