The Drive for Creativity and the Escape from Creativity: Neurocognitive Mechanisms

Cognitive Computation

Volumn 4, Issue 3, 2012, Pages 292-305

  Perlovsky, Leonid I ^a,b   Levine, Daniel S ^c  

^a HARVARD UNIVERSITY   (United States)

^b AIR FORCE RESEARCH LABORATORY   (United States)

^c UNIVERSITY OF TEXAS AT ARLINGTON   (United States)

Author keywords

Brain; Cognitive dissonance; Creativity; Emotion; Heuristics; Language

Indexed keywords

COGNITIVE DISSONANCE; CREATIVITY; EMOTION; HEURISTICS; LANGUAGE;

BRAIN;

KNOWLEDGE ACQUISITION;

EID: 84866520945     PISSN: 18669956     EISSN: 18669964     Source Type: Journal    
DOI: 10.1007/s12559-012-9154-3     Document Type: Article

References (100)

1. Arbib MA. From monkey-like action recognition to human language: an evolutionary framework for neurolinguistics. Behav Brain Sci. 2005; 28: 105-67.
2. Ashby FG, Isen AM, Turken AU. A neuropsychological theory of positive affect and its influence on cognition. Psychol Rev. 1999; 106: 529-50.
3. Baas M, De Dreu CKW, Nijstad BA. A meta-analysis of 25 years of research on mood and creativity: hedonic tone, activation, or regulatory focus? Psychol Bull. 2008; 134: 739-56.
4. Bar M, Kassam KS, Ghuman AS, Boshyan J, Schmid AM, Dale AM, et al. Top-down facilitation of visual recognition. Proc Natl Acad Sci USA. 2006; 103: 449-54.
5. Bar M. The proactive brain: using analogies and associations to generate predictions. Trends Cogn Sci. 2007; 11: 281-9.
6. Barbano M, Cador M. Opioids for hedonic experience and dopamine to get ready for it. Psychopharmacology. 2007; 191: 497-506.
7. Bartoshuk LM. Personal communication to author LIP. 2010.
8. Berridge KC. The debate over dopamine's role in reward: the case for incentive salience. Psychopharmacology. 2007; 191: 391-431.
9. Brown JW, Braver TS. Learned predictions of error likelihood in the anterior cingulate cortex. Science. 2005; 307: 1118-21.
10. Brown S, Martinez MJ, Parsons LM. Music and language side by side in the brain: a PET study of the generation of melodies and sentences. Eur J Neurosci. 2006; 23: 2791-803.
11. Bunge SA. How we use rules to select actions: a review of evidence from cognitive neuroscience. Cogn Affect Behav Neurosci. 2004; 4: 564-79.
12. Carpenter GA, Grossberg S. A massively parallel architecture for a self-organizing neural pattern recognition machine. Comput Vis Graph Image Process. 1987; 37: 54-115.
13. Chalmers DJ. Consciousness and its place in nature. In: Chalmers DJ, editor. The character of consciousness (Ch. 5). New York: Oxford University Press; 2010.
14. Chomsky N. Language and mind. New York: Harcourt Brace Jovanovich; 1972.
15. Cloninger CR. A new conceptual paradigm from genetics and psychobiology for the science of mental health. Aust N Z J Psychiatry. 1999; 33: 174-86.
16. Deacon T. The neural circuitry underlying primate calls and human language. Hum Evol J. 1989; 4(5): 367-401.
17. DeMartino B, Kumaran D, Seymour B, Dolan R. Frames, biases, and rational decision-making in the human brain. Science. 2006; 313: 684-7.
18. Denes-Raj V, Epstein S. Conflict between intuitive and rational processing: when people behave against their better judgment. J Pers Soc Psychol. 1994; 66: 819-29.
19. Farb NA, Anderson AK, Mayberg H, Bean J, McKeon D, Segal ZV. Minding one's emotions: mindfulness training alters the neural expression of sadness. Emotion. 2010; 10: 25-33.
20. Fontanari JF, Perlovsky LI. How language can help discrimination in the neural modeling fields framework. Neural Netw. 2008; 21: 250-6.
21. Fontanari JF, Perlovsky LI. A game theoretical approach to the evolution of structured communication codes. Theory Biosci. 2008; 127: 205-14. doi: 10. 1007/s12064-008-0024-1.
22. Fontanari FJ, Tikhanoff V, Cangelosi A, Ilin R, Perlovsky LI. Cross-situational learning of object-word mapping using neural modeling fields. Neural Netw. 2009; 22: 579-85.
23. Gable P, Harmon-Jones E. The motivational dimensional model of affect: implications for breadth of attention, memory, and cognitive categorization. Cogn Emot. 2010; 24: 322-37.
24. Grossberg S. A neural theory of punishment and avoidance: qualitative theory. Math Biosci. 1972; 15: 39-67.
25. Grossberg S. Studies of mind and brain. Dordrecht: Reidel; 1982.
26. Grossberg S, Levine DS. Neural dynamics of attentionally modulated Pavlovian conditioning: blocking, interstimulus interval, and secondary reinforcement. Appl Opt. 1987; 26: 5015-30.
27. Harmon-Jones E. From cognitive dissonance to the motivational functions of emotions. In: Wright RA, Greenberg J, Brehm SS, editors. Motivational analyses of social behavior: building on Jack Brehm's contributions to psychology. Mahwah: Lawrence Erlbaum Associates; 2004. p. 39-55.
28. Herbert C, Herbert BM, Pauli P. Emotional self-reference: brain structures involved in the processing of words describing one's own emotions. Neuropsychologia. 2011; 49: 2947-56.
29. Iyer LR, Doboli S, Minai AA, Brown VR, Levine DS, Paulus PB. Neural dynamics of idea generation and the effects of priming. Neural Netw. 2009; 22: 674-86.
30. Jackendoff RS. Word meanings and what it takes to learn them: Reflections on the Piaget-Chomsky debate. In: Jackendoff RS, editor. Languages of the mind: Essays on mental representation (Ch. 3). MA: MIT Press; 1992.
31. Kosslyn SM. Image and mind. Cambridge: Harvard University Press; 1980.
32. Levens SM, Phelps EA. Emotion processing effects on interference resolution in working memory. Emotion. 2008; 8: 267-80.
33. Levine DS. Introduction to neural and cognitive modeling. 2nd ed. Mahwah: Lawrence Erlbaum Associates; 2000.
34. Levine DS. Angels, devils, and censors in the brain. ComPlexus. 2005; 2: 35-59.
35. Levine DS. Value maps, drives, and emotions. In: Cutsuridis V, Taylor JG, Polani D, Hussain A, Tishby N, editors. Perception-reason-action cycle: models, algorithms, and systems. Berlin: Springer; 2011. p. 135-68.
36. Levine DS. Neural dynamics of affect, gist, probability, and choice. Cogn Sys Res. 2012; 15-16: 57-72. doi: 10. 1016/j. cogsys. 2011. 07. 002.
37. Levine DS. I think therefore I feel: neural mechanisms for knowledge-based pleasure. To appear in World Congress on Computational Intelligence 2012. Brisbane, Australia; 2012.
38. Levine DS, Perlovsky LI. Neuroscientific insights on biblical myths: simplifying heuristics versus careful thinking: scientific analysis of millennial spiritual issues. Zygon, J Sci Relig. 2008; 43: 797-821.
39. Lieberman P. Human Language and our reptilian brain: the subcortical bases of speech, syntax, and thought. Cambridge: Harvard University Press; 2000.
40. Luu P, Collins P, Tucker DM. Mood, personality, and self-monitoring: negative affect and emotionality in relation to frontal lobe mechanisms of error monitoring. J Exp Psychol Gen. 2000; 129: 43-60.
41. Masataka N, Perlovsky LI. Music can reduce cognitive dissonance. Nat Precedings http://hdl. handle. net/10101/npre. 2012. 7080. 1.
42. Maslow AH. Toward a psychology of being. New York: van Nostrand; 1968.
43. Mauss IB, Robinson MD. Measures of emotion: a review. Cogn Emot. 2009; 23: 209-37.
44. Mayer JD, Salovey P, Caruso DR, Sitarenios G. Emotional intelligence as a standard intelligence. Emotion. 2001; 1: 232-42.
45. Menon V, Uddin LQ. Saliency, switching, attention, and control: a network model of insula function. Brain Struct Funct. 2010; 214: 655-67.
46. Milne E, Grafman J. Ventromedial prefrontal cortex lesions in humans eliminate implicit gender stereotyping. J Neurosci (Special Issue). 2001; 21(12): 1-6.
47. Mitchell DGV. The nexus between decision making and emotion regulation: a review of convergent neurocognitive substrates. Behav Brain Res. 2011; 217: 215-31.
48. Moran JM, Macrae CN, Heatherton TF, Wyland CL, Kelley WM. Neuroanatomical evidence for distinct cognitive and affective components of self. J Cogn Neurosci. 2006; 18: 1586-94.
49. Paulus PB, Levine DS, Brown VR, Minai AA, Doboli S. Modeling ideational creativity in groups: connecting cognitive, neural, and computational approaches. Small Group Res. 2010; 41: 688-724.
50. Payne JW. Task complexity and contingent processing in decision making: an information search and protocol analysis. Organ Behav Hum Perform. 1976; 16: 366-87.
51. Perlovsky LI. Computational concepts in classification: neural networks, statistical pattern recognition, and model based vision. J Math Imaging Vis. 1994; 4: 81-110.
52. Perlovsky LI. Gödel theorem and semiotics. Proceedings of the conference on intelligent systems and semiotics '96. Vol 2 Gaithersburg, MD; 1996. p. 14-8.
53. Perlovsky LI. Physical concepts of intellect. Proc Russian Acad Sci. 1997; 354: 320-3.
54. Perlovsky LI. Conundrum of combinatorial complexity. IEEE Trans Pattern Anal Mach Intell. 1998; 20: 666-70.
55. Perlovsky LI. Neural networks and intellect: using model based concepts. New York: Oxford University Press; 2001.
56. Perlovsky LI. Physical theory of information processing in the mind: concepts and emotions. Seed (OnLine Journal). 2002; 2(2): 36-54.
57. Perlovsky LI. Integrating language and cognition. IEEE Connect Featur Artic. 2004; 2(2): 8-12.
58. Perlovsky LI. Evolving agents: communication and cognition. In: Gorodetsky V, Liu J, Skormin VA, editors. Autonomous intelligent systems: Agents and data mining. Berlin: Springer; 2005. p. 37-49.
59. Perlovsky LI. Evolution of consciousness and music. Zvezda, St. Petersburg (Russian), 2005; 8: 192-223.
60. Perlovsky LI. Toward physics of the mind: concepts, emotions, consciousness, and symbols. Phys Life Rev. 2006; 3: 22-55.
61. Perlovsky LI. Fuzzy dynamic logic. New Math Nat Comput. 2006; 2(1): 43-55.
62. Perlovsky LI. Evolution of languages, consciousness, and cultures. IEEE Comput Intell Mag. 2007; 2(3): 25-39.
63. Perlovsky LI. The mind versus logic: Aristotle and Zadeh. Society for Mathematics of Uncertainty. Crit Rev. 2007; 1(1): 30-3.
64. Perlovsky LI. Modeling Field Theory of higher cognitive functions. In: Loula A, Gudwin R, Queiroz J, editors. Artificial cognition systems. Hershey: Idea Group; 2007. p. 64-105.
65. Perlovsky LI. Symbols: Integrated cognition and language. In: Loula A, Gudwin R, Queiroz J, editors. Artificial cognition systems. Hershey: Idea Group; 2007. p. 121-51.
66. Perlovsky LI. Neural networks, fuzzy models and dynamic logic. In: Köhler R, Mehler A, editors. Aspects of automatic text analysis (Festschrift in honor of Burghard Rieger). Heidelberg: Springer; 2007. p. 363-86.
67. Perlovsky LI. Sapience, consciousness, and the knowledge instinct. (Prolegomena to a physical theory). In: Mayorga R, Perlovsky LI, editors. Sapient systems. London: Springer; 2008.
68. Perlovsky LI. Language and cognition. Neural Netw. 2009; 22: 247-57.
69. Perlovsky LI. Language and emotions: emotional Sapir-Whorf hypothesis. Neural Netw. 2009; 22: 518-26.
70. Perlovsky LI. 'Vague-to-crisp' neural mechanism of perception. IEEE Trans Neural Netw. 2009; 20: 1363-7.
71. Perlovsky LI. Musical emotions: functions, origin, evolution. Phys Life Rev. 2010; 7: 2-27.
72. Perlovsky LI. Intersections of mathematical, cognitive, and aesthetic theories of mind. Psychol Aesthet Creat Art. 2010; 4: 11-7.
73. Perlovsky LI. The mind is not a kludge. Skeptic. 2010; 15: 50-5.
74. Perlovsky LI. Neural mechanisms of the mind, Aristotle, Zadeh, and fMRI. IEEE Trans Neural Netw. 2010; 21: 718-33.
75. Perlovsky LI. Joint acquisition of language and cognition. WebmedCentral Brain, 2010; 1(10): WMC00994.
76. Perlovsky LI. Science and religion: Scientific understanding of emotions of religiously sublime. arXive. 2010.
77. Perlovsky LI. Music. Cognitive function, origin, and evolution of musical emotions. Webmedcentral Psychology 2011; 2(2): WMC001494.
78. Perlovsky LI. Cognitive function, origin, and evolution of musical emotions. Music Sci. 2012. doi: 10. 1177/1029864912448327.
79. Perlovsky LI. Cognitive function of music. Interdiscip Sci Rev 2012; 37(2): 129-42.
80. Perlovsky LI, Bonniot-Cabanac MC, Cabanac M. Curiosity and pleasure. Webmedcentral Psychology, 2010; 1(12): WMC001275.
81. Perlovsky LI, Ilin R. Neurally and mathematically motivated architecture for language and thought. special issue brain and language architectures: where we are now? Open Neuroimag J. 2010; 4: 70-80. http://www. bentham. org/open/tonij/openaccess2. htm.
82. Perlovsky LI, Ilin R. Grounded symbols in the brain, computational foundations for perceptual symbol system. Webmedcentral Psychology 2010; 1(12): WMC001357.
83. Perlovsky LI, Kozma R. Editorial-Neurodynamics of cognition and consciousness. In: Perlovsky LI, Kozma R, editors. Neurodynamics of cognition and consciousness. Heidelberg: Springer; 2007. p. 1-8.
84. Perlovsky LI, Levine DS. The drive for creativity. International joint conference on neural netw (IJCNN 2010). Barcelona, 2010; p. 1665-70.
85. Perlovsky LI, Mayorga R. Preface. In: Mayorga R, Perlovsky LI, editors. Sapient systems. London: Springer; 2008.
86. Perlovsky LI, McManus MM. Maximum likelihood neural networks for sensor fusion and adaptive classification. Neural Netw. 1991; 4: 89-102.
87. Phelps EA. Interaction of emotion and cognition. In: Barrett LE, Niedenthal PM, Winkielman P, editors. Emotion and consciousness. New York: Guilford Press; 2005.
88. Piaget J. Genetic epistemology. New York: Columbia University Press; 1970.
89. Powell LJ, Macrae CN, Cloutier J, Metcalfe J, Mitchell JP. Dissociable neural substrates for agentic versus conceptual representations of self. J Cogn Neurosci. 2010; 22: 2186-97.
90. Reyna VF, Brainerd CJ. Numeracy, ratio bias, and denominator neglect in judgments of risk and probability. Learn Individ Diff. 2008; 18: 89-107.
91. Reyna VF, Lloyd FJ, Brainerd CJ. Memory, development, and rationality: an integrative theory of judgment and decision making. In: Schneider S, Shanteau J, editors. Emerging perspectives on judgment and decision making. New York: Cambridge University Press; 2003. p. 201-45.
92. Rottenstreich Y, Hsee C. Money, kisses, and electric shocks: on the affective psychology of risk. Psych. Sci. 2001; 12: 185-90.
93. Schacter DL, Addis DR. The ghosts of past and future. Nature. 2007; 445(27): 2007.
94. Sterzer B, Kleinschmidt A. Anterior insula activations in perceptual paradigms: often observed but barely understood. Brain Struct. Funct. 2010; 214: 611-22.
95. Seeley WW, Menon V, Schatzberg AF, Keller J, Glover GH, Kenna H, Reiss AL, Greicius MD. Dissociable intrinsic connectivity networks for salience processing and executive control. J Neurosci. 2007; 27: 2349-65.
96. Tikhanoff V, Fontanari JF, Cangelosi A, Perlovsky LI. Language and cognition integration through modeling field theory: category formation for symbol grounding. In: Computer science, v. 4131. Springer: Heidelberg. 2006.
97. Tversky A, Kahneman D. Judgment under uncertainty: heuristics and biases. Science. 1974; 185: 1124-31.
98. Tversky A, Kahneman D. The framing of decisions and the rationality of choice. Science. 1981; 211: 453-8.
99. White, RW. Motivation reconsidered: the concept of competence. Psychol Rev. 1959; 297-333.
100. Yue X, Vessel EA, Biederman I. The neural basis of scene preferences. NeuroReport. 2007; 18: 525-9.