How does emotional content affect lexical processing?

REFERENCES

• Altarriba, J., & Bauer, L. M. (2004). The distinctiveness of emotion concepts: A comparison between emotion, abstract, and concrete words. American Journal of Psychology, 117, 389–410. doi:10.2307/4149007
   PubMed Web of Science ®Google Scholar
• Baayen, R. H. (2009). languageR: Datasets and functions with “Analyzing Linguistic Data: A practical introduction to statistics”. Retrieved from http:/cran.r-project.org/package=languageR
   Google Scholar
• Balota, D. A., Yap, M. J., Cortese, M. J., Hutchison, K. A., Kessler, B., Loftis, B., … Treiman, R. (2007). The English Lexicon Project. Behavior Research Methods, 39, 445–459. doi:10.3758/BF03193014
   PubMed Web of Science ®Google Scholar
• Barr, D. J., Levy, R., Scheepers, C., & Tily, H. J. (2013). Random effects structure for confirmatory hypothesis testing: Keep it maximal. Journal of Memory and Language, 68, 255–278. doi:10.1016/j.jml.2012.11.001
   Web of Science ®Google Scholar
• Bates, D., & Maechler, M. (2009). lme4: Linear mixed-effects models using S4 classes. Retrieved from http:/cran.r-project.org/package=lme4
   Google Scholar
• Bradley, M. M., & Lang, P. J. (1999). Affective Norms for English Words (ANEW): Stimuli, instruction manual and affective ratings (Tech Report C-1). Gainesville: University of Florida, Center for Research in Psychophysiology.
   Google Scholar
• Bradley, M. M., & Lang, P. J. (2000). Measuring emotion: Behavior, feeling, and physiology. Cognitive Neuroscience of Emotion, 25, 49–59.
   Google Scholar
• Coltheart, M. (1981). The MRC Psycholinguistic Database. Quarterly Journal of Experimental Psychology, 33A, 497–505.
   Web of Science ®Google Scholar
• Estes, Z., & Adelman, J. S. (2008a). Automatic vigilance for negative words is categorical and general. Emotion, 8, 453–457. doi:10.1037/a0012887
   Web of Science ®Google Scholar
• Estes, Z., & Adelman, J. S. (2008b). Automatic vigilance for negative words in lexical decision and naming: Comment on Larsen, Mercer & Balota (2006). Emotion, 8, 441–444. doi:10.1037/1528-3542.8.4.441
   PubMed Web of Science ®Google Scholar
• Havas, D. A., & Matheson, J. (2013). The functional role of the periphery in emotional language comprehension. Frontiers in Cognitive Science, 4, 294. doi:10.3389/fpsyg.2013.00294
   Web of Science ®Google Scholar
• Keuleers, E., Lacey, P., Rastle, K., & Brysbaert, M. (2012). The British Lexicon Project: Lexical decision data for 28,730 monosyllabic and disyllabic English words. Behavior Research Methods, 44, 287–304. doi:10.3758/s13428-011-0118-4
   PubMed Web of Science ®Google Scholar
• Kousta, S.-T., Vigliocco, G., Vinson, D. P., Andrews, M., & Del Campo, E. (2011). The representation of abstract words: Why emotion matters. Journal of Experimental Psychology: General, 140(1), 14–34. doi:10.1037/a0021446
   PubMed Web of Science ®Google Scholar
• Kousta, S.-T., Vinson, D. P., & Vigliocco, G. (2009). Emotion words, regardless of polarity, have a processing advantage over neutral words. Cognition, 112, 473–481. doi:10.1016/j.cognition.2009.06.007
   PubMed Web of Science ®Google Scholar
• Lang, P. J., Bradley, M. M., & Cuthbert, B. N. (1997). Motivated attention: Affect, activation and action. In P. J. Lang, R. F. Simons, & M. T. Balaban (Eds.), Attention and orienting: Sensory and motivational processes. Hillsdale, NJ: Erlbaum.
   Google Scholar
• Larsen, R. J., Mercer, K. A., & Balota, D. A. (2006). Lexical characteristics of words used in emotional Stroop experiments. Emotion, 6(1), 62–72. doi:10.1037/1528-3542.6.1.62
   PubMed Web of Science ®Google Scholar
• Larsen, R. J., Mercer, K. A., Balota, D. A., & Strube, M. J. (2008). Not all negative words slow down lexical decision and naming speed: Importance of word arousal. Emotion, 8, 445–452. doi:10.1037/1528-3542.8.4.445
   Web of Science ®Google Scholar
• Moseley, R., Carota, F., Hauk, O., Mohr, B., & Pulvermüller, F. (2012). A role for the motor system in binding abstract emotional meaning. Cerebral Cortex, 22, 1634–1647. doi:10.1093/cercor/bhr238
   PubMed Web of Science ®Google Scholar
• Pratto, F., & John, O. P. (1991). Automatic vigilance: The attention-grabbing power of negative social information. Journal of Personality and Social Psychology, 61, 380–391. doi:10.1037/0022-3514.61.3.380
   PubMed Web of Science ®Google Scholar
• R Core Team. (2013). R: A language and environment for statistical computing. Vienna: R Foundation for Statistical Computing. Retrieved from http://www.R-project.org/.
   Google Scholar
• Stadthagen-Gonzalez, H., & Davis, C. J. (2006). The Bristol norms for age of acquisition, imageability and familiarity. Behavior Research Methods, 38, 598–605. doi:10.3758/BF03193891
   PubMed Web of Science ®Google Scholar
• Strapparava, C., & Valitutti, A. (2004). WordNet-Affect: An affective extension of WordNet. In Proceedings of the 4th International Conference on Language Resources and Evaluation (LREC 2004) (pp. 1083–1086). Lisbon: European Language Resources Association.
   Google Scholar
• Vigliocco, G., Meteyard, L., Andrews, M., & Kousta, S.-T. (2009). Toward a theory of semantic representation. Language and Cognition, 1, 219–247. doi:10.1515/LANGCOG.2009.011
   Google Scholar
• Vigliocco, G.Vinson, D., Della Rosa, P., Kousta, S. T., Devlin, J., & Cappa, S. F. (2013). The neural representation of abstract words: A role of emotion. Cerebral Cortex. Advance online publication. doi:10.1093/cercor/bht025
   PubMed Web of Science ®Google Scholar
• Wurm, L. H. (2007). Danger and usefulness: An alternative framework for understanding rapid evaluation effects in perception? Psychonomic Bulletin and Review, 14, 1218–1225. doi:10.3758/BF03193116
   PubMed Web of Science ®Google Scholar