Dual-process models of cognition suggest that there are two types of thought: autonomous Type 1 processes and working memory dependent Type 2 processes that support hypothetical thinking. Models of creative thinking also distinguish between two sets of thinking processes: those involved in the generation of ideas and those involved with their refinement, evaluation, and/or selection. Here we review dual-process models in both these literatures and delineate the similarities and differences. Both generative creative processing and evaluative creative processing involve elements that (...) have been attributed to each of the dual processes of cognition. We explore the notion that creative thinking may rest upon the nature of a shifting process between Type 1 and Type 2 dual processes. We suggest that a synthesis of the evidence bases on dual-process models of cognition and of creative thinking, together with developing time-based approaches to explore the shifting process, could better inform the development of i.. (shrink)

Semantic memory plays a role in the creative process, either as an integral component or as the basis upon which executive functions operate on. Yet, due to the challenge of representing semantic memory, the relationship between semantic memory and creativity has not been thoroughly investigated. In recent years, computational network science tools are increasingly being applied at the cognitive level to examine language and memory systems. Network science is based on mathematical graph theory, providing quantitative methods to investigate complex systems (...) as networks. Here, a series of semantic network studies aimed at investigating different facets of creativity in low- and high-creative individuals will be reviewed. These studies include representing their structure of semantic memory, simulating uncontrolled search processes over their semantic memory, examining the relation of semantic memory structure to creative achievement and fluid intelligence, and relating flexibility of thought to the robustness of their semantic networks to attack. Finally, a general theory relating semantic memory structure to typical and atypical semantic processing will be presented and its relation to individual differences in creativity will be discussed. These studies demonstrate how the role of semantic memory in creativity can be investigated via quantitative measures of connectivity, distance, and structure of semantic networks. Thus, the application of network science tools to study creativity provides a quantitative and direct investigation of theories on creativity. Importantly, network science offers powerful tools in quantitatively studying different facets of high-level cognitive constructs such as creativity. (shrink)

Stawarczyk, Bezdek, and Zacks offer neuroscience evidence for a midline default network core, which appears to coordinate internal, top‐down mentation with externally‐triggered, bottom‐up attention in a push‐pull relationship. The network may enable the flexible pursuance of thoughts tuned into or detached from the current environment.

The associative theory of creativity states that creativity is associated with differences in the structure of semantic memory, whereas the executive theory of creativity emphasises the role of top-down control for creative thought. For a powerful test of these accounts, individual semantic memory structure was modelled with a novel method based on semantic relatedness judgements and different criteria for network filtering were compared. The executive account was supported by a correlation between creative ability and broad retrieval ability. The associative account (...) was independently supported, when network filtering was based on a relatedness threshold, but not when it was based on a fixed edge number or on the analysis of weighted networks. In the former case, creative ability was associated with shorter average path lengths and higher clustering of the network, suggesting that the semantic networks of creative people show higher small-worldness. (shrink)

According to Mednick’s (1962) theory of individual differences in creativity, creative individuals appear to have a richer and more flexible associative network than less creative individuals. Thus, creative individuals are characterized by “flat” (broader associations) instead of “steep” (few, common associations) associational hierarchies. To study these differences, we implement a novel computational approach to the study of semantic networks, through the analysis of free associations. The core notion of our method is that concepts in the network are related to each (...) other by their association correlations - overlap of similar associative responses (“association clouds”). We began by collecting a large sample of participants who underwent several creativity measurements and used a decision tree approach to divide the sample into low and high creative groups. Next, each group underwent a free association generation paradigm which allowed us to construct and analyze the semantic networks of both groups. Comparison of the semantic memory networks of persons with low creative ability and persons with high creative ability revealed differences between the two networks. The semantic memory network of persons with low creative ability seems to be more rigid, compared to the network of persons with high creative ability, in the sense that it is more spread out and breaks apart into more sub-parts. We discuss how our findings are in accord and extend Mednick’s (1962) theory and the feasibility of using network science paradigms to investigate high level cognition. (shrink)