Exploring Neural Signal Complexity as a Potential Link between Creative Thinking, Intelligence, and Cognitive Control

Abstract

Functional connectivity studies have demonstrated that creative thinking builds upon an interplay of multiple neural networks involving the cognitive control system. Theoretically, cognitive control has generally been discussed as the common basis underlying the positive relationship between creative thinking and intelligence. However, the literature still lacks a detailed investigation of the association patterns between cognitive control, the factors of creative thinking as measured by divergent thinking (DT) tasks, i.e., fluency and originality, and intelligence, both fluid and crystallized. In the present study, we explored these relationships at the behavioral and the neural level, based on N = 77 young adults. We focused on brain-signal complexity (BSC), parameterized by multi-scale entropy (MSE), as measured during a verbal DT and a cognitive control task. We demonstrated that MSE is a sensitive neural indicator of originality as well as inhibition. Then, we explore the relationships between MSE and factor scores indicating DT and intelligence. In a series of across-scalp analyses, we show that the overall MSE measured during a DT task, as well as MSE measured in cognitive control states, are associated with fluency and originality at specific scalp locations, but not with fluid and crystallized intelligence. The present explorative study broadens our understanding of the relationship between creative thinking, intelligence, and cognitive control from the perspective of BSC and has the potential to inspire future BSC-related theories of creative thinking.

Is Flexibility More than Fluency and Originality?

“…In Bamberg and Ulm, the test battery included five hours of testing and a variety of further covariates (e.g., the broad measurement of crystallized intelligence, insight tasks, personality, etc. (for a comprehensive list, see Weiss et al 2021a )), while the test battery in Greifswald only included the creativity tasks and some intelligence indicators as this study was complemented by an EEG measurement ( Kaur et al 2020 , 2021 ). The five-hour testing included various small and larger breaks to prevent fatigue.…”

Toward greater computational modeling in neurocognitive creativity research.

“…Meanwhile, research into the link between creative cognition and intelligence has found considerable overlap between the two in terms of lab-based performance (Frith, Elbich, et al, 2021; Karwowski et al, 2016, 2020) and suggests that they may depend on shared neural regions (Benedek et al, 2018; Frith, Elbich, et al, 2021). Research has also examined relationships between creativity and executive functions, finding that switching (Krumm et al, 2018; Nusbaum & Silvia, 2011; Pan & Yu, 2018; Zabelina & Ganis, 2018), updating (Benedek, Jauk, et al, 2014; Stolte et al, 2020; Zabelina et al, 2019), and inhibition (Camarda, Borst, et al, 2018; Kaur et al, 2021; Zabelina et al, 2019) all relate to aspects of creative performance.…”

“…Less original and distracting ideas require suppression Chrysikou, 2018;Lloyd-Cox et al, 2021). Inhibition relates to creative ability (Benedek et al, 2012;Kaur et al, 2021).…”

Multimodal Brain Signal Complexity Predicts Human Intelligence

“…Sufficient complexity of neural signals was hypothesized to constitute the basis for efficient neural communication (de Pasquale et al, 2016) and higher complexity was related to increased information processing capacity (Heisz and McIntosh, 2013). Further, individual variations in brain signal complexity have been associated with differences in creativity (Kaur et al, 2021), the genetic risk for psychological diseases (Li et al, 2008), and also with differences in intelligence (Dreszer et al, 2020;Lutzenberger et al, 1992). However, acrossstudy findings on relations between individual differences in intelligence and intrinsic brain signal complexity are heterogeneous.…”