Blair C. Armstrong Assistant Professor Department of Psychology & Department of Language Studies University of Toronto Scarborough (UTSC) Cross-appointment: Department of Computer Science, University of Toronto Affiliated Researcher Basque Center on Cognition, Brain, and Language (BCBL) Contact (e-mail preferred): E-mail: blair.armstrong@utoronto.ca Telephone: (1)-416-287-7146 Mailing Address: University of Toronto Scarborough Department of Psychology 1265 Military Trail Toronto, Ontario, Canada M1C 1A4 |
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Research
Interests
- Education - Publications -
Published Software -
Other Tools -
Teaching - Advising - Service - In the News
Teaching - Advising - Service - In the News
Research InterestsMy primary
research interests relate to the cognitive and neural representations,
processes, and learning mechanisms underlying word comprehension and
semantic memory. This work largely concerns developing
theories of how ambiguous words are comprehended, the source of the
similarities and differences between written and spoken word
comprehension, how learning mechanisms lead to the emergence of
cross-linguistic differences in lexical processing, and how
newly-learned words are integrated into the lexical system.
Complementing this work, I pursue research into how decision and
response systems engage the word comprehension and perceptual systems
in different tasks. My work focuses on developing explicit
mechanistic accounts of these cognitive systems. This work is
informed by tightly coordinated computational modeling using
biologically-plausible connectionist networks and by empirical
investigations using a range of behavioral and electrophysiological
techniques. I am also interested in how computational
algorithms can improve experimental methodologies such as stimulus
selection, speech onset detection, and data analysis.
CV Highlights |
Education |
2012 | PhD,
Psychology, Psychology Department, Carnegie Mellon
University Dissertation: The Temporal Dynamics of Word Comprehension and Response Selection: Computational and Behavioral Studies Advisor: Dr. David Plaut Committee: Dr. Marlene Behrmann, Dr. Brian MacWhinney, Dr. Natasha Tokowicz |
2012 | Graduate
Training Certificate, Center for the Neural Basis of
Cognition (CNBC), Carnegie Mellon University |
2010 | MS,
Psychology, Psychology Department, Carnegie Mellon
University Advisor: Dr. David Plaut Committee: Dr. Marlene Behrmann, Dr. Brian MacWhinney |
2007 | MA,
Psychology, Department of Psychology, University of Toronto Dissertation: Comprehending Ambiguous Words: Computational and Empirical Investigations Advisor: Dr. David Plaut Co-advisor: Dr. Steve Joordens |
2006 | HBSc,
Conferred with High Distinction, Psychology Specialist Program, University
of Toronto Scarborough Psychology Honours Thesis: Title: Accounting for Category-specific Semantic Deficits: A Computational Implementation of Conceptual Topography Theory Advisor: Dr. George Cree Neuroscience Honours Thesis: Title: The Golden Ratio: A Search for the Mathematical and Neural Basis of Beauty Advisors: Dr. Gerald Cupchik and Dr. Ted Petit |
PublicationsPeer-reviewed Articles: Li, J. & Armstrong, B.C. (2024). Probing the Representational Structure of Regular Polysemy via Sense Analogy Questions: Insights from Contextual Word Vectors. Cognitive Science, 48: e13416. https://doi.org/10.1111/cogs.13416 Lopez Zunini, R., Baart, M., Samuel, A. G., & Armstrong, B. C. (2022). Lexico-semantic access and audiovisual integration in the aging brain: Insights from mixed-effects regresion analyses of event-related potentials. Neuropsychologia. https://doi.org/10.1016/j.neuropsychologia.2021.108107 Beekhuizen, B., Armstrong, B. C., & Stevenson, S. (2021). Probing lexical ambiguity: Word vectors encode number and relatedness of senses. Cognitive Science, 45(5), e12943. https://doi.org/10.1111/cogs.12943 Lopez Zunini, R., Baart, M., Samuel, A. G., & Armstrong, B. C. (2020). Lexical access versus lexical decision processes for auditory, visual, and audiovisual items: Insights from behavioral and neural measures. Neuropsychologia. https://doi.org/10.1016/j.neuropsychologia.2019.107305 Frost, R., Armstrong, B. C., & Christiansen, M. H. (2019). Statistical learning research: A critical review and possible new directions. Psychological Bulletin, 145(12), 1128–1153. https://doi.org/10.1037/bul0000210 Ling, S., Lee, A. C. H., Armstrong, B. C., & Nestor, A. (2019). How are visual words represented? Insights from EEG-based visual word decoding, feature derivation and image reconstruction. Human Brain Mapping. https://doi.org/10.1002/hbm.24757 Siegelman, N., Bogaerts, L., Armstrong, B. C., & Frost, R. (2019). What exactly is learned in visual statistical learning? Insights from Bayesian modeling. Cognition. https://doi.org/10.1016/j.cognition.2019.06.014 Rice, C. A., Beekhuizen, B., Dubrovsky, V., Stevenson, S., & Armstrong, B. C. (2018). A comparison of homonym meaning frequency estimates derived from movie and television subtitles, free association, and explicit ratings. Behavior Research Methods. https://doi.org/10.3758/s13428-018-1107-7 Baart, M., Armstrong, B. C., Martin, C., Frost, R., & Carreiras, M. (2017). Cross-modal noise compensation in audiovisual words. Scientific Reports, 7(42055), http://dx.doi.org/10.1038/srep42055. Armstrong, B. C., Dumay, N., Kim, W., & Pitt, M. A. (2017). Generalization from newly learned words reveals structural properties of the human reading system. Journal of Experimental Psychology: General, 146(2), 227-249. http://dx.doi.org/10.1037/xge0000257 Roux, F.*, Armstrong, B. C.*, & Carreiras, M. (2016). Chronset: An automated tool for detecting speech onset. Behavior Research Methods. http://dx.doi.org/10.3758/s13428-016-0830-1 * = equal contribution. Armstrong, B. C., Frost, R., & Christiansen, M. H. (2017). The Long Road of Statistical Learning Research: Past, Present, and Future. Special issue on New Frontiers for Statistical Learning in the Cognitive Sciences [B. C. Armstrong, R. Frost, & M. H. Christiansen, Eds.], Philosophical Transactions of the Royal Society of London: Biological Sciences, 372(1711). http://dx.doi.org/10.1098/rstb.2016.0047 Armstrong, B. C., & Plaut, D. C. (2016). Disparate semantic ambiguity effects from semantic processing dynamics rather than qualitative task differences. Language, Cognition, and Neuroscience, 1(7), 1-27. http://dx.doi.org/10.1080/23273798.2016.1171366 Armstrong, B. C., Zugarramurdi, C., Alvaro, C., Valle Lisboa, J., & Plaut, D. C. (2015). Relative meaning frequencies for 578 homonyms in two Spanish dialects: A cross-linguistic extension of the English eDom norms. Behavior Research Methods, 48(3), 950-962. http://dx.doi.org/10.3758/s13428-015-0639-3 Armstrong, B. C., Ruiz-Blondet, M., Khalifian, N., Jin, Zanpeng, J., Kurtz, K. J., Laszlo, S. (2015). Brainprint: Assessing the uniqueness, collectability, and permanence of a novel method for ERP biometrics. Neurocomputing, 166, 59-66. http://dx.doi.org/10.1016/j.neucom.2015.04.025 **Subsequently selected for inclusion in the 2015 Virtual Special Issue Celebrating the Breadth of Biometrics Research 2015, which highlights select articles published across a number of Elsevier journals. ** Frost, R., Armstrong, B. C., Seigelman, N., Christiansen, M. H. (2015). Domain generality versus modality specificity: The paradox of statistical learning. Trends in Cognitive Sciences, 19(3), 117-125. http://dx.doi.org/10.1016/j.tics.2014.12.010. Invited peer-reviewed contribution. Lerner, I., Armstrong, B. C., & Frost, R. (2014). What can we learn from learning models about sensitivity to letter-order in visual word recognition? Journal of Memory and Language, 77, 40-58. http://dx.doi.org/10.1016/j.jml.2014.09.002 Laszlo, S., & Armstrong, B. C. (2014). Applying the dynamics of post-synaptic potentials to individual units in simulation of temporally extended ERP reading data. Brain & Language, 132, 22-27. http://dx.doi.org/10.1016/j.bandl.2014.03.002 Carreiras, M., Armstrong, B. C., Perea, M., & Frost, R. (2014). The What, When, Where, and How of Visual Word Recognition. Trends in Cognitive Sciences, 18(2), 90-98. http://dx.doi.org/10.1016/j.tics.2013.11.005 Invited peer-reviewed contribution. ** The article received the 2014 Best Neuroscience Publication Award from the Spanish Society of Experimental Psychology (SEPEX) ** Armstrong, B.C., Tokowicz, N., & Plaut, D.C. (2012). eDom: Norming software and relative meaning frequency norms for 544 homonyms. Behavioral Research Methods, 44(4), 1015-1027. http://dx.doi.org/10.3758/s13428-012-0199-8 Armstrong, B.C., Watson, C.E., & Plaut, D.C. (2012). SOS! An algorithm and software for the Stochastic Optimization of Stimuli. Behavior Research Methods, 44(3), 675-705. http://dx.doi.org/10.3758/s13428-011-0182-9 Armstrong, B.C., LeBoutillier, J.C., & Petit, T.L. (2012). Ultrastructural synaptic changes associated with Neurofibromatosis Type 1: Quantitative analysis of hippocampal region CA1 in a Nf1+/- mouse model. Synapse, 66(3), 246-255. http://dx.doi.org/10.1002/syn.21507 Connor, S., Williams P. T., Armstrong, B., Petit, T. L., Ivanco, T. L., Weeks, A. C. (2006). Long-term potentiation is associated with changes in synaptic ultrastructure in the rat neocortex. Synapse, 59(6), 378-382. http://dx.doi.org/10.1002/syn.20248 Peer-reviewed Conference Papers (* = presenter; _____ = trainee): Li, J.*, & Armstrong, B. C. (2024). Issues of Generalization from Unreliable or Unrepresentative Psycholinguistic Stimuli: A Case Study on Lexical Ambiguity. Proceedings of the Annual Meeting of the Cognitive Science Society. Li, J.*, & Armstrong, B. C. (2023). Probing the Representational Structure of Regular Polysemy in a Contextual Word Embedding Model via Sense Analogy Questions. Proceedings of the Annual Meeting of the Cognitive Science Society. Li, J., & Armstrong, B. C. (2023). Probing the Representational Structure of Regular Polysemy in a Contextual Word Embedding Model via Sense Analogy Questions. Proceedings of the Annual Meeting of the Cognitive Science Society. McCann, R., Armstrong, B. C., Reynolds, M., & Besner, D. (2022). New analyses of lexical influences on the processing of pseudo-homophones in the lexical decision task: Still more challenges for models of visual word recognition. Proceedings of the 44th Annual Meeting of the Cognitive Science Society. Miller, I. D., Dumay, N. Pitt, M., Lam, B., & Armstrong, B. C. (2020). Context variability promotes generalization in reading aloud: Insight from a neural network simulation. Proceedings of the 42nd Annual Meeting of the Cognitive Science Society. Alhama, R. G.*, Siegelman, N., Frost, R., & Armstrong, B. C. (2019). The role of information in visual word recognition: A perceptually-constrained connectionist account. Proceedings of the 41st Annual Conference of the cognitive Science Society. Mahwah, NH: Lawrence Erlbaum Associates. Mo, D. & Armstrong, B. C. (2019). Statistical learning of conjunctive probabilities. Proceedings of the 41st Annual Conference of the Cognitive Science Society. Mahwah, NH: Lawrence Erlbaum Associates. Beekhuizen, B.*, Milic, S., Armstrong, B. C., & Stevenson, S. (2018). What Company Do Semantically Ambiguous Words Keep? Insights from Distributional Word Vectors. Proceedings of the 40th Annual Conference of the Cognitive Science Society. Mahwah, NH: Lawrence Erlbaum Associates. Medeiros, J.*, & Armstrong, B. C.* (2017). Semantic ambiguity effects: A matter of time? Proceedings of the 39th Annual Conference of the Cognitive Science Society. Mahwah, NH: Lawrence Erlbaum Associates. Ruiz-Blondet, M.*, Khalifian, N., Armstrong, B. C., Jin, Zanpeng, J., Kurtz, K. J., Laszlo, S. (2014). Brainprint: Identifying unique features of neural activity with machine learning. Proceedings of the 36th Annual Conference of the Cognitive Science Society (pp. 827-832). Mahwah, NH: Lawrence Erlbaum Associates. Armstrong, B. C.*, & Plaut, D. C. (2013). Simulating overall and trial-by-trial effects in response selection with a biologically-plausible connectionist network. In M. Knauff, M. Pauen, N. Sebanz, & I. Wachsmuth (Eds.), Proceedings of the 35th Annual Conference of the Cognitive Science Society (pp. 139-144). Austin, TX: Cognitive Science Society. Laszlo, S., & Armstrong, B. C.* (2013). Applying the dynamics of post-synaptic potentials to individual units in simulation of temporally extended ERP reading data. In M. Knauff, M. Pauen, N. Sebanz, & I. Wachsmuth (Eds.), Proceedings of the 35th Annual Conference of the Cognitive Science Society (pp. 2826-2831). Austin, TX: Cognitive Science Society. Armstrong, B. C.* & Plaut, D. C. (2011). Inducing homonymy effects via stimulus quality and (not) nonword difficulty: Implications for models of semantic ambiguity and word recognition. In L. Carlson, C. Holscher, & T. Shipley (Eds.), Proceedings of the 33rd Annual Conference of the Cognitive Science Society (pp. 2223-2228). Austin, TX: Cognitive Science Society. Armstrong, B. C.*, Joordens, S., & Plaut, D. C. (2009). Yoked criteria shifts in decision system adaptation: Computational and behavioral investigations. In N.A. Taatgen & H. van Rijn (Eds.), Proceedings of the 31st Annual Conference of the Cognitive Science Society (pp. 2130-2135). Austin, TX: Cognitive Science Society. MacInnes, W. J.*, Armstrong, B. C., Pare, D., Cree, G. S., & Joordens, S. (2009). Everyone’s a critic: Memory models and uses for an artificial Turing judge. In B. Goertzel, M. Hutter, & P. Hitzler (Eds.) Proceedings of the Second Conference on Artificial General Intelligence (pp. 132-137). Paris, France: Atlantic Press. ** Second runner up for Kurzweil Best Artificial General Intelligence Paper at AGI 2009 ** Armstrong, B. C.*, & Plaut, D. C. (2008). Settling dynamics in distributed networks explain task differences in semantic ambiguity effects: Computational and behavioral evidence. In B. C. Love, K. McRae, & V. M. Sloutsky (Eds.) Proceedings of the 30th Annual Meeting of the Cognitive Science Society (pp. 273-278). Austin, TX: Cognitive Science Society. Book Chapters: Carreiras, M., Armstrong, B. C., & Dunabeitia, J. A. (2018). Reading. Invited chapter to appear in The Stevens' Handbook of Experimental Psychology and Cognitive Neuroscience, Fourth Edition [J. Wixted, Ed.]. Cree, G. S., & Armstrong, B. (2012). Computational models of semantic memory. In Spivey, M., McRae, K. & Joanisse, M. (Eds.), Cambridge Handbook of Psycholinguistics (pp. 259-282). New York: Cambridge University Press. Watson, C. E., Armstrong, B. C., & Plaut, D. C. (2012). Connectionist modeling of neuropsychological deficits in semantics, language, and reading. In M. Faust (Ed.), The Handbook of the Neuropsychology of Language (pp. 103-124). New York: Wiley-Blackwell. Peer-reviewed Articles in Undergraduate Journals Das, B., Meltzer, J. A., & Armstrong, B. C. (2021). Quantitative Assessment of Handedness and Cerebral Lateralization. Journal of Natural Sciences, 2(1). https://doi.org/10.33137/jns.v2i1.34660 Doctoral Dissertation: Armstrong, B. C. (2012). The Temporal Dynamics of Word Comprehension and Response Selection: Computational and Behavioral Studies. Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy, Psychology Department, Carnegie Mellon University. Conference Proceedings: S. Denison., M. Mack, Y. Xu, & B.C. Armstrong (Eds.), Proceedings of the 42nd Annual Conference of the Cognitive Science Society (2020). Cognitive Science Society. Special Issues: Guest Editor for a theme issue on New Frontiers for Statistical Learning in the Cognitive Sciences [B. C. Armstrong, R. Frost, M. H. Christiansen, Eds.]. (2017). Philosophical Transactions of the Royal Society: Biological Sciences. http://rstb.royalsocietypublishing.org/content/new-frontiers-statistical-learning-cognitive-sciences http://dx.doi.10.1098/rstb.2016.0047 SoftwareSOS:
eDom
Chronset:
TeachingCourses Taught: University of Toronto Scarborough (2017--):
BCBL (2012-2016):
AdvisingPostdoctoral:
Graduate:
Service:
Grant Reviewing: European Research Commission (ERC) National Sciences and Engineering Research Council (NSERC) Editorial Work: Guest Editor for a theme issue on New Frontiers for Statistical Learning in the Cognitive Sciences [B. C. Armstrong, R. Frost, M. H. Christiansen, Eds.]. (2017). Philosophical Transactions of the Royal Society: Biological Sciences. http://dx.doi.10.1098/rstb.2016.0047 Editorial Board Member, Journal of Experimental Psychology: Learning, Memory, & Cognition, 2019- Ad hoc reviewer for: Cognitive Science Journal of Experimental Psychology: Learning, Memory, and Cognition Journal of Memory & Language Language, Cognition and Neuroscience Behavior Research Methods Canadian Journal of Experimental Psychology Applied Psycholinguistics Psychonomic Bulletin & Review Cognition Bilingualism: Language & Cognition Journal of Cognitive Psychology Psychological Review Topics in Cognitive Science Cognitive Psychology Journal of Cognition and Development Experimental Psychology Visual Cognition Quarterly Journal of Experimental Psychology Cognitive Processing Scientific Reports Cortex The Journal of Open Psychology Data Frontiers in Psychology Proceedings of the Cognitive Science Society Annual Meetings Selected Proceedings of the EuroAsianPacific Joint Conference on Cognitive Science [EAPCogSci] Selected Proceedings of the Second Language Research Forum [SLRF] Selected Proceedings of the Workshop on Infant Language Development [WILD] In the NewsBrainprint: Identifying Individuals Based on the Neural Correlates of Reading Processes A series of news articles focused on my collaborative work with Professor Sarah Laszlo's research group at SUNY Binghamton, in which we studied how different classification methods can be used to uniquely identify individuals based on ERPs collected during reading. A sample of these articles follows:
Ambiguous Word Comprehension A press release by GUK (April, 2014) focused on my work in computational cognitive neuroscience and ambiguous word comprehension. LINK (in Spanish): http://guk.es/sala-de-prensa/neurociencia-para-que-los-ordenadores-entiendan-la-ironia-del-lenguaje-humano/ Archived Copy An artificial Judge for the Turing Test / Corpus-based Lexical-semantic knowledge An article in h+ Magazine (March, 2009) featured work that I co-authored and that was related to the development of an Artificial Critic for Humanness based on word co-occurrence statistics (MacInnes, Armstrong, et al. 2009; 2nd runner up for the Kurzweil prize at the 2009 Artificial General Intelligence Conference). LINK: http://www.hplusmagazine.com/articles/ai/future-machine-intelligence Archived Copy |
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Blair Armstrong,
2011-