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Can structural priming answer the important questions about language?

Published online by Cambridge University Press:  10 November 2017

Andrea E. Martin
Affiliation:
Max Planck Institute for Psycholinguistics, 6525 XD Nijmegen, Netherlands. [email protected]@[email protected]://sites.google.com/site/aemn1011/http://www.mpi.nl/people/huettig-falkhttp://www.mpi.nl/people/nieuwland-mante School of Philosophy, Psychology, and Language Sciences, University of Edinburgh, Edinburgh EH8 9JZ, United Kingdom.
Falk Huettig
Affiliation:
Max Planck Institute for Psycholinguistics, 6525 XD Nijmegen, Netherlands. [email protected]@[email protected]://sites.google.com/site/aemn1011/http://www.mpi.nl/people/huettig-falkhttp://www.mpi.nl/people/nieuwland-mante
Mante S. Nieuwland
Affiliation:
Max Planck Institute for Psycholinguistics, 6525 XD Nijmegen, Netherlands. [email protected]@[email protected]://sites.google.com/site/aemn1011/http://www.mpi.nl/people/huettig-falkhttp://www.mpi.nl/people/nieuwland-mante

Abstract

Structural priming makes a valuable contribution to psycholinguistics, but it taps into implicit memory representations and processes that may differ from what is deployed during online language processing. As a result, the strength of inductive inference regarding linguistic representation is rather limited. We question whether implicit memory for language can and should be equated with linguistic representation or with language processing.

Type
Open Peer Commentary
Copyright
Copyright © Cambridge University Press 2017 

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References

Hagoort, P. (2014) Nodes and networks in the neural architecture for language: Broca's region and beyond. Current Opinion in Neurobiology 28:136–41. doi:10.1016/j.conb.2014.07.013.CrossRefGoogle ScholarPubMed
King, J. R. & Dehaene, S. (2014) Characterizing the dynamics of mental representations: the temporal generalization method. Trends in Cognitive Sciences 18(4):203–10.CrossRefGoogle ScholarPubMed
Macmillan, N. A. & Creelman, C. D. (2004) Detection theory: A user's guide. Psychology Press.CrossRefGoogle Scholar
Martin, A. E. (2016) Language processing as cue integration: Grounding the psychology of language in perception and neurophysiology. Frontiers in Psychology 7:117.CrossRefGoogle ScholarPubMed
Martin, A. E., & Doumas, L. A. A. (2017) A mechanism for the cortical computation of hierarchical linguistic structure. PLoS Biology 15(3):e2000663.CrossRefGoogle ScholarPubMed
McElree, B. (2006) Accessing recent events. Psychology of Learning and Motivation 46:155200.CrossRefGoogle Scholar
Nieuwland, M. S., Martin, A. E. & Carreiras, M. (2013) Event-related brain potential evidence for animacy processing asymmetries during sentence comprehension. Brain and Language 126(2):151–58. doi:10.1016/j.bandl.2013.04.005.CrossRefGoogle ScholarPubMed
Reed, A. V. (1973) Speed-accuracy trade-off in recognition memory. Science 181(4099):574–76.CrossRefGoogle ScholarPubMed
Skipper, J. I. (2015) The NOLB model: A model of the natural organization of language and the brain. Cognitive Neuroscience of Natural Language Use 101–34.CrossRefGoogle Scholar