Cory D. Bonn


DSI Post-Doctoral Research Fellow
Centre for Cognitive Development
UBC Data Science Institute
Department of Psychology
University of British Columbia
Github | Twitter | CV


I'm broadly interested in how humans represent environmental statistics and causal structures and in finding ways to better analyze data. Specific interests include numerical cognition (current work), generalized magnitude representations (dissertation), and speech-category acquisition. I'm also interested in development of novel infant methods.

NEWS

2019

Oct. 1, 2019. Paper on newborns's association of brightness with number/duration out in PLOS ONE.

May 19, 2019. Gave talk at VSS on adaptation of number judgments with low-level features.

May 1, 2019. Began project funded by the UBC Data Science Institute, entitled "Quantifying individual differences from complex datasets in developmental psychology."

2018

April 8-9. Talk given on cross-dimensional ratio and rank processing at the 1st Mathematical Cognition and Learning Society Conference in Oxford, UK.

Jan. 1. Started post-doc at UBC Psychology.

2017

May 4-7. Poster entitled "Dot-size variance reduces biases in numerical discrimination and estimation tasks" at CAOS 2017 in Rovereto, IT.

2016

Sept. 28-30. Presented poster entitled "Sources of uncertainty in the approximate number system" at the Domain-General and Domain-Specific Foundations of Numerical and Arithmetic Processing Workshop in Tübingen, Germany.

Feb. 16. NEW WEBSITE!

Jan. 1. Started post-doc at LPP studying factors that affect noise levels in the infant and adult approximate number system.

2015

Dec. 10. Successfully defended PhD thesis entitled On Theories of Abstract, Quantitative Representation.

Sept. 1. Started NSF-GROW/STEM-Chateaubriand predoctoral fellowships in Paris at Laboratoire Psychologie de la Perception, Université Paris Descartes.

Aug. 10. Moved out of Rochester, NY.

July 1. Awarded Fyssen Foundation Postdoctoral Study Fellowship.

June 1. Awarded NSF-GROW Fellowship.

May 2. Awarded Embassy of France's STEM-Chateaubriand Fellowship.

BIOGRAPHY

I am currently a post-doc at the Centre for Cognitive Development, University of British Columbia, working with Darko Odic in the Early Development Group. As I am funded by UBC's Data Science Institute, I am concurrently working on models for solving problems associated with missingness in developmental data as well as projects on numerical cognition in the Odic lab. I did my PhD at the Department of Brain and Cognitive Sciences at the University of Rochester, working with Dick Aslin and Jessica Cantlon and previously did a post-doc in Paris with Véronique Izard and Lola de Hevia. In a former life, I was a pianist, but these days I find myself broadly interested in how humans learn about the causal and statistical structure of the world. Most recently, that has expanded to include numerical cognition, but I've worked on diverse problems related to generalized magnitude representation and distributional learning of phonemes. Before working on statistical learning, I was interested in music and auditory perception. I have an interest in methods development, particularly for use with infants, whether it be for creating new eye-tracking paradigms or extending the analytical toolbox of infant researchers.

PAPERS

Approximate Number System

Bonn, C.D., & Odic, D. (In prep). Adaptation to non-numeric features reveals mechanisms of number perception.

Bonn, C.D., & Izard, V. (In prep). Dot-size variance reduces biases in numerical discrimination and estimation tasks.

Abstract Quantity

Bonn, C.D., Netskou, M-E., Streri, A., & de Hevia, M.D. (2019). The association of brightness with number/duration in human newborns. PLOS ONE, 14(10), e0223192. https://doi.org/10.1371/journal.pone.0223192

Bonn, C.D., & Cantlon, J.F. (2017). Spontaneous, modality-general abstraction of a ratio scale. Cognition, 169, 36-45. https://doi.org/10.1016/j.cognition.2017.07.012

Bonn, C.D., & Cantlon, J.F. (Under revision). Learning relations between space, time, and number from environmental statistics.

Bonn, C.D., & Cantlon, J.F. (2012). The origins and structure of quantitative concepts. Cognitive Neuropsychology, 29:1-2, pp. 149-173.

Speech Perception and Categorization

Mulak, K., Bonn, C.D., Chládkova, 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.

Stasenko, A., Bonn, C., Teghipco, A., Garcea, F.E., Sweet, C., Dombovy, M., McDonough, J., and Mahon, B.Z. (2015). A causal test of the motor theory of speech perception: a case of impaired speech production and spared speech perception. Cognitive Neuropsychology, 32, 38-57.

Infant Methods

Bonn, C.D., & Aslin, R.N. (In prep). Probability matching in human infants: A demonstration using a novel forced-choice paradigm.

Pitch and Music Perception

Siu, J., Bonn, C.D., & Marvin, E.W. (Under Revision). Contributions of native language, spectral envelope, and absolute pitch possession to the perception of octave-ambiguous tritones in tone-language speakers.

CURRENT PROJECTS

DEVELOPMENT OF NUMERICAL COGNITION

At the LPP, Véronique Izard and I are working on a project in infants and adults that aims to decompose noise sources that contribute to uncertainty in the approximate number system and how those differ across individuals and across different developmental stages.

PAST PROJECTS

GENERALIZED MAGNITUDE REPRESENTATIONS

Keep your eyes open for my dissertation work, which explored the hypothesis space of generalized magnitude representations. We approached the topic from multiple perspectives, including statistical learning as well as analogical reasoning.

INFANT METHODS

Dick Aslin and I worked toward developing novel, forced-choice eye-tracking paradigms for use with infants. To be continued. . .

SPEECH CATEGORIZATION

I'm interested in how infants learn their native speech categories (phonemes) in an unsupervised fashion. To do this, infants need to solve some complex statistical learning and causal inference problems.

CURRENT COLLABORATORS

Cristina Conati
Lang Wu
Dick Aslin
Jessica Cantlon
Véronique Izard
Lola de Hevia

FUNDING

UBC Data Science Institute Postdoctoral Matching Fund.
NSERC Discovery Grant to Darko Odic and UBC Department of Psychology (2018-present)
Fondation Fyssen Postdoctoral Study Grant (2016 - 2017)
Embassy of France STEM-Chateaubriand Fellowship (Fall 2015)
National Science Foundation Graduate Research Opportunities Worldwide (GROW) Fellowship (Fall 2015)
National Science Foundation Graduate Research Fellowship (2011 - 2014)