The time course of contextual cohort effects in auditory processing of category-ambiguous words: MEG evidence for a single “clash” as noun or verb

References

• Adachi, Y., Shimogawara, M., Higuchi, M., Haruta, Y., & Ochiai, M. (2001). Reduction of non-periodic environmental magnetic noise in MEG measurement by continuously adjusted least squares method. IEEE Transactions on Appiled Superconductivity, 11(1), 669–672. doi: 10.1109/77.919433
   Google Scholar
• Baayen, H., Piepenbrock, R., & Gulikers, L. (1995). CELEX2 LDC96L14 [ Web download]. Philadelphia, PA: Linguistic Data Consortium. Retrieved from https://catalog.ldc.upenn.edu/LDC96L14
   Google Scholar
• Baayen, H., Wurm, L. H., & Aycock, J. (2007). Lexical dynamics for low-frequency complex words: A regression study across tasks and modalities. The Mental Lexicon, 2(3), 419–463. doi: 10.1075/ml.2.3.06baa
   Google Scholar
• Balling, L. W., & Baayen, H. (2012). Probability and surprisal in auditory comprehension of morphologically complex words. Cognition, 125(1), 80–106. doi: 10.1016/j.cognition.2012.06.003
   PubMed Web of Science ®Google Scholar
• Balota, D. A., Yap, M. J., Hutchison, K. A., Cortese, M. J., Kessler, B., Loftis, B., … Treiman, R. (2007). The English lexicon project. Behavior Research Methods, 39(3), 445–459. doi: 10.3758/BF03193014
   PubMed Web of Science ®Google Scholar
• Boersma, P., & Weenink, D. (2014). Praat: Doing phonetics by computer [Computer software]. Retrieved from http://www.praat.org/
   Google Scholar
• Brainard, D. H. (1997). The psychophysics toolbox. Spatial Vision, 10(4), 433–436. doi: 10.1163/156856897X00357
   PubMedGoogle Scholar
• Brodbeck, C. (2017). Eelbrain (0.25). doi: 10.5281/zenodo.438193
   Google Scholar
• Brysbaert, M., & New, B. (2009). Moving beyond Kučera and Francis: A critical evaluation of current word frequency norms and the introduction of a new and improved word frequency measure for American English. Behavior Research Methods, 41(4), 977–990. doi: 10.3758/BRM.41.4.977
   PubMed Web of Science ®Google Scholar
• Brysbaert, M., New, B., & Keuleers, E. (2012). Adding part-of-speech information to the SUBTLEX-US word frequencies. Behavior Research Methods, 44(4), 991–997. doi: 10.3758/s13428-012-0190-4
   PubMed Web of Science ®Google Scholar
• Dahan, D., & Magnuson, J. S. (2006). Spoken word recognition. In M. J. Traxler & M. A. Gernsbacher (Eds.), Handbook of psycholinguistics (2nd ed., pp. 249–283). Boston, MA: Elsevier. doi: 10.1016/B978-012369374-7/50009-2
   Google Scholar
• Dahan, D., Swingley, D., Tanenhaus, M. K., & Magnuson, J. S. (2000). Linguistic gender and spoken-word recognition in French. Journal of Memory and Language, 42(4), 465–480. doi: 10.1006/jmla.1999.2688
   Web of Science ®Google Scholar
• Dahan, D., & Tanenhaus, M. K. (2004). Continuous mapping from sound to meaning in spoken-language comprehension: Immediate effects of verb-based thematic constraints. Journal of Experimental Psychology: Learning, Memory, and Cognition, 30(2), 498–513.
   PubMed Web of Science ®Google Scholar
• Dale, A. M., Liu, A. K., Fischl, B. R., Buckner, R. L., Belliveau, J. W., Lewine, J. D., & Halgren, E. (2000). Dynamic statistical parametric mapping. Neuron, 26(1), 55–67. doi: 10.1016/S0896-6273(00)81138-1
   PubMed Web of Science ®Google Scholar
• Davies, M. (2008). The corpus of contemporary American English (COCA): 520 million words, 1990-present. Retrieved from https://corpus.byu.edu/coca/
   Google Scholar
• Desikan, R. S., Ségonne, F., Fischl, B., Quinn, B. T., Dickerson, B. C., Blacker, D., … Killiany, R. J. (2006). An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest. NeuroImage, 31(3), 968–980. doi: 10.1016/j.neuroimage.2006.01.021
   PubMed Web of Science ®Google Scholar
• Ettinger, A., Linzen, T., & Marantz, A. (2014). The role of morphology in phoneme prediction: Evidence from MEG. Brain and Language, 129, 14–23. doi: 10.1016/j.bandl.2013.11.004
   PubMed Web of Science ®Google Scholar
• Frauenfelder, U. H., & Tyler, L. K. (1987). The process of spoken word recognition: An introduction. Cognition, 25(1–2), 1–20. doi: 10.1016/0010-0277(87)90002-3
   PubMed Web of Science ®Google Scholar
• Gagnepain, P., Henson, R. N., & Davis, M. H. (2012). Temporal predictive codes for spoken words in auditory cortex. Current Biology, 22(7), 615–621. doi: 10.1016/j.cub.2012.02.015
   PubMed Web of Science ®Google Scholar
• Gahl, S. (2008). Time and thyme are not homophones: The effect of Lemma frequency on word durations in spontaneous speech. Language, 84(3), 474–496. doi: 10.1353/lan.0.0035
   Web of Science ®Google Scholar
• Gaskell, M. G., & Marslen-Wilson, W. D. (1997). Integrating form and meaning: A distributed model of speech perception. Language and Cognitive Processes, 12(5–6), 613–656. doi: 10.1080/016909697386646
   Web of Science ®Google Scholar
• Gramfort, A., Luessi, M., Larson, E., Engemann, D. A., Strohmeier, D., Brodbeck, C., … Hämäläinen, M. (2013). MEG and EEG data analysis with MNE-Python. Frontiers in Neuroscience, 7. doi: 10.3389/fnins.2013.00267
   PubMed Web of Science ®Google Scholar
• Gramfort, A., Luessi, M., Larson, E., Engemann, D. A., Strohmeier, D., Brodbeck, C., … Hämäläinen, M. S. (2014). MNE software for processing MEG and EEG data. NeuroImage, 86(Suppl. C), 446–460. doi: 10.1016/j.neuroimage.2013.10.027
   PubMed Web of Science ®Google Scholar
• Grosjean, F. (1980). Spoken word recognition processes and the gating paradigm. Perception & Psychophysics, 28(4), 267–283. doi: 10.3758/BF03204386
   PubMed Web of Science ®Google Scholar
• Grosjean, F., Dommergues, J.-Y., Cornu, E., Guillelmon, D., & Besson, C. (1994). The gender-marking effect in spoken word recognition. Perception & Psychophysics, 56(5), 590–598. doi: 10.3758/BF03206954
   PubMed Web of Science ®Google Scholar
• Gwilliams, L., Lewis, G. A., & Marantz, A. (2016). Functional characterisation of letter-specific responses in time, space and current polarity using magnetoencephalography. NeuroImage, 132(Suppl. C), 320–333. doi: 10.1016/j.neuroimage.2016.02.057
   PubMed Web of Science ®Google Scholar
• Gwilliams, L., & Marantz, A. (2015). Non-linear processing of a linear speech stream: The influence of morphological structure on the recognition of spoken Arabic words. Brain and Language, 147(Suppl. C), 1–13. doi: 10.1016/j.bandl.2015.04.006
   PubMed Web of Science ®Google Scholar
• Hale, J. (2001). A probabilistic earley parser as a psycholinguistic model. Proceedings of the second meeting of the North American Chapter of the Association for Computational Linguistics on Language technologies (pp. 1–8). Association for Computational Linguistics. doi: 10.3115/1073336.1073357
   Google Scholar
• Holmes, A. P., & Friston, K. J. (1998). Generalisability, random effects & population inference. NeuroImage, 7, S754–S700.
   Google Scholar
• Kemps, R. J. J. K., Wurm, L. H., Ernestus, M., Schreuder, R., & Baayen, H. (2005). Prosodic cues for morphological complexity in Dutch and English. Language and Cognitive Processes, 20(1–2), 43–73. doi: 10.1080/01690960444000223
   Web of Science ®Google Scholar
• King, J., Linzen, T., & Marantz, A. (to appear). Syntactic categories as lexical features or syntactic heads: An MEG approach. Linguistic Inquiry. Retrieved from http://ling.auf.net/lingbuzz/002477
   Google Scholar
• Luce, P. A. (1986). A computational analysis of uniqueness points in auditory word recognition. Perception & Psychophysics, 39(3), 155–158. doi: 10.3758/BF03212485
   PubMed Web of Science ®Google Scholar
• Luce, P. A., & Pisoni, D. B. (1998). Recognizing spoken words: The neighborhood activation model. Ear and Hearing, 19(1), 1–36. doi: 10.1097/00003446-199802000-00001
   PubMed Web of Science ®Google Scholar
• Luce, P. A., Pisoni, D. B., & Goldinger, S. D. (1990). Similarity neighborhoods of spoken words. In G. Altmann (Ed.), Cognitive models of speech perception: Psycholinguistic and computational perspectives (pp. 122–147). Cambridge,MA: MIT Press.
   Google Scholar
• Magnuson, J. S., Dixon, J. A., Tanenhaus, M. K., & Aslin, R. N. (2007). The dynamics of lexical competition during spoken word recognition. Cognitive Science, 31(1), 133–156. doi: 10.1080/03640210709336987
   PubMed Web of Science ®Google Scholar
• Magnuson, J. S., Tanenhaus, M. K., & Aslin, R. N. (2008). Immediate effects of form-class constraints on spoken word recognition. Cognition, 108(3), 866–873. doi: 10.1016/j.cognition.2008.06.005
   PubMed Web of Science ®Google Scholar
• Maris, E., & Oostenveld, R. (2007). Nonparametric statistical testing of EEG- and MEG-data. Journal of Neuroscience Methods, 164(1), 177–190. doi: 10.1016/j.jneumeth.2007.03.024
   PubMed Web of Science ®Google Scholar
• Marslen-Wilson, W. D. (1980). Speech understanding as a psychological process. In J. C. Simon (Ed.), Spoken language generation and understanding (pp. 39–67). Dordrecht: Springer. doi: 10.1007/978-94-009-9091-3_2
   Google Scholar
• Marslen-Wilson, W. D. (1987). Functional parallelism in spoken word-recognition. Cognition, 25(1), 71–102. doi: 10.1016/0010-0277(87)90005-9
   PubMed Web of Science ®Google Scholar
• Marslen-Wilson, W. D., & Welsh, A. (1978). Processing interactions and lexical access during word recognition in continuous speech. Cognitive Psychology, 10(1), 29–63. doi: 10.1016/0010-0285(78)90018-X
   Web of Science ®Google Scholar
• McAllister, J. M. (1988). The use of context in auditory word recognition. Perception & Psychophysics, 44(1), 94–97. doi: 10.3758/BF03207482
   PubMed Web of Science ®Google Scholar
• McClelland, J. L., & Elman, J. L. (1986). The TRACE model of speech perception. Cognitive Psychology, 18(1), 1–86. doi: 10.1016/0010-0285(86)90015-0
   PubMed Web of Science ®Google Scholar
• McQueen, J. M. (2007). Eight questions about spoken-word recognition. In G. M. Gaskell (Ed.), The Oxford handbook of psycholinguistics (pp. 37–53). Oxford: Oxford University Press. doi: 10.1093/oxfordhb/9780198568971.013.0003
   Google Scholar
• Moscoso del Prado Martín, F., Kostić, A., & Baayen, H. (2004). Putting the bits together: An information theoretical perspective on morphological processing. Cognition, 94(1), 1–18. doi: 10.1016/j.cognition.2003.10.015
   PubMed Web of Science ®Google Scholar
• Moseley, R. L., & Pulvermüller, F. (2014). Nouns, verbs, objects, actions, and abstractions: Local fMRI activity indexes semantics, not lexical categories. Brain and Language, 132, 28–42. doi: 10.1016/j.bandl.2014.03.001
   PubMed Web of Science ®Google Scholar
• Norris, D. (1994). Shortlist: A connectionist model of continuous speech recognition. Cognition, 52(3), 189–234. doi: 10.1016/0010-0277(94)90043-4
   Web of Science ®Google Scholar
• Norris, D., & McQueen, J. M. (2008). Shortlist B: A Bayesian model of continuous speech recognition. Psychological Review, 115(2), 357–395. doi: 10.1037/0033-295X.115.2.357
   PubMed Web of Science ®Google Scholar
• Oldfield, R. C. (1971). The assessment and analysis of handedness: The Edinburgh inventory. Neuropsychologia, 9(1), 97–113. doi: 10.1016/0028-3932(71)90067-4
   PubMed Web of Science ®Google Scholar
• Pelli, D. G. (1997). The VideoToolbox software for visual psychophysics: Transforming numbers into movies. Spatial Vision, 10(4), 437–442. doi: 10.1163/156856897X00366
   PubMedGoogle Scholar
• Shannon, C. E. (1948). A mathematical theory of communication. The Bell System Technical Journal, 27(3), 379–423. doi: 10.1002/j.1538-7305.1948.tb01338.x
   Google Scholar
• Shillcock, R. C., & Bard, E. G. (1993). Modularity and the processing of closed-class words. In G. Altmann, & R. C. Shillcock (Eds.), Cognitive models of speech processing: The second sperlonga meeting (pp. 163–185). East Sussex: Lawrence Erlbaum Associates.
   Google Scholar
• Strand, J., Simenstad, A., Cooperman, A., & Rowe, J. (2014). Grammatical context constrains lexical competition in spoken word recognition. Memory & Cognition, 42(4), 676–687. doi: 10.3758/s13421-013-0378-6
   PubMed Web of Science ®Google Scholar
• Swinney, D. A. (1979). Lexical access during sentence comprehension: (Re)consideration of context effects. Journal of Verbal Learning and Verbal Behavior, 18(6), 645–659. doi: 10.1016/S0022-5371(79)90355-4
   Google Scholar
• Swinney, D. A., & Love, T. (2002). Context effects on lexical processing during auditory sentence comprehension. In E. Wintruk, A. D. Friederici, & T. Lachmann (Eds.), Basic functions of language, reading and reading disability (pp. 25–40). Boston, MA: Springer. doi: 10.1007/978-1-4615-1011-6_3
   Google Scholar
• Tanenhaus, M. K., & Donnenwerth-Nolan, S. (1984). Syntactic context and lexical access. The Quarterly Journal of Experimental Psychology Section A, 36(4), 649–661. doi: 10.1080/14640748408402184
   Google Scholar
• Tanenhaus, M. K., Leiman, J. M., & Seidenberg, M. S. (1979). Evidence for multiple stages in the processing of ambiguous words in syntactic contexts. Journal of Verbal Learning and Verbal Behavior, 18(4), 427–440. doi: 10.1016/S0022-5371(79)90237-8
   Google Scholar
• Tyler, L. K. (1984). The structure of the initial cohort: Evidence from gating. Perception & Psychophysics, 36(5), 417–427. doi: 10.3758/BF03207496
   PubMed Web of Science ®Google Scholar
• Tyler, L. K., Randall, B., & Stamatakis, E. A. (2008). Cortical differentiation for nouns and verbs depends on grammatical markers. Journal of Cognitive Neuroscience, 20(8), 1381–1389. doi: 10.1162/jocn.2008.20095
   PubMed Web of Science ®Google Scholar
• Tyler, L. K., & Wessels, J. (1983). Quantifying contextual contributions to word-recognition processes. Perception & Psychophysics, 34(5), 409–420. doi: 10.3758/BF03203056
   PubMed Web of Science ®Google Scholar
• Vigliocco, G., Vinson, D. P., Druks, J., Barber, H., & Cappa, S. F. (2011). Nouns and verbs in the brain: A review of behavioural, electrophysiological, neuropsychological and imaging studies. Neuroscience & Biobehavioral Reviews, 35(3), 407–426. doi: 10.1016/j.neubiorev.2010.04.007
   PubMed Web of Science ®Google Scholar
• Wurm, L. H., Ernestus, M. T. C., Schreuder, R., & Baayen, H. (2006). Dynamics of the auditory comprehension of prefixed words: Cohort entropies and conditional root uniqueness points. The Mental Lexicon, 1(1), 125–146. doi: 10.1075/ml.1.1.08wur
   Google Scholar
• Yuan, J., & Liberman, M. (2008). Speaker identification on the SCOTUS corpus. The Journal of the Acoustical Society of America, 123(5), 3878–3878. doi: 10.1121/1.2935783
   Google Scholar
• Zwitserlood, P. (1989). The locus of the effects of sentential-semantic context in spoken-word processing. Cognition, 32(1), 25–64. doi: 10.1016/0010-0277(89)90013-9
   PubMed Web of Science ®Google Scholar