Cover not available
Part of
Experiencing Fictional Worlds
Edited by Benedict Neurohr and Lizzie Stewart-Shaw
[Linguistic Approaches to Literature 32] 2019
► pp. 33–52

Chapter 3
A predictive coding approach to Text World Theory

Text World Theory offers a beneficial tool for the analysis of texts and the structures of fictional worlds. A significant and fascinating topic is the cognitive and psychological reality behind the text-world structures identified by an expert researcher of literature and if they are experienced when read by a given individual for pleasure. Using a neurological model of perceptual processing called Predictive Coding, this chapter sets out to examine how a text might be processed in real time by a reader. This process must also be sensitive to readers’ prior knowledge in keeping with Text World Theory, and whether it is the first time the text is read or not. It will be shown that while the analyses provided by Text World Theory are valid and useful for describing fictional constructions, it is possible to be even more precise when describing the formation of text-worlds in a real-time reading process.
Keywords: Text World Theory, Predictive Coding, predictive model, error signal, processing, cognitive linguistics
Article outline
  • 3.1Introduction
  • 3.2Predictive Coding
  • 3.3Predictive Coding, texts and text-worlds
  • 3.4A text-world analysis
  • 3.5A Predictive Coding analysis
  • 3.6Conclusion
  • References
Published online: 21 February 2019
DOI logo
https://doi.org/10.1075/lal.32.03neu
References (25)
References
Clark, A. 2013. Whatever next? Predictive brains, situated agents, and the future of cognitive science. Behavioral and Brain Science 36(3): 181–204. DOI logoGoogle Scholar
Croft, W., Cruse, D. A. 2004. Cognitive Linguistics. New York: Cambridge University Press. DOI logoGoogle Scholar
Egner, T., Monti, J. M., and Summerfield, C. 2010. Expectation and Surprise Determine Neural Population Responses in the Ventral Visual Stream. Journal of Neuroscience 30(49): 16601–16608. DOI logoGoogle Scholar
Friston, K. 2005. A theory of cortical responses. Philosophical Transactions of the Royal Society B Biological Sciences 360(1521): 815–836. DOI logoGoogle Scholar
2002. Beyond Phrenology: What Can Neuroimaging Tell Us About Distributed Circuitry? Annual Review of Neuroscience 25(1): 221–250. DOI logoGoogle Scholar
Garrod, S., Gambi, C. and Pickering, M. J. 2014. Prediction at all levels: forward model predictions can enhance comprehension. Language, Cognition and Neuroscience 29(1): 46–48. DOI logoGoogle Scholar
Gavins, J. 2007. Text World Theory: An Introduction. Edinburgh: Edinburgh University Press. DOI logoGoogle Scholar
Halliday, M. A. K. and Matthiessen, C. M. I. M. 2013. Halliday’s Introduction to Functional Grammar. 4th edn. London: Routledge. DOI logoGoogle Scholar
von Helmholtz, H. 1962. Helmholtz’s Treatise on Physiological Optics, Volume 3, J. P. C. James P. C. Southall (ed). New York: Dover.Google Scholar
Hohwy, J. 2007. Functional Integration and the Mind. Synthese 159(3): 315–328. DOI logoGoogle Scholar
Hohwy, J., Roepstorff, A., and Friston, K. 2008. Predictive coding explains binocular rivalry: An epistemological review. Cognition 108(3): 687–701. DOI logoGoogle Scholar
Jack, B. N. and Hacker, G. 2014. Predictive Coding Explains Auditory and Tactile Influences on Vision during Binocular Rivalry. Journal of Neuroscience. 34(19): 6423–6424. DOI logoGoogle Scholar
Lahey, E. 2004. All the World’s a Subworld: Direct Speech and Subworld Creation in ‘After’ by Norman MacCaig. Nottingham Linguistic Circular 18: 21–28.Google Scholar
Langacker, R. W. 2009. Investigations in Cognitive Grammar. Berlin: Mouton de Gruyter. DOI logoGoogle Scholar
1986. An Introduction to Cognitive Grammar. Cognitive Science 10: 1–40. DOI logoGoogle Scholar
Lewis, D. 1973. Causation. The Journal of Philosophy 70(17): 556–567. DOI logoGoogle Scholar
Park, H.-J. and Friston, K. 2013. Structural and Functional Brain Networks: From Connections to Cognition. Science 342: 1238411. DOI logoGoogle Scholar
Rahnev, D., Lau, H. and de Lange, F. P. 2011. Prior Expectation Modulates the Interaction between Sensory and Prefrontal Regions in the Human Brain. Journal of Neuroscience 31(29): 10741–10748. DOI logoGoogle Scholar
Rescher, N. 1999. How Many Possible Worlds Are There? Philosophy and Phenomenological Research 59: 403–420. DOI logoGoogle Scholar
Sanderson, B. 2014. Words of Radiance: The Stormlight Archive Book Two. London: Gollancz.Google Scholar
Sanford, A. J. and Emmott, C. 2012. Mind, Brain and Narrative. Cambridge: Cambridge University Press. DOI logoGoogle Scholar
Squire, L. R. (ed). 2008. Fundamental Neuroscience. 3rd edn. Burlington, MA; London: Academic Press.Google Scholar
Summerfield, C., Trittschuh, E. H., Monti, J. M., Mesulam, M.-M. and Egner, T. 2008. Neural repetition suppression reflects fulfilled perceptual expectations. Nature Neuroscience 11(9): 1004–1006. DOI logoGoogle Scholar
Werth, P. 1999. Text Worlds: Representing Conceptual Space in Discourse. London: Longman.Google Scholar
Zwaan, R. A. 1994. Effect of Genre Expectations on Text Comprehension. Journal of Experimental Psychology 20(4): 920–933.Google Scholar
Cited by (2)

Cited by two other publications

Norledge, Jessica
2020. BuildingThe Ark: Text World Theory and the evolution of dystopian epistolary. Language and Literature: International Journal of Stylistics 29:1 ► pp. 3 ff. DOI logo
Statham, Simon
2020. The year’s work in stylistics 2019. Language and Literature: International Journal of Stylistics 29:4 ► pp. 454 ff. DOI logo

This list is based on CrossRef data as of 26 june 2024. Please note that it may not be complete. Sources presented here have been supplied by the respective publishers. Any errors therein should be reported to them.