↑
▾ Peer-reviewed Articles
▾ Peer-reviewed Conference Papers
▾ Book Chapters
▾ Peer-reviewed Articles in Undergraduate Journals
▾ Doctoral Dissertation
▾ Conference Proceedings
▾ Special Issues
▾ Software
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Peer-reviewed Articles


Siegelman, N., Raz., K., Armstrong, B. C. , & Frost, R. (in press). The statistical reader: The role of orthographic regularities in reading. Journal of Experimental Psychology: General.
Li, J.*, & Armstrong, B. C. (2024). Probing the Representational Structure of Regular Polysemy via Sense Analogy Questions: Insights from Contextual Word Vectors.  Cognitive Science, O48: e13416. 43 pages. 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.,145(12), 1128–1153. 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), https://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. https://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. C., , 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. Oral Presentation. Top 20% of submitted papers. Open-Source Materials Repo: https://osf.io/jsy87/
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 33rd Annual 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. C. (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, & Armstrong, B. C. (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 [Armstrong, B. C., R. Frost, M. H. Christiansen, Eds.]. (2017). Philosophical Transactions of the Royal Society: Biological Sciences. https://royalsocietypublishing.org/toc/rstb/2017/372/1711 http://doi.org/10.1098/rstb.2016.0047





Software



SOS: A software package for the Stochastic Optimization of Stimuli


eDom

  • An automated tool for collecting Relative Meaning Frequency ratings for homonyms (i.e., electronic Dominance ratings) based on dictionary (and participant-supplemented) definitions (developed with Natasha Tokowicz and David Plaut; an extension to different Spanish dialects was developed with Camila Zugarramurdi, Álvaro Cabana, Juan Valle Lisboa, and David Plaut)
  • Related articles and norms for American English and for two dialects of Spanish published in Behavior Research Methods
  • Software and norms available online at http://edom.cnbc.cmu.edu or https://www.bcbl.eu/databases/edom/

Chronset

  • An automated tool for detecting speech onset, developed with Frédéric Roux and Manuel Carreiras
  • Related articles published in Behavior Research Methods
  • This tool detects speech onset in a sound recording automatically, with near optimal precision as compared to multiple human ratings of speech onset based on a waveform and a spectrogram.
  • Standalone and online version of the software available at http://www.bcbl.eu/databases/chronset