2015
DOI: 10.3758/s13423-015-0925-1
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Toward an evolutionary-predictive foundation for creativity

Abstract: Dietrich and Haider (Psychonomic Bulletin & Review, 21 (5), 897-915, 2014) justify their integrative framework for creativity founded on evolutionary theory and prediction research on the grounds that Btheories and approaches guiding empirical research on creativity have not been supported by the neuroimaging evidence.^Although this justification is controversial, the general direction holds promise. This commentary clarifies points of disagreement and unresolved issues, and addresses mis-applications of evol… Show more

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Cited by 12 publications
(16 citation statements)
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“…Our investigation of cortical responses focused on the PFC, which has been previously reported as a higher-order neural network and is shown to be involved in musical and other types of creativity 10,13,1618 . The PFC is functionally subdivided on the underlying cytoarchitecture defined by BA; each area may contribute independent elements of the creative process 13,34 .…”
Section: Discussionmentioning
confidence: 99%
“…Our investigation of cortical responses focused on the PFC, which has been previously reported as a higher-order neural network and is shown to be involved in musical and other types of creativity 10,13,1618 . The PFC is functionally subdivided on the underlying cytoarchitecture defined by BA; each area may contribute independent elements of the creative process 13,34 .…”
Section: Discussionmentioning
confidence: 99%
“…The ABM used here, referred to as "EVOlution of Culture", abbreviated EVOC, is a model of cultural evolution that uses neural network based agents that (1) invent new ideas, (2) imitate actions implemented by neighbors, (3) evaluate ideas, and (4) implement successful ideas as actions (Gabora, 2008a). 2 EVOC was used because it is amenable to testing the above hypotheses concerning creativity; discussion of general questions about how culture evolves including comparison with other approaches (e.g., Boyd & Richerson, 1985) can be found elsewhere (Gabora, 2008b(Gabora, , 2011(Gabora, , 2013Gabora & Kauffman, 2016). The approach is consistent with a growing effort in cognitive science to leverage computer modeling techniques and knowledge of cognition to understand aggregate social outcomes (Goldstone & Gureckis, 2009).…”
Section: The Computational Modelmentioning
confidence: 99%
“…Haider and Frensch (1999), Wagner et al (2004), Gaschler et al (2013), Haider et al (2013), Dietrich and Haider (2015) have been pursuing the idea that during learning of skills there are such transitions. They used for example the number reduction task (Wagner et al, 2004).…”
Section: Stage 2: Coherence Detectionmentioning
confidence: 99%
“…For the tumor problem restructuring requires a broad associative search with a high variation rate (Hélie and Sun, 2010). Importantly, the search process is not blind, but guided by constraints which are stated by the instruction and the goal representation which is strongly tied to the concept of “skin” (Dietrich and Haider, 2015). New associations are possible and a state of balance between the given concepts could be attained.…”
Section: Examples and Generalizationmentioning
confidence: 99%