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Human creativity, evolutionary algorithms, and predictive representations: The mechanics of thought trials

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Abstract

Creative thinking is arguably the pinnacle of cerebral functionality. Like no other mental faculty, it has been omnipotent in transforming human civilizations. Probing the neural basis of this most extraordinary capacity, however, has been doggedly frustrated. Despite a flurry of activity in cognitive neuroscience, recent reviews have shown that there is no coherent picture emerging from the neuroimaging work. Based on this, we take a different route and apply two well established paradigms to the problem. First is the evolutionary framework that, despite being part and parcel of creativity research, has no informed experimental work in cognitive neuroscience. Second is the emerging prediction framework that recognizes predictive representations as an integrating principle of all cognition. We show here how the prediction imperative revealingly synthesizes a host of new insights into the way brains process variation-selection thought trials and present a new neural mechanism for the partial sightedness in human creativity. Our ability to run offline simulations of expected future environments and action outcomes can account for some of the characteristic properties of cultural evolutionary algorithms running in brains, such as degrees of sightedness, the formation of scaffolds to jump over unviable intermediate forms, or how fitness criteria are set for a selection process that is necessarily hypothetical. Prospective processing in the brain also sheds light on how human creating and designing – as opposed to biological creativity – can be accompanied by intentions and foresight. This paper raises questions about the nature of creative thought that, as far as we know, have never been asked before.

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References

  • Abraham, A. (2013). The promises and perils of the neuroscience of creativity. Frontiers in Human Neuroscience, 7, 1–9. doi:10.3389/fnhum.2013.00246

    Google Scholar 

  • Anderson, J. R., & Lebiere, C. J. (1998). The Atomic Components of Thoughts. Mahwah, NJ: Lawrence Erlbaum Associates.

    Google Scholar 

  • Arden, R., Chavez, R. S., Grazioplene, R., & Jung, R. E. (2010). Neuroimaging creativity: A psychometric view. Behavioural Brain Research, 214, 143–156. doi:10.1016/j.bbr.2010.05.015

    PubMed  Google Scholar 

  • Ashby, G. F., & Casale, M. B. (2002). The cognitive neuroscience of implicit category learning. In L. Jiménez (Ed.), Attention and Implicit Learning (pp. 109–141). Amsterdam: John Benjamins Publishing Company.

    Google Scholar 

  • Atance, C. M., & O’Neill, D. K. (2001). Episodic future thinking. Trends in Cognitive Sciences, 5, 533–539. doi:10.1016/S1364-6613(00)01804-0

    PubMed  Google Scholar 

  • Aziz-Zadeh, L., & Liew, S. L. (2013). Exploring the neural correlates of visual creativity. Social Cognitive and Affect Neuroscience, 8, 475–480. doi:10.1093/scan/nss021

    Google Scholar 

  • Baars, B. J. (1988). A cognitive theory of consciousness. Cambridge: Cambridge University Press.

    Google Scholar 

  • Baker, S. C., Rogers, R. D., Owen, A. M., Frith, C. D., Dolan, R. J., Frackowiak, R. S. J., & Robbins, T. W. (1996). Neural systems engaged in planning: A PET study of the Tower of London task. Neuropsychologia, 34, 515–526.

    PubMed  Google Scholar 

  • Bar, M. (2007). The proactive brain: Using analogies and associations to generate predictions. Trends in Cognitive Science, 11, 280–289. doi:10.1016/j.tics.2007.05.005

    Google Scholar 

  • Bar, M. (2009). The proactive brain: Memory for prediction. Philosophical Transactions of the Royal Society B, 364, 1235–1243. doi:10.1098/rstb.2008.0310

    Google Scholar 

  • Barsalou, L. W. (2009). Simulation, situated conceptualization, and prediction. Philosophical Transactions of the Royal Society, B: Biological Sciences, 364, 1281–1289. doi:10.1093/acprof:oso/9780195395518.003.0016

    PubMed Central  Google Scholar 

  • Blakemore, S.-J., & Decety, J. (2001). From the perception of action to the understanding of intention. Nature Reviews Neuroscience, 2, 561–567. doi:10.1177/0956797612444612

    PubMed  Google Scholar 

  • Blakemore, S. J., Smith, J., Steel, R., Johnstone, E. C., & Frith, C. D. (2000). The perception of self-produced sensory stimuli in patients with auditory hallucinations and passivity experiences: Evidence for a breakdown in self-monitoring. Psychological Medicine, 30, 1131–1139. doi:10.1017/S0033291799002676

    PubMed  Google Scholar 

  • Bowers, K. S., Regehr, G., Balthazard, C. G., & Parker, K. (1990). Intuition in the context of discovery. Cognitive Psychology, 22, 72–110.

    Google Scholar 

  • Boyd, R., & Richerson, P. J. (1985). Culture and the evolutionary process. Chicago: University of Chicago Press.

    Google Scholar 

  • Bubic, A., Von Cramon, D. Y., & Schubotz, R. I. (2010). Prediction, cognition and the brain. Frontiers in Human Neuroscience, 4. doi:10.3389/fnhum.2010.00025

  • Buckner, R. L., & Carroll, D. C. (2007). Self-projection and the brain. Trends in Cognitive Sciences, 11, 49–57. doi:10.1016/j.tics.2006.11.004

    PubMed  Google Scholar 

  • Calvin, W. H. (1987). The brain as a darwinian machine. Nature, 330, 33–34.

  • Calvin, W. H. (2007). Why a creative brain? Evolutionary setups for off-line planning of coherent stages. In H. Cohen & B. Stemmer (Eds.), Consciousness and cognition: Fragments of mind and brain (pp. 115–126). Amsterdam: Elsevier.

  • Campbell, D. T. (1960). Blind variation and selective retention in creative thought as in other knowledge processes. Psychological Review, 67, 380–400.

    PubMed  Google Scholar 

  • Campbell, D. T. (1974). Unjustified variation and selective retention in scientific discovery. In F. Ayala & T. Dobszhansky (Eds.), Studies in the philosophy of biology: Reduction and related problems (pp. 139–161). London: Macmillan.

    Google Scholar 

  • Caramazza, A., & Mahon, B. Z. (2006). The organisation of conceptual knowledge in the brain: The future’s past and some future directions. Cognitive Neuropsychology, 23, 13–38.

    PubMed  Google Scholar 

  • Cisek, P. (2006). Integrated neural processes for defining potential actions and deciding between them: A computational model. The Journal of Neuroscience, 26, 9761–9770. doi:10.1523/JNEUROSCI.5605-05.2006

    PubMed  Google Scholar 

  • Cleeremans, A. (2008). The radical plasticity thesis. Progress in Brain Research, 168, 19–33. doi:10.3389/fpsyg.2011.00086

    PubMed  Google Scholar 

  • Colder, B. (2011). Emulation as an integrating principle for cognition. Frontiers in Human Neuroscience, 5, 1–12. doi:10.3389/fnhum.2011.0005

    Google Scholar 

  • Collins, A. M., & Loftus, E. F. (1975). A spreading activation theory of semantic processing. Psychological Review, 82, 407–428.

    Google Scholar 

  • Corallo, G., Sackur, J., Dehaene, S., & Sigman, M. (2008). Limits on introspection: Distorted subjective time during the dual-task bottleneck. Psychological Science, 19, 1110–1117. doi:10.1111/j.1467-9280.2008.02211.x

    PubMed  Google Scholar 

  • Cowan, N. (2001). The magical number 4 in short-term memory: A reconsideration of mental storage capacity. Behavioral and Brain Sciences, 24, 87–185.

    PubMed  Google Scholar 

  • Crick, F., & Koch, C. (2003). A framework for consciousness. Nature Neuroscience, 6, 119–126. doi:10.1038/nn0203-119

    PubMed  Google Scholar 

  • Dagher, A., Owen, A. M., Boecker, H., & Brooks, D. J. (1999). Mapping the network for planning: A PET activation study with the Tower of London task. Brain, 122, 1973–1987. doi:10.1093/brain/122.10.1973

    PubMed  Google Scholar 

  • Dasgupta, S. (2004). Is creativity a Darwinian process? Creativity Research Journal, 16, 403–413.

    Google Scholar 

  • Dehaene, S., Bossini, S., & Giraux, P. (1993). The mental representation of parity and number magnitude. Journal of Experimental Psychology: General, 122, 371–396.

    Google Scholar 

  • Dennett, D. C. (1995). Darwin’s’ dangerous idea. New York: Simon & Schuster.

    Google Scholar 

  • Dennett, D. C. (2004). Could there be a Darwinian account of human creativity? In A. Moya & E. Font (Eds.), Evolution, From Molecules to Ecosystems (pp. 273–279). Oxford: Oxford University Press.

    Google Scholar 

  • Diedrichsen, J., Verstynen, T., Hon, A., Zhang, Y., & Ivry, R. B. (2007). Illusions of force perception: The role of sensori-motor predictions, visual information, and motor errors. Journal of Neurophysiology, 97, 3305–3313. doi:10.1152/jn.01076.2006

    PubMed  Google Scholar 

  • Dienes, Z., & Perner, J. (1999). A theory of implicit and explicit knowledge. Behavioral and Brain Sciences, 5, 735–808.

    Google Scholar 

  • Dietrich, A. (2004a). Neurocognitive mechanisms underlying the experience of flow. Consciousness and Cognition, 13, 746–761. doi:10.1016/j.concog.2004.07.002

    PubMed  Google Scholar 

  • Dietrich, A. (2004b). The cognitive neuroscience of creativity. Psychonomic Bulletin & Review, 11, 1011–1026. doi:10.3758/BF03196731

    Google Scholar 

  • Dietrich, A. (2007). Who is afraid of a cognitive neuroscience of creativity? Methods, 42, 22–27. doi:10.1016/j.ymeth.2006.12.00

    PubMed  Google Scholar 

  • Dietrich, A., & Kanso, R. (2010). A review of EEG, ERP and neuroimaging studies of creativity and insight. Psychological Bulletin, 136, 822–848. doi:10.1037/a0019749

    PubMed  Google Scholar 

  • Downing, K. L. (2009). Predictive models in the brain. Connection Science, 21, 39–74. doi:10.1080/09540090802610666

    Google Scholar 

  • Ellamil, M., Dobson, C., Beeman, M., & Christoff, K. (2012). Evaluative and generative modes of thought during the creative process. NeuroImage, 59, 1783–1794.

    PubMed  Google Scholar 

  • Eysenck, H. J. (1993). Creativity and personality: Suggestions for a theory. Psychological Inquiry, 4, 147–178.

    Google Scholar 

  • Fisher, J. C. (2006). Does simulation theory really involve simulation? Philosophical Psychology, 19, 417–432. doi:10.1080/09515080600726377

    Google Scholar 

  • Friston, K. J., & Stephan, K. E. (2007). Free-energy and the brain. Synthese, 159, 417–458. doi:10.1007/s11229-007-9237-y

    PubMed Central  PubMed  Google Scholar 

  • Frith, C. D. (1992). The cognitive neuropsychology of schizophrenia. Hove: Lawrence Erlbaum.

    Google Scholar 

  • Gansler, D. A., Moore, D. W., Susmaras, T. M., & Jerram, M. W. (2011). Cortical morphology of visual creativity. Neuropsychologia, 49(9), 2527–2532. Retrieved from: http://www.sciencedirect.com/science/article/pii/S002839321100234X.

    PubMed  Google Scholar 

  • Geary, D. C., & Huffman, K. J. (2002). Brain and cognitive evolution: Forms of modularity and function of mind. Psychological Bulletin, 128, 667–698. doi:10.1037//0033-2909.128.5.667

    PubMed  Google Scholar 

  • Gibson, J. J. (1966). The senses considered as perceptual systems. Boston: Houghton Mifflin.

    Google Scholar 

  • Gibson, J. J. (1979). The ecological approach to visual perception. Boston: Houghton Mifflin.

    Google Scholar 

  • Gigerenzer, G., & Gaissmaier, W. (2011). Heuristic decision making. Annual Review of Psychology, 62, 451–482. doi:10.1146/annurev-psych-120709-145346

    PubMed  Google Scholar 

  • Glenberg, A. M., & Kaschak, M. P. (2002). Grounding language in action. Psychonomic Bulletin & Review, 9, 558–565. doi:10.3758/BF03196313

    Google Scholar 

  • Gluck, M., & Myers, C. (1989). Gateway to learning: An introduction to neural network modeling of the hippocampus and learning. Norwell, MA: Kluwer Academic Publishers.

    Google Scholar 

  • Goldman, A. (1995). Interpretation psychologized. In M. Davis & T. Stone (Eds.), Folk Psychology: The theory of mind debate (pp. 74–99). Cambridge: Blackwell.

    Google Scholar 

  • Green, A. E., Kraemer, D. J. M., Fugelsang, J. A., Gray, J. R., & Dunbar, K. N. (2012). Neural correlates of creativity in analogical reasoning. Journal of Experimental Psychology: Learning, Memory, and Cognition, 38(2), 264–272. doi:10.1037/a0025764

    PubMed  Google Scholar 

  • Gross, H., Heinze, A., Seiler, T., & Stephan, V. (1999). Generative character of perception: A neural architecture for sensorimotor anticipation. Neural Networks, 12, 1101–1129. doi:10.1016/S0893-6080(99)00047-7

    PubMed  Google Scholar 

  • Grush, R. (1997). The architecture of representation. Philosophical Psychology, 10, 5–23.

    Google Scholar 

  • Grush, R. (2004). The emulation theory of representation: Motor control, imagery, and perception. Behavioral and Brain Sciences, 27, 377–396. doi:10.1017/S0140525X04000093

    PubMed  Google Scholar 

  • Haider, H., Eichler, A., & Lange, T. (2011). An old problem: How can we distinguish between conscious and unconscious knowledge acquired in an implicit learning task. Consciousness and Cognition, 20, 658–672. doi:10.1016/j.concog.2010.10.021

    PubMed  Google Scholar 

  • Hassabis, D., & Maguire, E. A. (2009). The construction system of the brain. Philosophical Transactions of the Royal Society B, 364, 1263–1271. doi:10.1098/rstb.2008.0296

    Google Scholar 

  • Hawkins, J. (2004). On intelligence. New York: Henry Holt and Company.

    Google Scholar 

  • Helie, S., & Sun, R. (2010). Incubation, insight, and creative problem solving: A unified theory and a connectionist model. Psychological Review, 117, 994–1024. doi:10.1037/a001953

    PubMed  Google Scholar 

  • Hesslow, G. (2002). Conscious thought as simulation of behaviour and perception. Trends in Cognitive Sciences, 6, 242–247. doi:10.1016/S1364-6613(02)01913-7

    PubMed  Google Scholar 

  • Holroyd, C. B., & Coles, M. G. (2002). The neural basis of human error processing: Reinforcement learning, dopamine, and the error-related negativity. Psychological Review, 109, 679–708. doi:10.1037/0033-295X.109.4.679j

    PubMed  Google Scholar 

  • Hommel, B. (2009). Action control according to TEC (theory of event coding). Psychological Research, 73, 512–526. doi:10.1007/s00426-009-0234-2

    PubMed Central  PubMed  Google Scholar 

  • Hommel, B., & Eglau, B. (2002). Control of stimulus-response translation in dual-task performance. Psychological Research, 66, 260–273. doi:10.1007/s00426-002-0100-y

    PubMed  Google Scholar 

  • Hommel, B., Musseler, J., Aschersleben, G., & Prinz, W. (2001). The theory of event coding (TEC): A framework for perception and action planning. Behavioral and Brain Sciences, 24, 849–878.

    PubMed  Google Scholar 

  • Houk, J., Adams, J., & Barto, A. (1995). A model of how the basal ganglia generate and use neural signals that predict reinforcement. In J. Houk, J. Davis, & D. Beiser (Eds.), Models of information processing in the basal ganglia (pp. 249–270). Cambridge, MA: MIT Press.

    Google Scholar 

  • Humphrey, N. (2002). The mind made flesh: Frontiers of psychology and evolution. Oxford: Oxford University Press.

    Google Scholar 

  • Ingold, T. (2000). The poverty of selectionism. Anthropology Today, 16, 1–2. doi:10.1111/1467-8322.00022

    Google Scholar 

  • Ingold, T. (2007). The trouble with 'evolutionary biology'. Anthropology Today, 23, 13–17. doi:10.1111/j.1467-8322.2007.00497.x

    Google Scholar 

  • James, W. (1890). Principles of Psychology. New York: Holt.

    Google Scholar 

  • Jauk, E., Benedek, M., & Neubauer, A. C. (2012). Tackling creativity at its roots: Evidence for different patterns of EEG α activity related to convergent and divergent modes of task processing. International Journal of Psychphysiology, 84(2), 219–225. doi:10.1016/j.ijpsycho.2012.02.012

    Google Scholar 

  • Johnson-Laird, P. N., & Byrne, R. M. J. (2009). “If” and the problem of conditional reasoning. Trends in Cognitive Sciences, 13, 282–287. doi:10.1016/j.tics.209.04.003

    PubMed  Google Scholar 

  • Jung, R. E., Mead, B. S., Carrasco, J., & Flores, R. A. (2013). The structure of creative cognition in the human brain. Frontiers in Human Neuroscience, 7, 330.

    PubMed Central  PubMed  Google Scholar 

  • Kawato, M., & Wolpert, D. (1998). Internal models for motor control. Sensory Guidance of Movement, 218, 291–307. doi:10.1016/S0959-4388(99)00028-8

    Google Scholar 

  • Kent, C., & Lamberts, K. (2008). The encoding–retrieval relationship: retrieval as mental simulation. Trends in Cognitive Sciences, 12, 92–98. doi:10.1016/j.tics.2007.12.004

    PubMed  Google Scholar 

  • Kiefer, M., Sim, E.-J., Herrnberger, B., Grothe, J., & Hoenig, K. (2008). The sound of concepts: Four markers for a link between auditory and conceptual brain systems. The Journal of Neuroscience, 28, 12224–12230.

    PubMed  Google Scholar 

  • Köhler, I. (1951). Über Aufbau und Wandlungen der Wahrnehmungswelt. Insbesondere über bedingte Empfindungen. Wien: Rohrer.

    Google Scholar 

  • Kronfeldner, M. E. (2010). Darwinian “blind” hypothesis formation revisited. Synthese, 175, 193–218. doi:10.1007/s11229-009-9498

    Google Scholar 

  • Lakoff, G., & Johnson, M. (1999). Philosophy in the Flesh. New York: Basic Books.

    Google Scholar 

  • Lau, H. (2008). A higher order Bayesian decision theory of consciousness. In R. Banerjee & B.K. Chakrabarti (Eds.), Progress in Brain Science, 168, 37-48.

  • Lewontin, R. C. (1970). The units of selection. Annual Review of Ecology and Systematics, 1, 1–18.

    Google Scholar 

  • Llinás, R. R. (2001). I of the vortex: From neurons to self. Boston: MIT Press.

    Google Scholar 

  • Llinás, R. R., & Roy, S. (2009). The ‘prediction imperative’ as the basis for self-awareness. Philosophical Transactions of the Royal Society B, 364, 1301–1307. doi:10.1098/rstb.2008.0309

    Google Scholar 

  • Marr, D. (1982). Vision: a computational approach. San Fransisco, CA: Freeman & Company.

    Google Scholar 

  • Martindale, C. (1990). The clockwork muse: The predictability of artistic change. New York: Basic Books.

    Google Scholar 

  • Martindale, C. (1999). Darwinian, Lamarckian, and rational creativity. Psychological Inquiry, 10, 340–341.

    Google Scholar 

  • Mehta, B., & Schaal, S. (2002). Forward models in visuomotor control. Journal of Neurophysiology, 88, 942–953.

    PubMed  Google Scholar 

  • Mesoudi, A., Whiten, A., & Laland, K. N. (2006). Towards a unified science of cultural evolution. Behavioural and Brain Sciences, 29, 329–383. doi:10.1017/S0140525X06009083

    Google Scholar 

  • Meyer, W. U., Reisenzein, R., & Schützwohl, A. (1997). Toward a process analysis of emotions: The case of surprise. Motivation and Emotion, 21, 251–274. doi:10.1023/A:1024422330338

    Google Scholar 

  • Michelson, A. A., & Morley, E. W. (1887). On the relative motion of the earth and the luminiferous ether. American Journal of Science, 34, 333–345.

    Google Scholar 

  • Miller, E. K., & Cohen, J. D. (2001). An integrative theory of prefrontal cortex function. Annual Review of Neuroscience, 24, 167–202. doi:10.1146/annurev.neuro.24.1.167

    PubMed  Google Scholar 

  • Moulton, S. T., & Kosslyn, S. M. (2009). Imagining predictions: Mental imagery as mental emulation. Philosophical Transactions of the Royal Society B, 364, 1273–1280. doi:10.1098/rstb.2008.0314

    Google Scholar 

  • Mumford, M. D. (1999). Blind variation or selective variation? Evaluative elements in creative thought. Psychological Inquiry, 10, 344–348.

    Google Scholar 

  • Niedenthal, P. M., Barsalou, L. W., Winkielman, P., Krauth-Gruber, S., & Ric, F. (2005). Embodiment in attitudes, social perception, and emotion. Personality and Social Psychology Review, 9, 184–211. doi:10.1207/s15327957pspr0903_1

    PubMed  Google Scholar 

  • O’Reagan, J. K., & Noë, A. (2001). A sensorimotor account of vision and visual consciousness. Behavioural and Brain Sciences, 24, 939–1031.

    Google Scholar 

  • Perkins, D. N. (1994). Creativity: Beyond the Darwinian paradigm. In M. A. Boden (Ed.), Dimensions of creativity (pp. 119–142). Cambridge, MA: MIT Press.

    Google Scholar 

  • Perruchet, P., Cleeremans, A., & Destrebecqz, A. (2006). Dissociating the effects of automatic activation and explicit expectancy on reaction times in a simple associative learning task. Journal of Experimental Psychology: Learning, Memory, and Cognition, 32, 955–965.

    PubMed  Google Scholar 

  • Perruchet, P., & Vinter, A. (2002). The self-organizing consciousness. Behavioral and Brain Sciences, 25, 297–388. doi:10.1037/0278-7393.32.5.955

    PubMed  Google Scholar 

  • Pezzulo, G., Butz, M. V., Castelfranchi, C., & Falcone, R. (Eds.). (2008). Anticipation in natural and artificial cognition. In G. Pezzulo, M. Butz, C. Castelfranchi, The challenge of anticipation: A unifying framework for the analysis and design of artificial cognitive systems, (pp.3-22). New York: Springer.

  • Pinker, S. (2002). The blank slate. New York: Penguin.

    Google Scholar 

  • Popper, K. R. (1972). Objective knowledge: An evolutionary approach. Oxford: Clarendon Press.

    Google Scholar 

  • Popper, K. R. (1974). Campbell on the evolutionary theory of knowledge. In P. A. Schilpp (Ed.), The philosophy of Karl Popper (pp. 1059–1065). LaSalle: Open Court.

    Google Scholar 

  • Popper, K. R. (1984). Evolutionary Epistemology. In J. W. Pollard (Ed.), Evolutionary theory: Paths into the future (pp. 239–255). New York: Wiley.

    Google Scholar 

  • Prinz, W. (1987). Ideo-motor action. In H. Heur & A. F. Sanders (Eds.), Perspectives on perception and action (pp. 47–76). Hillsdale, NJ: Erlbaum.

    Google Scholar 

  • Prinz, W. (1997). Perception and action planning. European Journal of Cognitive Psychology, 9, 129–154.

    Google Scholar 

  • Ramachandran, V. S. (1992). Blind spots. Scientific American, 266, 86–91.

    PubMed  Google Scholar 

  • Rao, R. P., & Ballard, D. H. (1999). Predictive coding in the visual cortex: A functional interpretation of some extra-classical receptive-field effects. Nature Neuroscience, 2, 79–87. doi:10.1038/4580

    PubMed  Google Scholar 

  • Read, D. W. (2006). Cultural evolution is not equivalent to Darwinian evolution. Behavioral and Brain Sciences, 29, 361. doi:10.1017/S0140525X0638908X

    Google Scholar 

  • Reber, A. S. (1996). Implicit leaning and tacit knowledge: An essay on the cognitive unconscious. Oxford: Oxford University Press.

    Google Scholar 

  • Reed, C. L., & Farah, M. J. (1995). The psychological reality of the body schema: A test with normal participants. Journal of Experimental Psychology: Human Perception & Performance, 21, 334–343. doi:10.1037/0096-1523.21.2.334

    Google Scholar 

  • Rescorla, R. A., & Wagner, A. R. (1972). A theory of Pavlovian conditioning: Variations in the effectiveness of reinforcement and nonreinforcement. In A. H. Black & W. F. Prokasy (Eds.), Classical Conditioning II: Current research and theory (pp. 64–99). New York: Appleton Century Crofts.

    Google Scholar 

  • Richerson, P. J., & Boyd, R. (2005). Not by genes alone: How culture transformed human evolution. Chicago: University of Chicago Press.

    Google Scholar 

  • Rosenthal, D. (2005). Consciousness and Mind. New York: Oxford University Press.

    Google Scholar 

  • Russ, S. W. (1999). An evolutionary model for creativity: Does it fit? Psychological Inquiry, 10, 359–361.

    Google Scholar 

  • Ruz, M., & Lupiáñez Castillo, J. (2002). A review of attentional capture: On its automaticity and sensitivity to endogenous control. Psicológica: Revista de Metodología y Psicología Experimental, 23, 283–310.

    Google Scholar 

  • Sawyer, K. (2011). The cognitive neuroscience of creativity: A critical review. Creativity Research Journal, 23, 137–154.

    Google Scholar 

  • Schacter, D. L., & Addis, D. R. (2007). The cognitive neuroscience of constructive memory: remembering the past and imagining the future. Philosophical Transactions of the Royal Society B, 362, 773–786. doi:10.1098/rstb.2007.2087

    Google Scholar 

  • Schacter, D. L., & Buckner, R. L. (1998). On the relationship among priming, conscious recollection, and intentional retrieval: Evidence from neuroimaging research. Neurobiology of Learning and Memory, 70, 284–303.

    PubMed  Google Scholar 

  • Schooler, J. W., & Dougal, S. (1999). Why creativity is not like the proverbial typing monkey. Psychological Inquiry, 10, 351–356.

    Google Scholar 

  • Schubotz, R. I. (2007). Prediction of external events with our motor system: Towards a new framework. Trends in Cognitive Sciences, 11, 211–218. doi:10.1016/j.tics.2007.02.006

    PubMed  Google Scholar 

  • Schultz, W. (2000). Multiple reward signals in the brain. Neuroscience, 1, 199–207. doi:10.1038/35044563

    PubMed  Google Scholar 

  • Shanks, D. R. (2005). Implicit Learning. In K. Lamberts & R. Goldstone (Eds.), Handbook of Cognition (pp. 202–220). London: Sage Publication.

    Google Scholar 

  • Shapiro, L. (2007). The embodied research program. Philosophy Compass, 2(2), 338–346. doi:10.1111/j.1747-9991.2007.00064.x

    Google Scholar 

  • Shen, W. B., Liu, C., & Chen, J. J. (2010). Neural basis of creativity: Evidence from structural and functional imaging. Advances in Psychological Science. Retrieved from: http://en.cnki.com.cn/Article_en/CJFDTOTAL-XLXD201009009.htm

  • Shin, Y. K., Proctor, R. W., & Capaldi, E. J. (2010). A review of contemporary ideomotor theory. Psychological Bulletin, 136, 943–974. doi:10.1037/a0020541

    PubMed  Google Scholar 

  • Simons, D. J., & Chabris, C. F. (1999). Gorillas in our midst – sustained inattentional blindness for dynamic events. Perception, 28, 1059–1074. doi:10.1068/p2952

    PubMed  Google Scholar 

  • Simonton, D. K. (1997). Creative productivity: A predictive and explanatory model of career trajectories and landmarks. Psychological Review, 104, 66–89.

    Google Scholar 

  • Simonton, D. K. (1999). Creativity as blind variation and selective retention: is the creative process Darwinian? Psychological Inquiry, 10, 309–328.

    Google Scholar 

  • Simonton, D. K. (2003). Scientific creativity as constrained stochastic behavior: The integration of process and person perspectives. Psychological Bulletin, 129, 475–494.

    PubMed  Google Scholar 

  • Simonton, D. K. (2007). The creative process in Picasso’s Guernica sketches: Monotonic improvements or nonmonotonic variants. Creativity Research Journal, 19, 329–344. doi:10.1080/10400410701753291

    Google Scholar 

  • Sio, U. N., & Ormerod, T. C. (2009). Does incubation enhance problem solving: A meta-analytic review. Psychological Bulletin, 135, 94–120. doi:10.1037/a0014212

    PubMed  Google Scholar 

  • Sternberg, R. J. (1998). Cognitive mechanisms in human creativity: Is variation blind or sighted? Journal of Creative Behavior, 32, 159–176. doi:10.1002/j.2162-6057.1998.tb00813.x

    Google Scholar 

  • Sternberg, R. J. (1999). Darwinian creativity as a conventional religious faith. Psychological Inquiry, 10, 357–359.

    Google Scholar 

  • Takeuchi, H., Taki, Y., Hashizume, H., Sassa, Y., Nagase, T., Nouchi, R., & Kawashima, R. (2011). Failing to deactivate: The association between brain activity during a working memory task and creativity. NeuroImage, 55(2), 681–687. doi:10.1016/j

    PubMed  Google Scholar 

  • Taylor, S. F., Stern, E. R., & Gehring, W. J. (2007). Neural systems for error monitoring: Recent findings and theoretical perspectives. The Neuroscientist, 13, 162–172. doi:10.1177/1073858406298184

    Google Scholar 

  • Tennebaum, J. B., Kemp, C., Griffiths, T. L., & Goodman, N. D. (2011). How to grow a mind: Statistics, structure and abstraction. Science, 331, 1279–1285. doi:10.1126/science.1192788

    Google Scholar 

  • Thomas, L. E., & Lleras, A. (2009). Swinging into thought: Directed movement guides insight in problem solving. Psychonomic Bulletin & Review, 16, 719–723.

    Google Scholar 

  • Tomasello, M. (1999). The cultural origins of human cognition. Cambridge, MA: Harvard University Press.

    Google Scholar 

  • Ward, T. B., Smith, S. M., & Finke, R. A. (1999). Creative cognition. In R. J. Sternberg (Ed.), Handbook of Creativity, (pp. 189-212). Cambridge University Press.

  • Wegner, D. M. (2003). The mind’s best trick: How we experience conscious will. Trends in Cognitive Sciences, 7, 65–69. doi:10.1016/S1364-6613(03)00002-0

    PubMed  Google Scholar 

  • Whittlesea, B. W. A. (2002). False memory and the discrepancy-attribution hypothesis: The prototype-familiarity illusion. Journal of Experimental Psychology: General, 131, 96–115.

    Google Scholar 

  • Wilbert, J., & Haider, H. (2010). The subjective experience of committed errors and the discrepancy-attribution hypothesis. Acta Psychologica, 139, 370–381. doi:10.1016/j.actpsy.2011.11.010

    Google Scholar 

  • Willingham, D. B. (1999). Implicit motor sequence learning is not purely perceptual. Memory Cognition, 27, 561–572. doi:10.3758/BF03211549

    PubMed  Google Scholar 

  • Wilson, A. D., & Golonka, S. (2013). Embodied cognition is not what you think it is. Frontiers in Psychology: Cognitive Science, 4, 1–12.

    Google Scholar 

  • Wolpert, D. M., Doya, K., & Kawato, M. (2003). A unifying computational framework for motor control and social interaction. Philosophical Transactions of the Royal Society Series B, 358, 593–602. doi:10.1098/rstb.2002.1238

    Google Scholar 

  • Wolpert, D. M., & Ghahramani, Z. (2000). Computational principles of movement neuroscience. Nature Neuroscience, 3, 1212–1228.

    PubMed  Google Scholar 

  • Wolpert, D. M., Ghahramani, Z., & Jordan, M. I. (1995). An internal model for sensorimotor integration. Science, 269, 1880–1882. doi:10.1126/science.7569931

    PubMed  Google Scholar 

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Dietrich, A., Haider, H. Human creativity, evolutionary algorithms, and predictive representations: The mechanics of thought trials. Psychon Bull Rev 22, 897–915 (2015). https://doi.org/10.3758/s13423-014-0743-x

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