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Forward models and their implications for production, comprehension, and dialogue

Published online by Cambridge University Press:  24 June 2013

Martin J. Pickering
Affiliation:
Department of Psychology, University of Edinburgh, Edinburgh EH8 9JZ, United Kingdom. martin.pickering@ed.ac.ukhttp://www.psy.ed.ac.uk/Staff/academics.html#PickeringMartin
Simon Garrod
Affiliation:
University of Glasgow, Institute of Neuroscience and Psychology, Glasgow G12 8QT, United Kingdom. simon@psy.gla.ac.ukhttp://staff.psy.gla.ac.uk/~simon/

Abstract

Our target article proposed that language production and comprehension are interwoven, with speakers making predictions of their own utterances and comprehenders making predictions of other people's utterances at different linguistic levels. Here, we respond to comments about such issues as cognitive architecture and its neural basis, learning and development, monitoring, the nature of forward models, communicative intentions, and dialogue.

Type
Authors' Response
Copyright
Copyright © Cambridge University Press 2013 

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References

Adank, P., Hagoort, P. & Bekkering, H. (2010) Imitation improves language comprehension. Psychological Science 21:1903–909.CrossRefGoogle ScholarPubMed
Barsalou, L. (1999) Perceptual symbol systems. Behavioral and Brain Sciences 22:577600.Google Scholar
D'Ausilio, A., Jarmolowska, J., Busan, P., Bufalari, I. & Craighero, L. (2011) Tongue corticospinal modulation during attended verbal stimuli: Priming and coarticulation effects. Neuropsychologia 49:3670–76.Google Scholar
Dahan, D., Drucker, S. J. & Scarborough, R. A. (2008) Talker adaptation in speech perception: Adjusting the signal or the representations? Cognition 108:710–18.CrossRefGoogle ScholarPubMed
De Ruiter, J. P., Mitterer, H. & Enfield, N. J. (2006) Predicting the end of a speaker's turn; a cognitive cornerstone of conversation. Language 82(3):515–35.CrossRefGoogle Scholar
Dell, G. S. (1986) A spreading-activation theory of retrieval in sentence production. Psychological Review 93:283321.Google Scholar
DeLong, K. A., Urbach, T. P. & Kutas, M. (2005) Probabilistic word pre-activation during language comprehension inferred from electrical brain activity. Nature Neuroscience 8(8):1117–21.Google Scholar
Flinker, A., Chang, E. F., Kirsch, H. E., Barbaro, N. M., Crone, N. E. & Knight, R.T. (2010) Single-trial speech suppression of auditory cortex activity in humans. Journal of Neuroscience 30:16643–50.Google Scholar
Glenberg, A. M. & Gallese, V. (2012) Action-based language: A theory of language acquisition, comprehension, and production. Cortex 48(7):905–22. DOI:10.1016/j.cortex.2011.04.010.CrossRefGoogle Scholar
Grossberg, S. (1980) How does a brain build a cognitive code? Psychological Review 87(1):151.Google Scholar
Heinks-Maldonado, T. H., Nagarajan, S. S. & Houde, J. F. (2006) Magnetoencephalographic evidence for a precise forward model in speech production. NeuroReport 17(13):1375–79.Google Scholar
Huettig, F. & Hartsuiker, R. J. (2010) Listening to yourself is like listening to others: External, but not internal, verbal self-monitoring is based on speech perception. Language and Cognitive Processes 25:347–74.CrossRefGoogle Scholar
Hurley, S. (2008a) The shared circuits model (SCM): How control, mirroring, and simulation can enable imitation, deliberation, and mindreading. Behavioral and Brain Sciences 31(01):122.Google Scholar
Jordan, M. I. & Rumelhart, D. E. (1992) Forward models: Supervised learning with a distal teacher. Cognitive Science, 16: 307–54.Google Scholar
Kawato, M., Furawaka, K. & Suzuki, R. (1987) A hierarchical neural network model for the control and learning of voluntary movements. Biological Cybernetics 56: 117.Google Scholar
Kawato, M., Maeda, Y., Uno, Y. & Suzuki, R. (1990) Trajectory formation of arm movement by cascade neural network model based on minimum torque-change criterion. Biological Cybernetics, 62: 275–88.CrossRefGoogle ScholarPubMed
Lesage, E., Morgan, B. E., Olson, A. C., Meyer, A. S. & Miall, R. C. (2012) Cerebellar rTMS disrupts predictive language processing. Current Biology 22, R794–95.CrossRefGoogle ScholarPubMed
Levelt, W. J. M. (1989) Speaking: From intention to articulation. MIT Press.Google Scholar
Mani, N. & Huettig, F. (2012) Prediction during language processing is a piece of cake – but only for skilled producers. Journal of Experimental Psychology: Human Perception and Performance 38: 843–47.Google Scholar
Miall, R. C. & Wolpert, D. M. (1996) Forward models for physiological motor control. Neural Networks 9: 1265–79.Google Scholar
Nozari, N., Dell, G. S. & Schwartz, M. F. (2011) Is comprehension necessary for error detection? A conflict-based account of monitoring in speech production. Cognitive Psychology 63(1):133. DOI:10.1016/j.cogpsych.2011.05.001.CrossRefGoogle ScholarPubMed
Ondobaka, S., de Lange, F. P., Newman-Norlund, R. D., Wiemers, M. & Bekkering, H. (2011) Interplay between action and movement intentions during social interaction. Psychological Science 23: 3035.Google Scholar
Pezzulo, G. (2011a) Grounding procedural and declarative knowledge in sensorimotor anticipation. Mind and Language 26:78114.Google Scholar
Pickering, M. J. & Garrod, S. (2004) Toward a mechanistic psychology of dialogue. Behavioral and Brain Sciences 27(2):169226.Google Scholar
Tremblay, S., Shiller, D. M. & Ostry, D. J. (2003) Somatosensory basis of speech production. Nature 423: 866–69.CrossRefGoogle ScholarPubMed
Trude, A. M. & Brown-Schmidt, S. (2012) Talker-specific perceptual adaptation during on-line speech perception. Language and Cognitive Processes 27: 9791001.Google Scholar
Wolpert, D. M., Ghahramani, Z. & Flanagan, J. R. (2001) Perspectives and problems in motor learning. Trends in Cognitive Sciences 5:487–94.Google Scholar