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Creativity and the Brain

Duch, Wlodzislaw (2007) Creativity and the Brain. [Book Chapter] (In Press)

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Abstract

Neurocognitive approach to higher cognitive functions that bridges the gap between psychological and neural level of description is introduced. Relevant facts about the brain, working memory and representation of symbols in the brain are summarized. Putative brain processes responsible for problem solving, intuition, skill learning and automatization are described. The role of non-dominant brain hemisphere in solving problems requiring insight is conjectured. Two factors seem to be essential for creativity: imagination constrained by experience, and filtering that selects most interesting solutions. Experiments with paired words association are analyzed in details and evidence for stochastic resonance effects is found. Brain activity in the process of invention of novel words is proposed as the simplest way to understand creativity using experimental and computational means. Perspectives on computational models of creativity are discussed.

Item Type:Book Chapter
Keywords:creativity, computational creativity, neurocognitive informatics, neural basis of language, priming
Subjects:Neuroscience > Neurolinguistics
Computer Science > Language
Computer Science > Artificial Intelligence
ID Code:5356
Deposited By:Duch, Prof Wlodzislaw
Deposited On:19 Jan 2007
Last Modified:02 May 2011 16:54

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Select the SEEK icon to attempt to find the referenced article. If it does not appear to be in cogprints you will be forwarded to the paracite service. Poorly formated references will probably not work.

Arieli, A., Sterkin A.,Grinvald, A. & Aertsen, A. (1996). A. dynamics of ongoing activity: explanation of the large variability in evoked cortical responses. Science, 273, 1868–1871.

Baars, B.J. (1998). A cognitive theory of consciousness. Cambridge: Cambridge University Press.

Baddeley, A.D. (2002). Is working memory still working? European Psychologist, 7, 85-97.

Berns, G. (2005). Satisfaction: The science of finding true fulfillment. New York: Henry Holt.

Bowden, E.M., Jung-Beeman, M., Fleck, J., & Kounios, J. (2005). New approaches to demystifying insight. Trends in Cognitive Science, 9, 322-328.

Caplan, D., & Waters, G.S. (1999). Verbal working memory and sentence comprehension. Behavioral and Brain Sciences, 22, 77-94.

Cowan, N. (2005). Working memory capacity. New York: Psychology Press.

Damasio, H., Grabowski, T.J., Tranel, D., Hichwa, R. D., & Damasio, A. R. (1996). A neural basis for lexical retrieval. Nature, 380, 499-505.

Duch, W. (1996). Categorization, prototype theory and neural dynamics. In T. Yamakawa & G. Matsumoto (Eds.), Proceedings of the 4th International Conference on Soft Computing '96 (pp. 482-485). Iizuka, Japan.

Duch, W. (1997). Platonic model of mind as an approximation to neurodynamics. In: Brain-like computing and intelligent information systems, ed. S-i. Amari, N. Kasabov, Springer, Singapore, chap. 20, pp. 491-512, 1997.

Duch, W. (2005a). Brain-inspired conscious computing architecture. Journal of Mind and Behavior, 26(1-2), 1-22.

Duch, W. (2005b). Rules, Similarity, and Threshold Logic. Commentary on Emmanuel M. Pothos, The Rules versus Similarity distinction. Behavioral and Brain Sciences 28(1), 23-23.

Duch, W. (2006). Computational creativity. Paper read at the IEEE World Congress on Computational Intelligence, Vancouver, July, 16-21, IEEE Press, pp. 1162-1169.

Duch, W., & Blachnik, M. (2004). Fuzzy rule-based systems derived from similarity to prototypes. Lecture Notes in Computer Science, 3316, 912-917.

Duch, W., & Diercksen, G.H.F. (1995). Feature space mapping as a universal adaptive system. Computer Physics Communications, 87, 341-371.

Duch, W., R. Setiono, R., & Zurada, J. (2004). Computational intelligence methods for understanding of data. Proceedings of the IEEE 92(5), 771-805.

Duff, K., Schoenberg, M.R., Scott, J.G.., & Adams, R. L. (2005). The relationship between executive functioning and verbal and visual learning and memory. Archives of Clinical Neuropsychology, 20, 111-122.

Fries, P., Neuenschwander, S., Engel, A.K., Goebel, R., & Singer, W. (2001). Rapid feature selective neuronal synchronization through correlated latency shifting. Nature Neuroscience, 4, 194-200.

Gazzaniga, M. (1998). The mind’s past. Berkeley, California: University of California Press.

Gopnik, A., & Meltzoff, A. N. (1997). Words, thoughts and theories. Cambridge, Mass: MIT Press.

Gopnik, A., & Schulz, L. (2004). Mechanisms of theory formation in young children. Trends in Cognitive Sciences, 8(8), 371-377.

Gottfried, J.A., O'Doherty, J., & Dolan, R. J. (2003). Encoding predictive reward value in human amygdala and orbitofrontal Cortex. Science, 301, 1104-1107.

Grossberg, S. (2000). The complementary brain: Unifying brain dynamics and modularity. Trends in Cognitive Sciences, 4, 233-246.

Grossberg, S. (2003). Resonant neural dynamics of speech perception. Journal of Phonetics, 31, 423-445.

Gruszka, A., & Nęcka, E. (2002). Priming and acceptance of close and remote associations by creative and less creative people. Creativity Research Journal 14(2), 193-205.

Heilman, K.M., Nadeau, S.E., & Beversdorf, D.O. (2003). Creative innovation: Possible brain mechanism. Neurocase, 9, 369-379.

Hofstadter, D. R. (1995). Fluid concepts and creative analogies: Computer models of the fundamental mechanisms of thought. NewYork: Basic Books.

Humphries, M., Gurney, K., & Prescott, T. (2005). Action selection in a macroscopic model of the brainstem reticular formation. In J.J. Bryson, T.J. Prescott & A. Seth (Eds.), Modelling natural action selection (pp. 61-68). Brighton, UK: AISB Press.

Jensen, A. (1998). The g factor. Westport, Connecticut: Praeger.

Jung-Beeman, M., Bowden, E.M., Haberman, J., Frymiare, J.L., Arambel-Liu, S., Greenblatt, R., Reber, P.J., &. Kounios, J. (2004). Neural activity when people solve verbal problems with insight. PLoS Biology, 2(4), 500-510.

Kelso, J.A.S. (1995). Dynamic patterns. The self-organization of brain and behavior. Cambridge, Mass: MIT Press.

Lapointe, L. L. (2005). Aphasia and related neurogenic language disorders (Third edition). New York: Thieme.

Martin, M., Wiggs, C.L., Ungerleider, L.G., & Haxby, J.V. (1996). Neural correlates of category-specific knowledge. Nature, 379, 649-652.

Mednick, S.A. (1962). The associative basis of the creative process. Psychological Review, 69, 220–232.

Mitchell, M. (1993). Analogy-making as perception: A computer model. Cambridge, MA: MIT Press.

Mitchell, T.N., Free, S.L., Merschhemke, M., Lemieux, L., Sisodiya M.S.M., & Shorvon, S.D. (2003) Reliable Callosal Measurement: Population Normative Data Confirm Sex-Related Differences, American Journal of Neuroradiology 24:410-418.

Molfese, D.L. (2000). Predicting dyslexia at 8 years of age using neonatal brain responses. Brain and Language, 72, 238-245, 2000.

Molfese, D.L., & Molfese, V.J. (2000). The continuum of language development during infancy and early childhood: Electrophysiological correlates. In C. Rovee-Collier, L. P. Lipsitt & H. Hayne (Eds.), Progress in infancy research (Vol. 1, pp. 251-287). Mahwah, N.J.: Lawrence Erlbaum Associates.

Pulvermueller, F. (2001). Brain reflections of words and their meaning. Trends in Cognitive Sciences, 5, 517-524.

Pulvermueller, F. (2002). A brain perspective on language mechanisms: from discrete neuronal ensembles to serial order. Progress in Neurobiology, 67, 85-111.

Pulvermueller, F. (2003). The neuroscience of language. On brain circuits of words and serial order. Cambridge: Cambridge University Press.

Pulvermueller, P., Shtyrov, Y., & Ilmoniemi, R. (2005). Brain signatures of meaning access in action word recognition. Journal of Cognitive Neuroscience, 17(6), 884-892.

Rakover, S. S. (1990). Metapsychology: Missing links in behavior, mind, and science. New York: Paragon House Publisher.

Redick, T.S., & Engle, R.W. (2006). Working memory capacity and attention network test performance. Applied Cognitive Psychology, 20, 713 - 721.

Rehling, J. (2001). Letter spirit (part two): Modeling creativity in a visual domain. Ph.D. thesis submitted to Indiana University.

Ruchkin, D.S., Grafman, J., Cameron, K., & Berndt, R.S. (2003). Working memory retention systems: A state of activated long-term memory. Behavioral and Brain Sciences, 26(6), 709-728.

Runco,M., & Pritzker, S. (1999) (Eds.). Encyclopedia of creativity (Vols. 1 & 2). San Diego: Academic Press.

Schultz, A. (2000). Multiple reward signals in the brain. Nature Reviews of Neuroscience 1(3), 199-207.

Singer, W. (1999). Neuronal synchrony: a versatile code for the definition of relations? Neuron, 24, 49–65.

Smith, L. B., & Thelen, E. (1993) (Eds.). A dynamic systems approach to the development: Applications. Cambridge, M.A.: Bradford.

Sternberg, R. J., & Davidson, J.E. (1995). The nature of insight. Cambridge: MIT Press.

Sternberg, R.J., & Lubart, T.I. (1999). The concept of creativity: Prospects and paradigms. In R. J. Sternberg (Ed.), Handbook of creativity (pp.3-15). Cambridge: Cambridge University Press.

Thelen, E. & Smith, L.B. (1994). A dynamic systems approach to the development of cognition and action. Cambridge, M.A.: Bradford.

Vogel, E.K., McCollough, A.W., & Machizawa, M.G. (2005) Neural measures reveal individual differences in controlling access to working memory. Nature, 438, 500-503.

Wellens, T., Shatokhin, V., & Buchleitner, A. (2004). Stochastic resonance. Reports on Progress in Physics, 67, 45-105.

Wilson, R.A., & Keil, F.C. (1999) (Eds.). MIT encyclopedia of cognitive sciences. Cambridge, Mass: MIT Press.

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