Network neuroscience of creative cognition: mapping cognitive mechanisms and individual differences in the creative brain

Beaty, Roger E.; Seli, Paul; Schacter, Daniel L.

doi:10.1016/j.cobeha.2018.08.013

Cited by 222 publications

(168 citation statements)

References 61 publications

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“…Thus, the complex trait of creativity emerges from large-scale neural assemblies working in synchrony during the time of heightened creativity. In this line, a review by Beaty et al (2019) elaborated on the creative network dynamics and demonstrated that the executive and default mode networks can reliably predict creative thinking ability of individuals. They argued that creativity is a result of the interaction between associative and executive processes.…”

Section: Global and Local Neurophysiological Explanations Of Creativitymentioning

confidence: 99%

What Does Temporal Brain Signal Complexity Reveal About Verbal Creativity?

Kaur

Ouyang

Sommer

et al. 2020

Front. Behav. Neurosci.

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Recent empirical evidence reveals that creative idea generation builds upon an interplay of multiple neural networks. Measures of temporal complexity yield important information about the underlying mechanisms of these co-activated neural networks. A few neurophysiological studies investigated brain signal complexity (BSC) during the production of creative verbal associations and resting states, aiming to relate it with creative task performance. However, it is unknown whether the complexity of brain signals can distinguish between productions of typical and original verbal associations. In the present study, we investigated verbal creativity with multiscale entropy (MSE) of electroencephalography (EEG) signals, which quantifies complexity over multiple timescales, capturing unique dynamic features of neural networks. MSE was measured in verbal divergent thinking (DT) states while emphasizing on producing either typical verbal associations or original verbal associations. We hypothesized that MSE differentiates between brain states characterizing the production of typical and original associations and is a sensitive neural marker of individual differences in producing original associations. Results from a sample of N = 92 young adults revealed slightly higher average MSE for original as compared with typical association production in small and medium timescales at frontal electrodes and slightly higher average MSE for typical association production in higher timescales at parietal electrodes. However, measurement models failed to uncover specificity of individual differences as MSE in typical vs. original associations was perfectly correlated. Hence, individuals with higher MSE in original association condition also exhibit higher MSE during the production of typical associations. The difference between typical and original association MSE was not significantly associated with human-rated originality of the verbal associations. In sum, we conclude that MSE is a potential marker of creative verbal association states, but replications and extensions are needed, especially with respect to the brain-behavior relationships.

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Section: Global and Local Neurophysiological Explanations Of Creativitymentioning

confidence: 99%

What Does Temporal Brain Signal Complexity Reveal About Verbal Creativity?

Kaur

Ouyang

Sommer

et al. 2020

Front. Behav. Neurosci.

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“…The key role of specific structural links between neuronal populations for the global stability of cortex was investigated; the relation between experimentally observed activity and anatomical structure was explained (Schuecker et al, 2017). The connectome prediction method has been used to evaluate the ability of creative thinking from the patterns of brain connectivity at rest and during tasks, indicating that the variation in brain-network connectivity presents a trustworthy biomarker of the ability in creative thinking (Beaty et al, 2019). A connectome-based hybrid model for the brain network was developed from diffusionweighted Magnetic Resonance Imaging (MRI) tractography and region parcellations from anatomical MRI.…”

Section: Brain Association Graph Brain Network the Connectome Andmentioning

confidence: 99%

“…Cognitive processes about network interactions during creative performance have been identified and they are: Internally focused attention, prepotent-response inhibition, and goaldirected memory retrieval. Correlational research using prediction modeling shows that functional connectivity between networks enables to predict an individual's ability in creative thinking (Beaty et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

Progress and Challenges of Neuroscience and Brain-inspired Artificial Intelligence

Wang¹,

Alexander²

2019

Neuroscience International

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Neuroscience and brain-inspired artificial intelligence are significant research areas. Many countries have launched brain-related projects in which neuroscience and brain-inspired artificial intelligence are major targeted areas to increase national interests and enhance their strength in key areas such as military and homeland security in the competitive global world. Methods, emerging technologies, and progress in neuroscience and brain-inspired artificial intelligence are introduced in this paper that specifically include brain-inspired computing, brain association graph, brain networks, the connectome, brain reconstruction, imaging technologies used for the brain, chips and devices inspired by the human brain, brain-computer interface or brain-machine interfaces, cyborg, neuro-robotics, and quantum robotics. Challenges in some of the topics are also presented and discussed.

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“…Previous studies have revealed that creativity is a complex construct that requires the involvement of various brain functions such as memory, future simulation, semantic processing, and attention. Besides, recent neuroimaging studies of creativity have suggested the involvement of multiple brain networks, including the following: the default mode network (DN), the executive control network (ECN), and the salience network (SN) (Beaty et al, 2016(Beaty et al, , 2017(Beaty et al, , 2019Yeh et al, 2019;Girn et al, 2020). The relationship between divergent thinking and brain regions within the DN has been reported in several fMRI studies (Fink et al, 2010;Takeuchi et al, 2012;Gonen-Yaacovi et al, 2013;Beaty et al, 2014;Wei et al, 2014).…”

Section: Introductionmentioning

confidence: 99%

Effects of Transcranial Direct Current Stimulation on Brain Networks Related to Creative Thinking

Koizumi

Ueda

Nakao

2020

Front. Hum. Neurosci.

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Human creative thinking is unique and capable of generating novel and valuable ideas. Recent research has clarified the contribution of different brain networks (default mode network, DN; executive control network; salience network) to creative thinking. However, the effects of brain stimulation on brain networks during creative thinking and on creative performance have not been clarified. The present study was designed to examine the changes in functional connectivity (FC) and effective connectivity (EC) of the largescale brain network, and the ensuing changes in creative performance, induced by transcranial direct current stimulation (tDCS). Fourteen healthy male students underwent two tDCS sessions, one with actual stimulation and one with sham stimulation, on two separate days. Participants underwent tDCS (anode over the left dorsolateral prefrontal cortex, DLPFC; cathode over the right inferior parietal lobule, IPL) for 20 min. Before and after the tDCS session, electroencephalography signals were acquired from 32 electrodes over the whole head during the creative thinking task. On FC analysis, the delta band FC between the posterior cingulate cortex and IPL significantly increased only after real stimulation. We also found that the change of flexibility score was significantly correlated with the change in: (i) delta band FC between mPFC and left lateral temporal cortex (LTC) and (ii) alpha band FC between IPL and right LTC. On EC analysis, decreased flow within the DN (from left LTC to right IPL) was observed. Our results reveal that tDCS could affect brain networks, particularly the DN, during creative thinking and modulate key FC in the generation of flexible creative ideas.

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Network neuroscience of creative cognition: mapping cognitive mechanisms and individual differences in the creative brain

Cited by 222 publications

References 61 publications

What Does Temporal Brain Signal Complexity Reveal About Verbal Creativity?

What Does Temporal Brain Signal Complexity Reveal About Verbal Creativity?

Progress and Challenges of Neuroscience and Brain-inspired Artificial Intelligence

Effects of Transcranial Direct Current Stimulation on Brain Networks Related to Creative Thinking

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