How insight emerges in a distributed, content- addressable memory

Neuroscience of Creativity

Volumn , Issue , 2013, Pages 19-43

  Gabora, Liane ^a   Ranjan, Apara ^a  

^a UNIVERSITY OF BRITISH COLUMBIA   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 85036572619     PISSN: None     EISSN: None     Source Type: Book    
DOI: None     Document Type: Chapter

References (77)

1. Aerts, D. (2009). Quantum structure in cognition. Journal of Mathematical Psychology, 53, 314-348.
2. Aerts, D., Broekaert, J., Gabora, L., & Veloz, T. (2012). The guppy effect as interference. In Proceedings of the Sixth International Symposium on Quantum Interaction. June 27-29, Paris.
3. Aerts, D., & Gabora, L. (2005a). A state-context-property model of concepts and their combinations I: The structure of the sets of contexts and properties. Kybernetes, 34, 151-175.
4. Aerts, D., & Gabora, L. (2005b). A state-context-property model of concepts and their combinations II: A Hilbert space representation. Kybernetes, 34, 176-205.
5. Anderson, J. R. (1983). A spreading activation theory of memory. Journal of Verbal Learning and Verbal Behavior, 22, 261-295.
6. Andrews-Hanna, J. R., Reilder, J. S., Huang, C., & Buckner, R. L. (2010). Evidence for the default network’s role in spontaneous cognition. Journal of Neurophysiology, 104, 322-335.
7. Barsalou, L. (1987). The instability of graded structure: Implications for the nature of concepts. In U. Neisser (Ed.), Concepts and conceptual development: Ecological and intellectual factors in categorization. Cambridge: Cambridge University Press.
8. Beghetto, R. A. & Kaufman, J. C. (2007). Toward a broader conception of creativity: A case for ” mini-c ” creativity. Journal of Aesthetics, Creativity, and the Arts, 1, 73-79.
9. Blasdel, G. G., & Salama, G. (1986). Voltage sensitive dyes reveal a modular organization in monkey striate cortex. Nature, 321, 579-585.
10. Boden, M. A. (1990). The creative mind: Myths and mechanism. London: Abacus.
11. Bruza, P., Kitto, K., Nelson, D., & McEvoy, C. (2009). Is there something quantumlike in the human mental lexicon? Journal of Mathematical Psychology, 53, 362-377.
12. Bruza, P. D., Kitto, K., Ramm, B., Sitbon, L., Blomberg, S., & Song, D. (2010). Quantum-like non-separability of concept combinations, emergent associates and abduction. Logic Journal of the IGPL, 20, 445-457.
13. Chaiken, S., & Trope, Y. (1999). Dual-process theories in social psychology. New York: Guilford Press.
14. Chandrasekharan, S. (2009). Building to discover: A common coding model. Cognitive Science, 33, 1059-1086.
15. Churchland, P. S., & Sejnowski, T. (1992). The computational brain. Cambridge, MA: MIT Press.
16. Churchland, P. S., Sejnowski, T. J., & Arbib, M. A. (1992). The computational brain. Science, 258, 1671-1672.
17. Collins, A. M., & Loftus, E. F. (1975). A spreading-activation theory of semantic processing. Psychological Review, 82, 407-428.
18. Dayan, P., & Abbott, L. F. (2001). Theoretical neuroscience: Computational and mathematical modeling of neural systems. Cambridge, MA: MIT Press.
19. DiPaola, S., & Gabora, L. (2009). Incorporating characteristics of human creativity into an evolutionary art algorithm Genetic Programming and Evolvable Machines, 10 (2), 97-110.
20. Edelman, G. (1987). Neural Darwinism: The theory of neuronal group selection. New York: Basic Books.
21. Edelman, G. (2000). Bright air, brilliant fire: On the matter of the mind. New York: Basic Books.
22. Eliasmith, C., & Anderson, C. H. (2003). Neural engineering: Computation, representation, and dynamics in neurobiological systems. Cambridge, MA: MIT Press.
23. Evans, J., & Frankish, K. (Eds.). (2009). In two minds: Dual processes and beyond. New York: Oxford University Press.
24. Feldman, J., & Ballard, D. (1982). Connectionist models and their properties. Cognitive Science, 6, 204-254.
25. Finke, R. A., Ward, T. B., & Smith, S. M. (1992). Creative cognition: Theory, research, and applications. Cambridge, MA: MIT Press.
26. Freud, S. (1949). An outline of psychoanalysis. New York: Norton.
27. Gabora, L. (2001). Cognitive mechanisms underlying the origin and evolution of culture. Ph.D. Dissertation, Free University of Brussels.
28. Gabora, L. (2000). Toward a theory of creative inklings. In R. Ascott (Ed.), Art, technology, and consciousness (pp. 159-164). Bristol, UK: Intellect Press.
29. Gabora, L. (2002). Cognitive mechanisms underlying the creative process. In T. Hewett & T. Kavanagh (Eds.), Proceedings of the Fourth International Conference on Creativity and Cognition, 126-133. October 13-16, Loughborough University, UK. New York: ACM Press.
30. Gabora, L. (2003). Contextual focus: A cognitive explanation for the cultural transition of the Middle/Upper Paleolithic. In R. Alterman & D. Kirsh (Eds.), Proceedings of the 25th Annual Meeting of the Cognitive Science Society. July 31-August 2, Boston, MA. Hillsdale, NJ: Lawrence Erlbaum.
31. Gabora, L. (2005). Creative thought as a non-Darwinian evolutionary process. Journal of Creative Behavior, 39, 262-283.
32. Gabora, L. (2010). Revenge of the ” neurds ”: Characterizing creative thought in terms of the structure and dynamics of human memory. Creativity Research Journal, 22, 1-13.
33. Gabora, L. (under revision). The honing theory of creativity.
34. Gabora, L., & Aerts, D. (2002). Contextualizing concepts using a mathematical generalization of the quantum formalism. Journal of Experimental & Theoretical Artificial Intelligence, 14, 327-358.
35. Gabora, L., & Aerts, D. (2009). A mathematical model of the emergence of an integrated worldview. Journal of Mathematical Psychology, 53, 434-451.
36. Gabora, L., Chia, L., & Firouzi, H. (2013). A computational model of two cognitive transitions underlying cultural evolution. In Proceedings of the 35th Annual Meeting of the Cognitive Science Society. Austin, TX: Cognitive Science Society.
37. Gabora, L., & DiPaola, S. (2012). How did humans become so creative? In Proceedings of the International Conference on Computational Creativity. May 31-June 1, 2012, Dublin, Ireland.
38. Gabora, L., Rosch, E., & Aerts, D. (2008). Toward an ecological theory of concepts. Ecological Psychology, 20, 84-116.
39. Gabora, L., & Saab, A. (2011). Creative interference and states of potentiality in analogy problem solving. In Proceedings of the Annual Meeting of the Cognitive Science Society. July 20-23, 2011, Boston MA.
40. Gabora, L. Scott, E., & Kauffman, S. (in press). A quantum model of exaptation: Incorporating potentiality into biological theory. Progress in Biophysics & Molecular Biology.
41. Gardner, H. (1993). Frames of mind: The theory of multiple intelligences. New York: Basic Books.
42. Guilford, J. P. (1950). Creativity. American Psychologist, 5, 444-454.
43. Hampton, J. (1987). Inheritance of attributes in natural concept conjunctions. Memory & Cognition, 15, 55-71.
44. Hancock, P. J. B., Smith, L. S., & Phillips, W. A. (1991). A biologically supported error-correcting learning rule. Neural Computation, 3, 201-212.
45. Hebb, D. (1949). The organization of behavior. New York: Wiley.
46. Hebb, D. (1980). Essay on mind. Hillsdale, NJ: Lawrence Erlbaum.
47. Hinton, G., McClelland, J., & Rumelhart, D. (1986). Distributed representations. In D. Rumelhart, J. McClelland, & the PDP Research Group (Eds.), Parallel distributed processing (Vol. 1, pp. 77-109). Cambridge, MA: MIT Press.
48. Holden, S. B., & Niranjan, M. (1997). Average-case learning curves for radial basis function networks. Neural Computation, 9, 441-460.
49. Hopfield, J. J. (1982). Neural networks and physical systems with emergent collective computational abilities. Proceedings of the National Academy of Sciences (Biophysics), 79, 2554-2558.
50. Hopfield, J. J., Feinstein, D. I., & Palmer, R. D. (1983). “Unlearning” has a stabilizing effect in collective memories. Nature, 304, 159-160.
51. Hubel, D. A., & Wiesel, T. N. (1965). Receptive fields and functional architecture in two non-striate visual areas (18 and 19) of the cat. Journal of Neurophysiology, 28, 229-289.
52. James, W. [ 1890 ] (1950). The principles of psychology. New York: Dover.
53. Lin, L., Osan, R., Shoham, S., Jin, W., Zuo, W., & Tsien, J. Z. (2005). Identification of network-level coding units for real-time representation of episodic experiences in the hippocampus. Proceedings of the National Academy of Sciences of the United States of America, 102, 6125-6130.
54. Lin, L., Osan, R., & Tsien, J. Z. (2006). Organizing principles of real-time memory encoding: Neural clique assemblies and universal neural codes. Trends in Neurosciences, 29, 48-57.
55. Loftus, E. F. (1980). Memory: Surprising new insights into how we remember and why we forget. Reading, MA: Addison-Wesley.
56. Lu, Y. W., Sundararajan, N., & Saratchandran, P. (1997). A sequential learning scheme for function approximation using minimal radial basis function neural networks. Neural Computation, 9, 461-478.
57. Marr, D. A. (1969). Theory of the cerebellar cortex. Journal of Physiology, 202, 437-470.
58. McClelland, J. L., & Rumelhart, D. E. (1986). A distributed model of memory. In D. Rumelhart, J. McClelland, & the PDP Research Group (Eds.), Parallel distributed processing: Explorations in the microstructure of cognition (Vol. II, Ch. 17). Cambridge, MA: MIT Press.
59. Mednick, S. (1962). The associative basis of the creative process. Psychological Review, 69, 220-232.
60. Miikkulainen, R. (1997). Natural language processing with subsymbolic neural networks. In A. Brown (Ed.), Neural network perspectives on cognition and adaptive robotics. Bristol, UK: Institute of Physics Press.
61. Nelson, D. L., McEvoy, C. L., & Pointer, L. (2003). Spreading activation or spooky activation at a distance? Journal of Experimental Psychology: Learning, Memory, and Cognition, 29, 42-52.
62. Nelson, D. L., McEvoy, C. L., & Schreiber, T. A. (2004). The University of South Florida word association, rhyme and word fragment norms. Behavior Research Methods, Instruments, & Computers, 36, 408-420.
63. Newell, A., & Simon, H. (1972). Human problem solving. Edgewood Cliffs, NJ: Prentice-Hall.
64. Newell, A., Shaw, C., & Simon, H. (1957). The process of creative thinking. In H. E. Gruber, G. Terrell, & M. Wertheimer (Eds.), Contemporary approaches to creative thinking (pp. 153-189). New York: Pergamon.
65. Ohlsson, S. (1992). Information-processing explanations of insight and related phenomena. In M. T. Keane & K. J. Gilhooly (Eds.), Advances in the psychology of thinking (Vol. 1, pp. 1-44). New York: Harvester Wheatsheaf.
66. Osherson, D., & Smith, E. (1981). On the adequacy of prototype theory as a theory of concepts. Cognition, 9, 35-58.
67. Paterson, H. M., Kemp, R. I., & Forgas, J. P. (2009). Co-witnesses, confederates, and conformity: The effects of discussion and delay on eyewitness memory Psychiatry, Psychology, and Law, 16, S112-S124.
68. Runco, M. A. (2004a). Creativity. Annual Review of Psychology, 55, 657-687.
69. Runco, M. A. (2004b). Everyone is creative. In R. J. Sternberg, E. L. Grigorenko, & J. L. Singer (Eds.), Creativity: From potential to realization (pp. 21-30). Washington, DC: American Psychological Association.
70. Schacter, D. L. (2001). The seven sins of memory: How the mind forgets and remembers. Reading, MA: Houghton Mifflin.
71. Signer, J. L., & Antrobus, J. S. (1963). A factor-analytic study of day-dreaming and conceptually related cognitive and personality variables. Perceptual and Motor Skills, 17, 187-209.
72. Simonton, D. K. (1999). Creativity as blind variation and selective retention: Is the creative process Darwinian? Psychological Inquiry, 10, 309-328.
73. Smallwood, J., & Schooler, J. W. (2006). The restless mind. Psychological Bulletin, 132, 946-958.
74. Smith, E. E., & Kosslyn, S. M. (2007). Cognitive psychology: Mind and brain. Upper Saddle River, NJ: Pearson Prentice Hall.
75. Smolensky, P. (1988). On the proper treatment of connectionism. Behavioral and Brain Sciences, 11, 1-43.
76. Veloz, T., Gabora, L., Eyjolfson, M., & Aerts, D. (2011). A model of the shifting relationship between concepts and contexts in different modes of thought. In Proceedings of the Fifth International Symposium on Quantum Interaction. June 27-29, 2011, Aberdeen, UK.
77. Willshaw, D., & Dayan, P. (1990). Optimal plasticity from matrix memories: What goes up must come down Neural Computation, 2 (1), 85-93.