1887
  1. Home
  2. e-Journals
  3. The Mental Lexicon
  4. Volume 11, Issue 1
  5. Article
Volume 11, Issue 1
  • ISSN 1871-1340
  • E-ISSN: 1871-1375
USD
Buy:$35.00 + Taxes

Abstract

A large literature documenting facilitative effects for high frequency complex words and phrases has led to proposals that high frequency phrases may be stored in memory rather than constructed on-line from their component parts (similarly to high frequency complex words). To investigate this, we explored language processing during a novel picture description task. Using the magneto-encephalographam (MEG) technique and generalised additive mixed-effects modelling, we characterised the effects of the frequency of use of single words as well as two-, three-, and four-word sequences (N-grams) on brain activity during the pre-production stage of unconstrained overt picture description. We expected amplitude responses to be modulated by N-gram frequency such that if N-grams were stored we would see a corresponding reduction or flattening in amplitudes as frequency increased. We found that while amplitude responses to increasing N-gram frequencies corresponded with our expectations about facilitation, the effect appeared at low frequency ranges and for single words only in the phonological network. We additionally found that high frequency N-grams elicited activity increases in some networks, which may be signs of competition or combination depending on the network. Moreover, this effect was not reliable for single word frequencies. These amplitude responses do not clearly support storage for high frequency multi-word sequences. To probe these unexpected results, we turned our attention to network topographies and the timing. We found that, with the exception of an initial ‘sentence’ network, all the networks aggregated peaks from more than one domain (e.g. semantics and phonology). Moreover, although activity moved serially from anterior ventral networks to dorsal posterior networks during processing, as expected in combinatorial accounts, sentence processing and semantic networks ran largely in parallel. Thus, network topographies and timing may account for (some) facilitative effects associated with frequency. We review literature relevant to the network topographies and timing and briefly discuss our results in relation to current processing and theoretical models.

© 2016 John Benjamins Publishing Company
Loading

Article metrics loading...

/content/journals/10.1075/ml.11.1.06tre
2016-06-07
2025-04-26

  • From This Site

    /content/journals/10.1075/ml.11.1.06tre
    dcterms_title,dcterms_subject,pub_keyword
    -contentType:Journal -contentType:Contributor -contentType:Concept -contentType:Institution
    10
    5
Loading full text...

Full text loading...

References

  1. Abbot-Smith, K. , & Tomasello, M
    (2006) Exemplar-learning and schematization in a usage-based account of syntactic acquisition. The Linguistic Review, 23, 275–290. doi: 10.1515/TLR.2006.011
     https://doi.org/10.1515/TLR.2006.011 [Google Scholar]
  2. Allen, K. , Pereira, F. , Botvinick, M. , & Goldberg, A.E.
    (2012) Distinguishing grammatical constructions with fMRI pattern analysis. Brain and Language, 123(3), 174–182. doi: 10.1016/j.bandl.2012.08.005
     https://doi.org/10.1016/j.bandl.2012.08.005 [Google Scholar]
  3. Arbib, M.A. , & Lee, J
    (2008) Describing visual scenes: Towards a neurolinguistics based on construction grammar. Brain Research, 1225, 146–162. doi: 10.1016/j.brainres.2008.04.075
     https://doi.org/10.1016/j.brainres.2008.04.075 [Google Scholar]
  4. Arnon, I. , & Snider, N
    (2010) More than words: Frequency effects for multi-word phrases. Journal of Memory and Language, 62, 67–82. doi: 10.1016/j.jml.2009.09.005
     https://doi.org/10.1016/j.jml.2009.09.005 [Google Scholar]
  5. Baayen, R.H.
    (2010) A real experiment is a factorial experiment?The Mental Lexicon, 5(1), 149–157. doi: 10.1075/ml.5.1.06baa
     https://doi.org/10.1075/ml.5.1.06baa [Google Scholar]
  6. (2010b) Demythologizing the word frequency effect: A discriminative learning perspective. The Mental Lexicon, 5, 436–461. doi: 10.1075/ml.5.3.10baa
     https://doi.org/10.1075/ml.5.3.10baa [Google Scholar]
  7. Baayen, R.H. , Hendrix, P. , & Ramscar, M
    (2013) Sidestepping the combinatorial explosion: An explanation of N-gram frequency effects based on naive discriminative learning. Language and Speech, 56(3), 329–347. doi: 10.1177/0023830913484896
     https://doi.org/10.1177/0023830913484896 [Google Scholar]
  8. Bajada, C.J. , Ralph, M.A.L. , & Cloutman, L.L.
    (2015) Transport for language South of the Sylvian Fissure: The routes and history of the main tracts and stations in the ventral language network. Cortex, 69, 141–151. doi: 10.1016/j.cortex.2015.05.011
     https://doi.org/10.1016/j.cortex.2015.05.011 [Google Scholar]
  9. Bannard, C. , & Matthews, D
    (2008) Stored word sequences in language learning: The effect of familiarity on children’s repetition of four-word combinations. Psychological Science, 19, 241–248. doi: 10.1111/j.1467‑9280.2008.02075.x
     https://doi.org/10.1111/j.1467-9280.2008.02075.x [Google Scholar]
  10. Bardouille, T. , & Bow, S
    (2012) State-related changes in MEG functional connectivity reveal the task-positive sensorimotor network. PLoS One, 7, 1–8. doi: 10.1371/journal.pone.0048682
     https://doi.org/10.1371/journal.pone.0048682 [Google Scholar]
  11. Bell, A. , Brenier, J.M. , Gregory, M. , Girand, C. , & Jurafsky, D
    (2009) Predictability effects on durations of content and function words in conversational English. Journal of Memory and Language, 60, 92–111. doi: 10.1016/j.jml.2008.06.003
     https://doi.org/10.1016/j.jml.2008.06.003 [Google Scholar]
  12. Bemis, D.K. , & Pylkkänen, L
    (2012) Basic linguistic composition recruits the left anterior temporal lobe and left angular gyrus during both listening and reading. Cerebral Cortex, bhs170.
     [Google Scholar]
  13. (2013) Flexible composition: MEG evidence for the deployment of basic combinatorial linguistic mechanisms in response to task demands. PloS One, 8, e73949. doi: 10.1371/journal.pone.0073949
     https://doi.org/10.1371/journal.pone.0073949 [Google Scholar]
  14. Bien, H. , Baayen, H.R. , & Levelt, W.J.M
    (2011) Frequency effects in the production of Dutch deverbal adjectives and inflected verbs. In R. Bertram , J. Hyönä , & M. Laine (Eds.), Morphology in language comprehension, production and acquisition (pp. 683–715). London: Psychology Press.
     [Google Scholar]
  15. Binder, J. , Desai, R. , Graves, W. , & Conant, L
    (2009, DEC). Where is the semantic system? A critical review and meta-analysis of 120 functional neuroimaging studies. Cerebral Cortex, 19, 2767–2796. doi: 10.1093/cercor/bhp055
     https://doi.org/10.1093/cercor/bhp055 [Google Scholar]
  16. Binney, R.J. , Parker, G.J.M. , & Lambon Ralph, M.A
    (2012) Convergent Connectivity and Graded Specialization in the Rostral Human Temporal Lobe as Revealed by Diffusion-Weighted Imaging Probabilistic Tractography. Journal of Cognitive Neuroscience, 24, 1998–2014. doi: 10.1162/jocn_a_00263
     https://doi.org/10.1162/jocn_a_00263 [Google Scholar]
  17. Bock, J
    (1986) Meaning, sound, and syntax - Lexical priming in sentence production. Journal of Experimental Psychology-Learning Memory and Cognition, 12, 575–586. doi: 10.1037/0278‑7393.12.4.575
     https://doi.org/10.1037/0278-7393.12.4.575 [Google Scholar]
  18. Bonaiuto, J. & Arbib, M.A
    (2010) Extending the mirror neuron system model, II: what did I just do? A new role for mirror neurons. Biological Cybernetics, 102, 341–59. doi: 10.1007/s00422‑010‑0371‑0
     https://doi.org/10.1007/s00422-010-0371-0 [Google Scholar]
  19. Bonner, M.F. , Peelle, J.E. , Cook, P.A. , & Grossman, M
    (2013) Heteromodal conceptual processing in the angular gyrus. NeuroImage, 71, 175–186. doi: 10.1016/j.neuroimage.2013.01.006
     https://doi.org/10.1016/j.neuroimage.2013.01.006 [Google Scholar]
  20. Bornkessel, I. , Zysset, S. , Friederici, A.D. , von Cramon, D.Y. , & Schlesewsky, M
    (2005) Who did what to whom? The neural basis of argument hierarchies during language comprehension. NeuroImage, 26, 221–233. doi: 10.1016/j.neuroimage.2005.01.032
     https://doi.org/10.1016/j.neuroimage.2005.01.032 [Google Scholar]
  21. Brennan, J. , Nir, Y. , Hasson, U. , Malach, R. , Heeger, D. , & Pylkkänen, L
    (2012) Syntactic structure building in the anterior temporal lobe during natural story listening. Brain and Language, 120, 163–173. doi: 10.1016/j.bandl.2010.04.002
     https://doi.org/10.1016/j.bandl.2010.04.002 [Google Scholar]
  22. Brookes, M.J. , Woolrich, M. , Luckhoo, H. , Price, D. , Hale, J.R. , Stephenson, M.C. , Barnes, G.R. , Smith, S.M. , & Morris, P.G.
    (2011) Investigating the electrophysiological basis of resting state networks using magnetoencephalography. Procedings of the National Academy of Sciences of the United States of America, 108, 16783–16788. doi: 10.1073/pnas.1112685108
     https://doi.org/10.1073/pnas.1112685108 [Google Scholar]
  23. Bybee, J. , & McClelland, J.L.
    (2005) Alternatives to the combinatorial paradigm of linguistic theory based on domain general principles of human cognition. The Linguistic Review, 22, 381–410. doi: 10.1515/tlir.2005.22.2‑4.381
     https://doi.org/10.1515/tlir.2005.22.2-4.381 [Google Scholar]
  24. Caplan, D. , Chen, E. , & Waters, G
    (2008) Task-dependent and task-independent neurovascular responses to syntactic processing. Cortex, 44, 257–275. doi: 10.1016/j.cortex.2006.06.005
     https://doi.org/10.1016/j.cortex.2006.06.005 [Google Scholar]
  25. Catani, M. , Jones, D. , & Fytche, D
    (2005) Perisylvian language networks of the human brain. Annals of Neurology, 57, 8–16. doi: 10.1002/ana.20319
     https://doi.org/10.1002/ana.20319 [Google Scholar]
  26. Catani, M. , Mesulam, M.M. , Jakobsen, E. , Malik, F. , Matersteck, A. , Wieneke, C. , Thompson, C.K. , Thiebaut de Schotten, M. , Dell’Acqua, F. , Weintraub, S. , & Rogalski, E
    (2013) A novel frontal pathway underlies verbal fluency in primary progressive aphasia. Brain, awt163, 2619–2628. doi: 10.1093/brain/awt163
     https://doi.org/10.1093/brain/awt163 [Google Scholar]
  27. Cohen, J
    (1983) The cost of dichotomization. Applied Psychological Measurement, 7, 249–253. doi: 10.1177/014662168300700301
     https://doi.org/10.1177/014662168300700301 [Google Scholar]
  28. Columbus, G
    (2010) Processing MWUs: Are MWU subtypes psycholinguistically real?In D. Wood (Ed.), Perspectives on formulaic language: Acquisition and communication (pp. 194–212). London and New York: Continuum.
     [Google Scholar]
  29. (2012) An analysis of the processing of multiword units in sentence reading and unit presentation using eye movement data: Implications for theories of mwus. PhD dissertation, University of Alberta, Edmonton, Canada.
     [Google Scholar]
  30. Culicover, P.W. , & Jackendoff, R
    (2005) Simpler syntax. Oxford, UK: Oxford University Press. doi: 10.1093/acprof:oso/9780199271092.001.0001
     https://doi.org/10.1093/acprof:oso/9780199271092.001.0001 [Google Scholar]
  31. De Cat, C. , Klepousniotou, E. , & Baayen, R.H.
    (2015) Representational deficit or processing effect? An electrophysiological study of noun-noun compound processing by very advanced L2 speakers of English. Frontiers in Psychology, 6, 77 doi: 10.3389/fpsyg.2015.00077
     https://doi.org/10.3389/fpsyg.2015.00077 [Google Scholar]
  32. Dehaene‐Lambertz, G. , Dehaene, S. , Anton, J.L. , Campagne, A. , Ciuciu, P. , Dehaene, G.P. , Denghien, I. , Jobert, A. , Lebihan, D. , Sigman, M. , Pallier, C. , & Poline, J.B.
    (2006) Functional segregation of cortical language areas by sentence repetition. Human Brain Mapping, 27, 360–371. doi: 10.1002/hbm.20250
     https://doi.org/10.1002/hbm.20250 [Google Scholar]
  33. Del Prato, P. , & Pylkkanen, L
    (2014) MEG evidence for conceptual combination but not numeral quantification in the left anterior temporal lobe during language production. Language Sciences, 5, 524.
     [Google Scholar]
  34. den Ouden, D.B. , Saur, D. , Mader, W. , Schelter, B. , Lukic, S. , Wali, E. , Timmer, J. , & Thompson, C.K.
    (2012) Network modulation during complex syntactic processing. NeuroImage, 59, 815–823. doi: 10.1016/j.neuroimage.2011.07.057
     https://doi.org/10.1016/j.neuroimage.2011.07.057 [Google Scholar]
  35. Dikker, S. , & Pylkkänen, L
    (2013) Predicting language: MEG evidence for lexical preactivation. Brain and language, 127, 55–64. doi: 10.1016/j.bandl.2012.08.004
     https://doi.org/10.1016/j.bandl.2012.08.004 [Google Scholar]
  36. Dronkers, N. , Wilkins, D. , Van Jr., V. , Redfern, B. , & Jaeger, J.J.
    (2004) Lesion analysis of the brain areas involved in language comprehension. Cognition, 92, 145–177. doi: 10.1016/j.cognition.2003.11.002
     https://doi.org/10.1016/j.cognition.2003.11.002 [Google Scholar]
  37. Duffau, H. , Moritz-Gasser, S. , & Mandonnet, E
    (2014) A re-examination of the neural basis of language processing: Proposal of a dynamic hodotopical model from data provided by brain stimulation mapping during picture naming. Brain and Language, 131, 1–10. doi: 10.1016/j.bandl.2013.05.011
     https://doi.org/10.1016/j.bandl.2013.05.011 [Google Scholar]
  38. Ellis, N.C. , & Simpson-Vlach, R (2009) Formulaic language in native speakers: Triangulating psycholinguistics, corpus linguistics, and education. Corpus Linguistics and Linguistic Theory, 5(1), 61–78. doi: 10.1515/CLLT.2009.003
     https://doi.org/10.1515/CLLT.2009.003 [Google Scholar]
  39. Elman, J.L.
    (2009) On the meaning of words and dinosaur bones: Lexical knowledge without a lexicon. Cognitive Science, 33, 547–582. doi: 10.1111/j.1551‑6709.2009.01023.x
     https://doi.org/10.1111/j.1551-6709.2009.01023.x [Google Scholar]
  40. Embick, D. , Hackl, M. , Schaeffer, J. , Kelepir, M. , & Marantz, A
    (2001) A magnetoencephalographic component whose latency reflects lexical frequency. Cognitive Brain Research, 10, 345–348. doi: 10.1016/S0926‑6410(00)00053‑7
     https://doi.org/10.1016/S0926-6410(00)00053-7 [Google Scholar]
  41. Erickson, L.C. , Zielinski, B.A. , Zielinski, J.E. , Liu, G. , Turkeltaub, P.E. , Leaver, A.M. , & Rauschecker, J.P. (2014) Distinct cortical locations for integration of audiovisual speech and the McGurk effect. Language Sciences, 5, 534.
     [Google Scholar]
  42. Faraway, J.J.
    (2006) Extending linear models with R: Generalized linear, mixed effects and nonparametric regression models. Boca Raton, FL: Chapman & Hall/CRC.
     [Google Scholar]
  43. Fedorenko, E. , Duncan, J. , & Kanwisher, N
    (2012) Language-selective and domain-general regions lie side by side within Broca’s area. Current Biology, 22, 2059–2062. doi: 10.1016/j.cub.2012.09.011
     https://doi.org/10.1016/j.cub.2012.09.011 [Google Scholar]
  44. Fornito, A. , Zalesky, A. , & Breakspear, M
    (2013) Graph analysis of the human connectome: Promise, progress, and pitfalls. NeuroImage80, 426–444. doi: 10.1016/j.neuroimage.2013.04.087
     https://doi.org/10.1016/j.neuroimage.2013.04.087 [Google Scholar]
  45. Goldberg, A.E.
    (2003) Constructions: A new theoretical approach to language. Trends in Cognitive Science, 7(5), 219–224. doi: 10.1016/S1364‑6613(03)00080‑9
     https://doi.org/10.1016/S1364-6613(03)00080-9 [Google Scholar]
  46. Goldberg, A
    (2006) Constructions at work: the nature of generalization in language. Oxford, UK: Oxford University Press.
     [Google Scholar]
  47. Gregory, M.L. , Raymond, W.D. , Bell, A. , Fosler-Lussier, E. , & Jurafsky, D
    (1999) The effects of collocational strength and contextual predictability in lexical production. CLS–99, 35, 151–166.
     [Google Scholar]
  48. Grewe, T. , Bornkessel-Schlesewsky, I. , Zysset, S. , Wiese, R. , von Cramon, D.Y. , & Schlesewsky, M
    (2007) The role of the posterior superior temporal sulcus in the processing of unmarked transitivity. NeuroImage, 35, 343–352. doi: 10.1016/j.neuroimage.2006.11.045
     https://doi.org/10.1016/j.neuroimage.2006.11.045 [Google Scholar]
  49. Griffiths, J.D. , Marslen-Wilson, W.D. , Stamatakis, E.A. , & Tyler, L.K.
    (2013) Functional organization of the neural language system: Dorsal and ventral pathways are critical for syntax. Cerebral Cortex, 23, 139–147. doi: 10.1093/cercor/bhr386
     https://doi.org/10.1093/cercor/bhr386 [Google Scholar]
  50. Grill-Spector, K. , Henson, R. , & Martin, A
    (2006) Repetition and the brain: Neural models of stimulus-specific effects. Trends in Cognitive Sciences, 10, 14–23. doi: 10.1016/j.tics.2005.11.006
     https://doi.org/10.1016/j.tics.2005.11.006 [Google Scholar]
  51. Hagoort, P (2005) On Broca, brain, and binding: A new framework. Trends in Cognitive Science, 9, 416–423. doi: 10.1016/j.tics.2005.07.004
     https://doi.org/10.1016/j.tics.2005.07.004 [Google Scholar]
  52. (2013) MUC (Memory, Unification, Control) and beyond. Frontiers in Psychology, 4.
     [Google Scholar]
  53. Haller, S. , Klarhoefer, M. , Schwarzbach, J. , Radue, E.W. , & Indefrey, P
    (2007) Spatial and temporal analysis of fMRI data on word and sentence reading. European Journal of Neuroscience, 26, 2074–2084. doi: 10.1111/j.1460‑9568.2007.05816.x
     https://doi.org/10.1111/j.1460-9568.2007.05816.x [Google Scholar]
  54. Hansen, P.C. , Kringelbach, M.L. , & Salmelin, R
    (2010) MEG: An introduction to methods. Oxford, UK: Oxford University Press. doi: 10.1093/acprof:oso/9780195307238.001.0001
     https://doi.org/10.1093/acprof:oso/9780195307238.001.0001 [Google Scholar]
  55. Hastie, T. , & Tibshirani, R
    (1990) Generalized additive model regression. New York, NY: Chapman & Hall.
     [Google Scholar]
  56. Hebb, D.O.
    (1949) The organization of behavior. New York, NY: Wiley & Sons.
     [Google Scholar]
  57. Hein, G. , & Knight, R.T.R.T
    (2008) Superior temporal sulcus – it’s my area: Or is it?Journal of Cognitive Neuroscience, 20, 2125–2136. doi: 10.1162/jocn.2008.20148
     https://doi.org/10.1162/jocn.2008.20148 [Google Scholar]
  58. Hendrix, P
    (2009) Electrophysiological effects in language production: A picture naming study using generalized additive modeling. MA dissertation, Radboud University, Nijmegen, the Netherlands.
     [Google Scholar]
  59. Herrmann, B. , Maess, B. , Hahne, A. , Schröger, E. , & Friederici, A.D.
    (2011) Syntactic and auditory spatial processing in the human temporal cortex: An MEG study. NeuroImage, 57, 624–633. doi: 10.1016/j.neuroimage.2011.04.034
     https://doi.org/10.1016/j.neuroimage.2011.04.034 [Google Scholar]
  60. Hickok, G. , & Poeppel, D
    (2004) Dorsal and ventral streams: A framework for understanding aspects of the functional anatomy of language. Cognition, 92, 67–99. doi: 10.1016/j.cognition.2003.10.011
     https://doi.org/10.1016/j.cognition.2003.10.011 [Google Scholar]
  61. (2007) The cortical organization of speech processing. Nature Reviews Neuroscience, 8, 393–402. doi: 10.1038/nrn2113
     https://doi.org/10.1038/nrn2113 [Google Scholar]
  62. Hocking, J. , & Price, C.J.
    (2008) The role of the posterior superior temporal sulcus in audiovisual processing. Cerebral Cortex, 18, 2439–2449. doi: 10.1093/cercor/bhn007
     https://doi.org/10.1093/cercor/bhn007 [Google Scholar]
  63. Hurley, R.S. , Paller, K.A. , Rogalski, E.J. , & Mesulam, M.M.
    (2012) Neural mechanisms of object naming and word comprehension in primary progressive aphasia. The Journal of Neuroscience, 32, 4848–4855. doi: 10.1523/JNEUROSCI.5984‑11.2012
     https://doi.org/10.1523/JNEUROSCI.5984-11.2012 [Google Scholar]
  64. Indefrey, P. , Brown, C.M. , Hellwig, F. , Amunts, K. , Herzog, H. , & Seitz, R.J.
    (2001) A neural correlate of syntactic encoding during speech production. Proceedings of the National Academy of Sciences of the United States of America , 98, 5933–5936.
     [Google Scholar]
  65. Indefrey, P. , & Levelt, W.J.
    (2004) The spatial and temporal signatures of word production components. Cognition, 92, 101–144. doi: 10.1016/j.cognition.2002.06.001
     https://doi.org/10.1016/j.cognition.2002.06.001 [Google Scholar]
  66. Jackendoff, R
    (2002a) Foundations of language. Oxford, UK: Oxford University Press. doi: 10.1093/acprof:oso/9780198270126.001.0001
     https://doi.org/10.1093/acprof:oso/9780198270126.001.0001 [Google Scholar]
  67. (2002b) What’s in the lexicon?In S. Nooteboom , F. Weerman , & F. Wijnen (Eds.), Storage and computation in the language faculty (pp. 23–58). Dordrecht, The Netherlands: Kluwer Academic Press. doi: 10.1007/978‑94‑010‑0355‑1_2
     https://doi.org/10.1007/978-94-010-0355-1_2 [Google Scholar]
  68. (2007) A parallel architecture perspective on language processing. Brain Research, 1146, 2–22. doi: 10.1016/j.brainres.2006.08.111
     https://doi.org/10.1016/j.brainres.2006.08.111 [Google Scholar]
  69. (2011) What is the human language faculty: Two views. Language, 87, 586–624. doi: 10.1353/lan.2011.0063
     https://doi.org/10.1353/lan.2011.0063 [Google Scholar]
  70. Janssen, N. , & Barber, H.A.
    (2012) Phrase frequency effects in language production. PloS One, 7, e33202. doi: 10.1371/journal.pone.0033202
     https://doi.org/10.1371/journal.pone.0033202 [Google Scholar]
  71. Jiang, N. , & Nekrasova, T
    (2007) The processing of formulaic sequences by second language speakers. The Modern Language Journal, 91, 433–445. doi: 10.1111/j.1540‑4781.2007.00589.x
     https://doi.org/10.1111/j.1540-4781.2007.00589.x [Google Scholar]
  72. Jurafsky, D. , Bell, M. , & Raymond, W
    (2001) Probabilistic relations between words: Evidence from reduction in lexical production. In J. Bybee & P. Hopper (Eds.), Frequency and the emergence of linguistic structure (pp. 229–254). Amsterdam: John Benjamins. doi: 10.1075/tsl.45.13jur
     https://doi.org/10.1075/tsl.45.13jur [Google Scholar]
  73. Kapatsinski, V. , & Radicke, J
    (2009) Frequency and the emergence of prefabs: Evidence from monitoring. In R. Corrigan , E. Moravcsik , H. Ouali , & K. Wheatley (Eds.), Formulaic language, Vol. ii: Acquisition, loss, psychological reality, functional explanations (pp. 499–522). Amsterdam: John Benjamins. doi: 10.1075/tsl.83.14kap
     https://doi.org/10.1075/tsl.83.14kap [Google Scholar]
  74. Keele, L
    (2008) Semiparametric regression for the social sciences. New York, NY: Chapman & Hall/CRC.
     [Google Scholar]
  75. Keller, F. , & Lapata, M
    (2003) Using the web to obtain frequencies for unseen bigrams. Journal Computational Linguistics, 29, 459–484. doi: 10.1162/089120103322711604
     https://doi.org/10.1162/089120103322711604 [Google Scholar]
  76. Kryuchkova, T. , Tucker, B.V. , Wurm, L.H. , & Baayen, R.H.
    (2012) Danger and usefulness are detected early in auditory lexical processing: Evidence from electroencephalography. Brain and Language, 122, 81–91. doi: 10.1016/j.bandl.2012.05.005
     https://doi.org/10.1016/j.bandl.2012.05.005 [Google Scholar]
  77. Lahnakoski, J.M. , Glerean, E. , Salmi, J. , Jääskeläinen, I.P. , Sams, M. , Hari, R. , & Nummenmaa, L
    (2012) Naturalistic fMRI mapping reveals superior temporal sulcus as the hub for the distributed brain network for social perception. Frontiers in Human Neuroscience, 6, 233. doi: 10.3389/fnhum.2012.00233
     https://doi.org/10.3389/fnhum.2012.00233 [Google Scholar]
  78. Lamb, S
    (1966) Outline of stratificational grammar. Washington, DC: Georgetown University Press.
     [Google Scholar]
  79. Lau, E.F. , Gramfort, A. , Hämäläinen, M.S. , & Kuperberg, G.R.
    (2013) Automatic semantic facilitation in anterior temporal cortex revealed through multimodal neuroimaging. The Journal of Neuroscience, 33, 17174–17181. doi: 10.1523/JNEUROSCI.1018‑13.2013
     https://doi.org/10.1523/JNEUROSCI.1018-13.2013 [Google Scholar]
  80. Levelt, W.J.
    (1983) Monitoring and self-repair in speech. Cognition, 14, 41–104. doi: 10.1016/0010‑0277(83)90026‑4
     https://doi.org/10.1016/0010-0277(83)90026-4 [Google Scholar]
  81. Lewis, G. , & Poeppel, D
    (2014) The role of visual representations during the lexical access of spoken words. Brain and Language, 134, 1–10. doi: 10.1016/j.bandl.2014.03.008
     https://doi.org/10.1016/j.bandl.2014.03.008 [Google Scholar]
  82. Lewis, G. , Solomyak, O. , & Marantz, A
    (2011) The neural basis of obligatory decomposition of suffixed words. Brain and Language, 118, 118–127. doi: 10.1016/j.bandl.2011.04.004
     https://doi.org/10.1016/j.bandl.2011.04.004 [Google Scholar]
  83. Li, L. , Miller, E.K. , & Desimone, R
    (2004) The representation of stimulus familiarity in anterior inferior temporal cortex. Journal of Neuropsychology, 69, 1918–1929.
     [Google Scholar]
  84. Llorens, A. , Trébuchon, A. , Riès, S. , Liégeois-Chauvel, C. , & Alario, F
    (2014) How familiarization and repetition modulate the picture naming network. Brain and Language, 133, 47–58. doi: 10.1016/j.bandl.2014.03.010
     https://doi.org/10.1016/j.bandl.2014.03.010 [Google Scholar]
  85. Lu, Z. , & Kaufman, L
    (2003) Magnetic source imaging of the human brain. New York, NY: Routledge.
     [Google Scholar]
  86. MacCallum, R. , Zhang, S. , Preacher, K. , & Rucker, D
    (2002) On the practice of dichotomization of quantitative variables. Psychological Methods, 7, 19–40. doi: 10.1037/1082‑989X.7.1.19
     https://doi.org/10.1037/1082-989X.7.1.19 [Google Scholar]
  87. Magnusdottir, S. , Fillmore, P. , den Ouden, D.B. , Hjaltason, H. , Rorden, C. , Kjartansson, O. , Bonilha, L. , & Fridriksson, J
    (2013) Damage to left anterior temporal cortex predicts impairment of complex syntactic processing: A lesion‐symptom mapping study. Human Brain Mapping, 34, 2715–2723. doi: 10.1002/hbm.22096
     https://doi.org/10.1002/hbm.22096 [Google Scholar]
  88. Makuuchi, M. , Bahlmann, J. , Anwander, A. , & Friederici, A.D.
    (2009) Segregating the core computational faculty of human language from working memory. Proceedings of the National Academy of Sciences , 106, 8362–8367.
     [Google Scholar]
  89. Makuuchi, M. , & Friederici, A.D.
    (2013) Hierarchical functional connectivity between the core language system and the working memory system. Cortex, 49, 2416–2423. doi: 10.1016/j.cortex.2013.01.007
     https://doi.org/10.1016/j.cortex.2013.01.007 [Google Scholar]
  90. Marantz, A
    (2005) Generative linguistics within the cognitive neuroscience of language. The Linguistic Review, 22, 429–445. doi: 10.1515/tlir.2005.22.2‑4.429
     https://doi.org/10.1515/tlir.2005.22.2-4.429 [Google Scholar]
  91. Marchini, J. , Heaton, C. , & Ripley, B
    (2012) fastICA: FastICA Algorithms to perform ICA and Projection Pursuit (R package version 1.1-16).
     [Google Scholar]
  92. Marek, A. , Habets, B. , Jansma, B.M. , Nager, W. , & Muente, T.F.
    (2007) Neural correlates of conceptualisation difficulty during the preparation of complex utterances. Aphasiology, 21, 1147–1156. doi: 10.1080/02687030600646577
     https://doi.org/10.1080/02687030600646577 [Google Scholar]
  93. Martin, N. , Weisberg, R. , & Saffran, E
    (1989) Variables influencing the occurrence of naming errors – implications for models of lexical retrieval. Journal of Memory and Language, 28, 462–485. doi: 10.1016/0749‑596X(89)90022‑3
     https://doi.org/10.1016/0749-596X(89)90022-3 [Google Scholar]
  94. Mei, L. , Xue, G. , Lu, Z-L. , He, Q. , Zhang, M ., et al
    (2014) Artificial language training reveals the neural substrates underlying addressed and assembled phonologies. PLoS ONE, 9, e93548. doi: 10.1371/journal.pone.0093548
     https://doi.org/10.1371/journal.pone.0093548 [Google Scholar]
  95. Mesulam, M.M.
    (1998) From sensation to cognition. Brain, 121, 1013–1052. doi: 10.1093/brain/121.6.1013
     https://doi.org/10.1093/brain/121.6.1013 [Google Scholar]
  96. Mesulam, M. , Rogalski, E. , Wieneke, C. , Cobia, D. , Rademaker, A. , Thompson, C. , & Weintraub, S
    (2009) Neurology of anomia in the semantic variant of primary progressive aphasia. Brain, awp138, 132(9), 2553–2565. doi: 10.1093/brain/awp138
     https://doi.org/10.1093/brain/awp138 [Google Scholar]
  97. Mesulam, M.M. , Wieneke, C. , Hurley, R. , Rademaker, A. , Thompson, C.K. , Weintraub, S. , & Rogalski, E.J.
    (2013) Words and objects at the tip of the left temporal lobe in primary progressive aphasia. Brain, 136, 601–618. doi: 10.1093/brain/aws336
     https://doi.org/10.1093/brain/aws336 [Google Scholar]
  98. Meyer, C.F. , Grabowski, R. , Han, H.-Y. , Mantzouranis, K. , & Moses, S
    (2003) The world wide web as linguistic corpus. In P. Leistyna & C.F. Meyer (Eds.), Language and computers, corpus analysis: Language structure and language use (pp. 241–254). Amsterdam: Rodopi.
     [Google Scholar]
  99. Mion, M. , Patterson, K. , Acosta-Cabronero, J. , Pengas, G. , Izquierdo-Garcia, D. , Hong, Y.T. , Fryer, T.D. , Williams, G.B. , Hodges, J.R. , & Nestor, P.J.
    (2010) What the left and right anterior fusiform gyri tell us about semantic memory. Brain, 133, 3256–3268. doi: 10.1093/brain/awq272
     https://doi.org/10.1093/brain/awq272 [Google Scholar]
  100. Motulsky, H. , & Christopoulos, A
    (2004) Fitting models to biological data using linear and non-linear regression. A practical guide to curve fitting. Oxford, UK: Oxford University Press.
     [Google Scholar]
  101. Newman, A.J. , Supalla, T. , Hauser, P. , Newport, E.L. , & Bavelier, D
    (2010) Dissociating neural subsystems for grammar by contrasting word order and inflection. Proceedings of the National Academy of Sciences , 107, 7539–7544.
     [Google Scholar]
  102. Noonan, K.A. , Jefferies, E. , Visser, M. , & Lambon Ralph, M.A
    (2013) Going beyond inferior prefrontal involvement in semantic control: evidence for the additional contribution of dorsal angular gyrus and posterior middle temporal cortex. Journal of Cognitive Neuroscience, 25:1824–1850. doi: 10.1162/jocn_a_00442
     https://doi.org/10.1162/jocn_a_00442 [Google Scholar]
  103. Noppeney, U. , & Price, C.J.
    (2004) An fMRI study of syntactic adaptation. Journal of Cognitive Neuroscience, 16, 702–713. doi: 10.1162/089892904323057399
     https://doi.org/10.1162/089892904323057399 [Google Scholar]
  104. Okada, K. , & Hickok, G
    (2006) Left posterior auditory-related cortices participate both in speech perception and speech production: Neural overlap revealed by fMRI. Brain and Language, 96, 112–117. doi: 10.1016/j.bandl.2006.04.006
     https://doi.org/10.1016/j.bandl.2006.04.006 [Google Scholar]
  105. Oomen, C. , & Postma, A
    (2001) Effects of time pressure on mechanisms of speech production and self-monitoring. Journal of Psycholinguistic Research, 30, 163–184. doi: 10.1023/A:1010377828778
     https://doi.org/10.1023/A:1010377828778 [Google Scholar]
  106. Patterson, K. , Nestor, P.J. , & Rogers, T.T.
    (2007) Where do you know what you know? The representation of semantic knowledge in the human brain. Nature Reviews Neuroscience, 8, 976–987. doi: 10.1038/nrn2277
     https://doi.org/10.1038/nrn2277 [Google Scholar]
  107. Price, C
    (2010) The anatomy of language: A review of 100 fMRI studies published in 2009. Annals of the New York Academy of Sciences: The Year in Cognitive Neuroscience, 1191, 62–88. doi: 10.1111/j.1749‑6632.2010.05444.x
     https://doi.org/10.1111/j.1749-6632.2010.05444.x [Google Scholar]
  108. (2012) A review and synthesis of the first 20 years of PET and fMRI studies of heard speech, spoken language and reading. NeuroImage, 15, 816–847. doi: 10.1016/j.neuroimage.2012.04.062
     https://doi.org/10.1016/j.neuroimage.2012.04.062 [Google Scholar]
  109. Pylkkänen, L. , Stringfellow, A. , Flagg, E. , & Marantz, A
    (2000) A neural response sensitive to repetition and phonotactic probability: MEG investigations of lexical access. In Proceedings of Biomag (pp. 363–367).
     [Google Scholar]
  110. Pylkkänen, L. , Stringfellow, A. , & Marantz, A
    (2002) Neuromagnetic evidence for the timing of lexical activation: An MEG component sensitive to phonotactic probability but not to neighborhood density. Brain and Language, 81, 666–678. doi: 10.1006/brln.2001.2555
     https://doi.org/10.1006/brln.2001.2555 [Google Scholar]
  111. Pylkkanen, L. , & Marantz, A
    (2003) Tracking the time course of word recognition with meg. Trends in Cognitive Sciences, 7, 187–189. doi: 10.1016/S1364‑6613(03)00092‑5
     https://doi.org/10.1016/S1364-6613(03)00092-5 [Google Scholar]
  112. Pylkkänen, L. , Feintuch, S. , Hopkins, E. , & Marantz, A
    (2004) Neural correlates of the effects of morphological family frequency and family size: An MEG study. Cognition, 91, B35–B45. doi: 10.1016/j.cognition.2003.09.008
     https://doi.org/10.1016/j.cognition.2003.09.008 [Google Scholar]
  113. Rauschecker, J.P. , & Scott, S.K.
    (2009) Maps and streams in the auditory cortex: Nonhuman primates illuminate human speech processing. Nature Neuroscience, 12, 718–724. doi: 10.1038/nn.2331
     https://doi.org/10.1038/nn.2331 [Google Scholar]
  114. R Development Core Team
    (2012) R: A language and environment for statistical computing. Vienna, Austria (ISBN 3-900051-07-0).
     [Google Scholar]
  115. Roelofs, A. , Meyer, A.S. , & Levelt, W.J.
    (1998) A case for the lemma/lexeme distinction in models of speaking: Comment on Caramazza and Miozzo (1997). Cognition, 69(2), 219–230. doi: 10.1016/S0010‑0277(98)00056‑0
     https://doi.org/10.1016/S0010-0277(98)00056-0 [Google Scholar]
  116. Saur, D. , Kreher, B.W. , Schnell, S. , Kümmerer, D. , Kellmeyer, P. , Vry, M.S. , Umarova, R. , Musso, M. , Glauche, V. , Abel, S. , Huber, W. , Rijntjes, M. , Hennig, J. , & Weiller, C
    (2008) Ventral and dorsal pathways for language. Proceedings of the National Academy of Sciences , 105, 18035–18040.
     [Google Scholar]
  117. Segaert, K. , Kempen, G. , Petersson, K.M. , & Hagoort, P
    (2013) Syntactic priming and the lexical boost effect during sentence production and sentence comprehension: An fMRI study. Brain and Language, 124(2), 174–183. doi: 10.1016/j.bandl.2012.12.003
     https://doi.org/10.1016/j.bandl.2012.12.003 [Google Scholar]
  118. Schwartz, M.F. , Kimberg, D.Y. , Walker, G.M. , Faseyitan, O. , Brecher, A. , Dell, G.S. , & Coslett, H.B.
    (2009) Anterior temporal involvement in semantic word retrieval: VLSM evidence from aphasia. Brain, 132, 3411–3427. doi: 10.1093/brain/awp284
     https://doi.org/10.1093/brain/awp284 [Google Scholar]
  119. Sekiguchi, T. , Koyama, S. , & Kakigi, R
    (2000) The effect of word repetition on evoked magnetic responses in the human brain. Japanese Psychological Research, 42(1), 3–14. doi: 10.1111/1468‑5884.00126
     https://doi.org/10.1111/1468-5884.00126 [Google Scholar]
  120. Simon, D.A. , Lewis, G. , & Marantz, A
    (2012) Disambiguating form and lexical frequency effects in MEG responses using homonyms. Language and Cognitive Processes, 27, 275–287. doi: 10.1080/01690965.2011.607712
     https://doi.org/10.1080/01690965.2011.607712 [Google Scholar]
  121. Siyanova-Chanturia, A. , Conklin, K. , & Heuven, W.J.van
    (2011) Seeing a phrase “time and again” matters: The role of phrasal frequency in the processing of multiword sequences. Journal of Experimental Psychology: Learning, Memory, and Cognition, 37, 776–784. doi: 10.1037/a0022531
     https://doi.org/10.1037/a0022531 [Google Scholar]
  122. Solomyak, O. , & Marantz, A
    (2009) Lexical access in early stages of visual word processing: A single-trial correlational MEG study of heteronym recognition. Brain and Language, 108, 191–196. doi: 10.1016/j.bandl.2008.09.004
     https://doi.org/10.1016/j.bandl.2008.09.004 [Google Scholar]
  123. Sosa, A.V. , & MacFarlane, J
    (2002) Evidence for frequency-based constituents in the mental lexicon: Collocations involving the word of. Brain and Language, 82, 227–236. doi: 10.1016/S0093‑934X(02)00032‑9
     https://doi.org/10.1016/S0093-934X(02)00032-9 [Google Scholar]
  124. Taulu, S. , & Simola, J
    (2006) Spatiotemporal signal space separation method for rejecting nearby interference in MEG measurements. Physics in Medicine and Biology, 51, 1759–1768. doi: 10.1088/0031‑9155/51/7/008
     https://doi.org/10.1088/0031-9155/51/7/008 [Google Scholar]
  125. Thelwall, M. , & Sud, P
    (2012) Webometrics research with the Bing Search API 2.0. Journal of Informetrics, 6, 44–52. doi: 10.1016/j.joi.2011.10.002
     https://doi.org/10.1016/j.joi.2011.10.002 [Google Scholar]
  126. Tremblay, A
    (2009) Processing advantages of lexical bundles: Evidence from self-paced reading, word and sentence recall, and free recall with event-related brain potential recordings. PhD dissertation. University of Alberta.
     [Google Scholar]
  127. (2013) icaOcularCorrection: Independent components analysis (ICA) based eye-movement correction (R package version 2.4.3.5.1 alpha – pre-release).
     [Google Scholar]
  128. Tremblay, A. , & Baayen, R.H.
    (2010) Holistic processing of regular four-word sequences: A behavioral and ERP study of the effects of structure, frequency, and probability on immediate free recall. In D. Wood (Ed.), Perspectives on formulaic language: Acquisition and communication (pp. 151–173). London and New York: Continuum.
     [Google Scholar]
  129. Tremblay, A. , Derwing, B. , Libben, G. , & Westbury, C
    (2011) Processing advantages of lexical bundles: Evidence from self-paced reading and sentence recall tasks. Language Learning, 61, 569–613. doi: 10.1111/j.1467‑9922.2010.00622.x
     https://doi.org/10.1111/j.1467-9922.2010.00622.x [Google Scholar]
  130. Tremblay, A. , & Tucker, B.V.
    (2011) The effects of N-gram probabilistic measures on the recognition and production of four-word sequences. The Mental Lexicon, 6, 302–324. doi: 10.1075/ml.6.2.04tre
     https://doi.org/10.1075/ml.6.2.04tre [Google Scholar]
  131. Tremblay, A. & Newman, A.J.
    (2015) Modeling non-linear relationships in ERP data using mixed-effects regression with R examples. Psychophysiology, 1–16. doi: 10.1111/psyp.12299
     https://doi.org/10.1111/psyp.12299 [Google Scholar]
  132. Troyer, M. , O’Donnell, T.J. , Fedorenko, E. , & Gibson, E
    (2011) In N.A. Taatgen & H. van Rijn (Eds.), Proceedings of the 33rd Annual Conference of the Cognitive Science Society (pp.336–341). Austin, TX: Cognitive Science Society.
     [Google Scholar]
  133. Tyler, L.K. , Marslen-Wilson, W.D. , Randall, B. , Wright, P. , Devereux, B.J. , Zhuang, J. , Papoutsi, M. , & Stamatakis, E.A.
    (2011) Left inferior frontal cortex and syntax: function, structure and behaviour in patients with left hemisphere damage. Brain, 134, 415–431. doi: 10.1093/brain/awq369
     https://doi.org/10.1093/brain/awq369 [Google Scholar]
  134. Ullman, M
    (2007) The biocognition of the mental lexicon. In M.G. Gaskell (Ed.), The Oxford handbook of psycholinguistics (pp.267–286). Oxford: Oxford University Press.
    [Google Scholar]
  135. Underwood, G. , Schmitt, N. , & Galpin, A
    (2004) The eyes have it. An eye-movement study into the processing of formulaic sequences. In N. Schmitt (Ed.), Formulaic sequences. Acquisition, processing and use (pp. 153–172). Amsterdam: John Benjamins. doi: 10.1075/lllt.9.09und
     https://doi.org/10.1075/lllt.9.09und [Google Scholar]
  136. Vigneau, M. , Beaucousin, V. , Herve, P. , Duffau, H. , Crivello, F. , & Houde, O
    (2006) Meta-analyzing left hemisphere language areas: Phonology, semantics, and sentence processing. NeuroImage, 30, 1414–1432. doi: 10.1016/j.neuroimage.2005.11.002
     https://doi.org/10.1016/j.neuroimage.2005.11.002 [Google Scholar]
  137. Visser, M. , & Ralph, M.L.
    (2011) Differential contributions of bilateral ventral anterior temporal lobe and left anterior superior temporal gyrus to semantic processes. Journal of Cognitive Neuroscience, 23, 3121–3131. doi: 10.1162/jocn_a_00007
     https://doi.org/10.1162/jocn_a_00007 [Google Scholar]
  138. Vrba, J. , Taulu, S. , Nenonen, J. , & Ahonen, A
    (2010) Signal space separation beamformer. Brain Topography, 23, 128–133. doi: 10.1007/s10548‑009‑0120‑7
     https://doi.org/10.1007/s10548-009-0120-7 [Google Scholar]
  139. Walker, G.M. , Schwartz, M.F. , Kimberg, D.Y. , Faseyitan, O. , Brecher, A. , Dell, G.S. , & Coslett, H.B.
    (2011) Support for anterior temporal involvement in semantic error production in aphasia: New evidence from VLSM. Brain and Language, 117, 110–122. doi: 10.1016/j.bandl.2010.09.008
     https://doi.org/10.1016/j.bandl.2010.09.008 [Google Scholar]
  140. Westerlund, M. , & Pylkkänen, L
    (2014) The role of the left anterior temporal lobe in semantic composition vs. semantic memory. Neuropsychologia, 57, 59–70. doi: 10.1016/j.neuropsychologia.2014.03.001
     https://doi.org/10.1016/j.neuropsychologia.2014.03.001 [Google Scholar]
  141. Willems, R.M. , Özyürek, A. , & Hagoort, P
    (2009) Differential roles for left inferior frontal and superior temporal cortex in multimodal integration of action and language. NeuroImage, 47, 1992–2004. doi: 10.1016/j.neuroimage.2009.05.066
     https://doi.org/10.1016/j.neuroimage.2009.05.066 [Google Scholar]
  142. Wilson, S.M. , Demarco, A.T. , Henry, M.L. , Gesierich, B. , Babiak, M. , Mandelli, M.L. , Miller, B.L. , & Gorno-Tempini, M.L
    (2014) What role does the anterior temporal lobe play in sentence-level processing? Neural correlates of syntactic processing in semantic variant primary progressive Aphasia. Journal of Cognitive Neuroscience, 26, 970. doi: 10.1162/jocn_a_00550
     https://doi.org/10.1162/jocn_a_00550 [Google Scholar]
  143. Wood, S.N
    (2006) Generalized additive models. New York, NY: Chapman & Hall/CRC.
     [Google Scholar]
  144. Wood, S.N.
    (2012) mgcv: Mixed GAM Computation Vehicle with GCV/AIC/REML Smoothness Estimation (R package version 1.7-22).
     [Google Scholar]
  145. Zhang, L. , Xi, J. , Xu, G. , Shu, H. , Wang, X. , & Li, P
    (2011) Cortical dynamics of acoustic and phonological processing in speech perception. PloS One, 6, e20963. doi: 10.1371/journal.pone.0020963
     https://doi.org/10.1371/journal.pone.0020963 [Google Scholar]
  146. Zuur, A.F. , Ieno, E.N. , Walker, N.J. , Saveliev, A.A. , & Smith, G.M.
    (2009) Mixed effects models and extensions in ecology with R. New York, NY: Springer. doi: 10.1007/978‑0‑387‑87458‑6
     https://doi.org/10.1007/978-0-387-87458-6 [Google Scholar]
/content/journals/10.1075/ml.11.1.06tre
Loading
  • Article Type: Research Article
Keyword(s): generalized additive mixed-effects modelling (GAMM); magneto-encephalogram (MEG); N-gram frequency; scene description; serial/parallel processing

Most Cited

This is a required field
Please enter a valid email address
Approval was successful
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error