1. 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 Conference of the Cognitive Science Society (pp. 273–278). Austin, TX: Cognitive Science Society.
2. 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. Hölscher, & T. F. Shipley (Eds.), Expanding the space of cognitive science: Proceedings of the 33rd Annual Meeting of the Cognitive Science Society (pp. 2223–2228). Austin, TX: Cognitive Science Society.
3. Armstrong, B. C., Watson, C. E., & Plaut, D. C. (2012). SOS! An algorithm and software for the stochastic optimization of stimuli. Behavior Research Methods. doi: 10.3758/s13428-011-0182-9
4. Azuma, T., & Van Orden, G. (1997). Why SAFE is better than FAST: The relatedness of a word’s meanings affects lexical decision times. Journal of Memory and Language, 36, 484–504.
5. Baayen, R. H., Davidson, D. J., & Bates, D. M. (2008). Mixed-effects modeling with crossed random effects for subjects and items. Journal of Memory and Language, 59, 390–412. doi: 10.1016/j.jml.2007.12.005