Article published In: Narrative Inquiry
Vol. 25:1 (2015) ► pp.22–36
Literary narrative as a cognitive structure in the brain
Published online: 19 February 2016
https://doi.org/10.1075/ni.25.1.02gar
https://doi.org/10.1075/ni.25.1.02gar
This paper proposes that literary narrative is the result of an unconscious computation in the brain, a computation that arises from the dynamical interaction of specific innate and representational lower-order neuronal circuits and mappings. It is also proposed that these specific circuits constitute the fundamental building blocks of literary narrative. The analysis further suggests that as literary narrative evolves in the brain, its development is influenced by an evolutionarily-biased broad class of attractors known as archetypes. In this context, a description of literary narrative is devised, and six phases leading to the production of literary narrative are then identified. The description presented here may have applications in the production of literary narrative by artificial systems.
References (51)
Bargh, J.A., & Morsella, E. (2008). The unconscious mind. Perspectives on psychological science, 3(1), 73–79.
Barsalou, L.W. (2009). Simulation, situated conceptualization, and prediction. Philosophical Transactions of the Royal Society B: Biological Sciences, 364(1521), 1281–1289.
. (2010). Grounded cognition: Past, present, and future. Topics in Cognitive Science, 2(4), 716–724.
Başar, E. (2009). S-matrix and Feynman space-time diagrams to quantum brain approach. An extended proposal. Neuro Quantology, 7(1), 30–45.
Bullmore, E., & Sporns, O. (2012). The economy of brain network organization. Nature Reviews Neuroscience, 13(5), 336–349.
Camazine, S. (2003). Self-organization in biological systems. Princeton, NJ: Princeton University Press.
De Wolf, T., & Holvoet, T. (2004). Emergence and self-organisation: A statement of similarities and differences. Engineering Self-Organising Systems, 34641, 1–15.
Deco, G., Jirsa, V.K., & McIntosh, A.R. (2010). Emerging concepts for the dynamical organization of resting-state activity in the brain. Nature Reviews Neuroscience, 12(1), 43–56.
Edelman, G.M. (2003). Naturalizing consciousness: A theoretical framework.
Proceedings of the National Academy of Sciences
, 100(9), 5520–5524.
Flusberg, S.J., Thibodeau, P.H., Sternberg, D.A., & Glick, J.J. (2010). A connectionist approach to embodied conceptual metaphor. Embodied and Grounded Cognition, 1(197), 142.
. (2008). A pseudo-equilibrium thermodynamic model of information processing in nonlinear brain dynamics. Neural Networks, 21(2), 257–265.
Freeman, W.J., & Vitiello, G. (2008). The dissipative quantum model of brain and laboratory observations. In I. Licata & A. Sakaji (A cura di) Physics of Emergence and Organization (pp. 233–251). Singapore: World Scientific Publishing.
Friston, K. (2010). The free-energy principle: A unified brain theory? Nature Reviews Neuroscience, 11(2), 127–138.
Gervás, P., Lönneker-Rodman, B., Meister, J.C., & Peinado, F. (2006, May). Narrative models: Narratology meets artificial intelligence. In
International Conference on Language Resources and Evaluation. Satellite Workshop: Toward Computational Models of Literary Analysis
(pp. 44–51).
Hannula, D.E., & Greene, A.J. (2012). The hippocampus reevaluated in unconscious learning and memory: At a tipping point? Frontiers in Human Neuroscience, 6, 80.
Henke, K. (2010). A model for memory systems based on processing modes rather than consciousness. Nature Reviews Neuroscience, 11(7), 523–532.
Hopfield, J.J., & Tank, D.W. (1986). Computing with neural circuits - A model. Science, 233(4764), 625–633.
Hopfield, J.J. (1982). Neural networks and physical systems with emergent collective computational abilities.
Proceedings of the National Academy of Sciences
, 79(8), 2554–2558.
Jaeger, H.M., & Liu, A.J. (2010). Far-from-equilibrium physics: An overview. arXiv preprint arXiv:10091.4874.
Johnson, B.R., & Lam, S.K. (2010). Self-organization, natural selection, and evolution: Cellular hardware and genetic software. BioScience, 60(11), 879–885.
Karsenti, E. (2008). Self-organization in cell biology: A brief history. Nature Reviews Molecular Cell Biology, 9(3), 255–262.
Kent, C., & Lamberts, K. (2008). The encoding–retrieval relationship: Retrieval as mental simulation. Trends in Cognitive Sciences, 12(3), 92–98.
Klm, I.J. (1995). Topographical representations of mental images in primary visual cortex. Nature, 378(6556), 496–498.
Lakoff, G. (2008). The neural theory of metaphor. In R.W. Gibbs (Ed.), The Cambridge handbook of metaphor and thought (pp. 17–38). New York, NY: Cambridge University Press.
Lakoff, G., & Narayanan, S. (2010, March). Toward a computational model of narrative. In AAAI Fall Symposium: Computational Models of Narrative, 21–28.
Miyashita, Y. (2004). Cognitive memory: Cellular and network machineries and their top-down control. Science, 306(5695), 435–440.
Moulton, S.T., & Kosslyn, S.M. (2009). Imagining predictions: Mental imagery as mental emulation. Philosophical Transactions of the Royal Society B: Biological Sciences, 364(1521), 1273–1280.
Pasemann, F. (2002). Complex dynamics and the structure of small neural networks. Network: Computation in Neural Systems, 13(2), 195–216.
Post, R.M., & Weiss, S.R. (1997). Emergent properties of neural systems: How focal molecular neurobiological alterations can affect behavior. Development and Psychopathology, 9(4), 907–929.
Quartz, S.R., & Sejnowski, T.J. (1997). The neural basis of cognitive development: A constructivist manifesto. Behavioral and brain sciences, 20(4), 537–556.
Rabinovich, M.I., & Varona, P. (2011). Robust transient dynamics and brain functions. Frontiers in computational neuroscience, 5, 24.
Reder, L.M., Park, H., & Kieffaber, P.D. (2009). Memory systems do not divide on consciousness: Reinterpreting memory in terms of activation and binding. Psychological Bulletin, 135(1), 23–49.
Rugg, M.D., Otten, L.J., & Henson, R.N. (2002). The neural basis of episodic memory: evidence from functional neuroimaging. Philosophical Transactions of the Royal Society of London. Series B: Biological Sciences, 357(1424), 1097–1110.
Schacter, D.L., Addis, D.R., & Buckner, R.L. (2008). Episodic simulation of future events. Annals of the New York Academy of Sciences, 1124(1), 39–60.
Schendan, H.E., & Ganis, G. (2012). Electrophysiological potentials reveal cortical mechanisms for mental imagery, mental simulation, and grounded (embodied) cognition. Frontiers in psychology, 3, 329.
Schoner, G., & Kelso, J.A. (1988). Dynamic pattern generation in behavioral and neural systems. Science, 239(4847), 1513–1520.
Serugendo, G.D.M., Gleizes, M.P., & Karageorgos, A. (2006). Self-organisation and emergence in MAS: An overview. Informatica (Slovenia), 30(1), 45–54.
Soon, C.S., Brass, M., Heinze, H.J., & Haynes, J.D. (2008). Unconscious determinants of free decisions in the human brain. Nature Neuroscience, 11(5), 543–545.
Spreng, R.N., & Grady, C.L. (2010). Patterns of brain activity supporting autobiographical memory, prospection, and theory of mind, and their relationship to the default mode network. Journal of Cognitive Neuroscience, 22(6), 1112–1123.
Thagard, P., & Stewart, T.C. (2011). The AHA! experience: Creativity through emergent binding in neural networks. Cognitive Science, 35(1), 1–33.
Werner, G. (2009). Consciousness related neural events viewed as brain state space transitions. Cognitive neurodynamics, 3(1), 83–95.
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