The Longer One Thinks, the More Creative? Exploring the Neural Mechanisms Behind the Temporal Effect
Poster No:
787
Submission Type:
Abstract Submission
Authors:
Yuanyun He1, Jiabao Lin1
Institutions:
1Guangzhou University of Chinese Medicine, Guangzhou, Guangdong
First Author:
Co-Author:
Introduction:
Divergent thinking (DT) refers to the ability to generate multiple creative ideas within a certain time frame (Kuang et al., 2022). Time is one of the key influencing factors of divergent thinking (Baer & Oldham, 2006; Jia & Zeng, 2021; Rominger et al., 2022). As the allotted task time changes, the performance of divergent thinking may be dominated by different cognitive components (Maillet et al., 2019; Paek et al., 2021; Yuan et al., 2021). Short-duration tasks may involve more rapid information processing and intuitive responses, linked to swift cognitive processing capabilities (Oh-Descher et al., 2017). Long-duration tasks likely involve deeper cognitive processing, such as memory retrieval and information integration, characterized by more deliberate contemplation (Oh-Descher et al., 2017). Many studies have explored the neural mechanisms underlying divergent thinking through various tasks (Kuang et al., 2022). However, there is no consensus on whether short-duration and long-duration processing tasks involve different cognitive components and are supported by unique neural mechanisms.
Methods:
Relevant literature from 2000 to 2024 was reviewed under the guidance of the PRISMA flow diagram (Page et al., 2020). We searched in the PubMed, Elsevier, Web of Science, SAGE, Oxford Press Wiley, and Springer databases with keywords involving (creativity OR creative performance OR creative thinking OR creative ability OR creativity test OR divergent thinking OR creative product OR creative production OR idea generation OR original idea) AND (fMRI, functional magnetic resonance imaging), yielded 1457 studies. After selection and exclusion, a total of 36 studies were included, including 17 studies for short-duration DT and 19 studies for long-duration DT. The detailed screening process is shown in Figure 1.
We used GingerALE 3.0.2 to perform the meta-analysis. In the single analyses for short-duration and long-duration DT, we choose the cluster-level family-wise error correction of p＜0.05, corrected for multiple comparisons (3000 permutations) with a cluster forming threshold of p＜0.001 (Müller et al., 2017). Then, we carried out two contrast analyses (i.e., Short＞Long and Long＞Short) and a conjunction analysis (i.e., Short∩Long). The parameters were set as follows: a cluster forming threshold of p＜0.01 was used with a 3000 times permutation, and the minimum cluster size was 100 mm³.
We used GingerALE 3.0.2 to perform the meta-analysis. In the single analyses for short-duration and long-duration DT, we choose the cluster-level family-wise error correction of p＜0.05, corrected for multiple comparisons (3000 permutations) with a cluster forming threshold of p＜0.001 (Müller et al., 2017). Then, we carried out two contrast analyses (i.e., Short＞Long and Long＞Short) and a conjunction analysis (i.e., Short∩Long). The parameters were set as follows: a cluster forming threshold of p＜0.01 was used with a 3000 times permutation, and the minimum cluster size was 100 mm³.
·Figure 1
Results:
In the single analyses, three brain clusters were significantly activated in the short-duration DT, including inferior parietal lobe (IPL)/postcentral gyrus (PoCG), middle frontal gyrus (MFG)/inferior frontal gyrus (IFG) and caudate. The ALE analysis indicated three significantly activated clusters in the long-duration DT: superior frontal gyrus (SFG)/medial frontal gyrus (MedFG), IPL/PoCG and cuneus (CUN)/lingual gyrus (LG). In the contrast analyses (see figure 2-1), two clusters were found in the contrast of Short＞Long, including caudate and MFG/IFG. Meanwhile, two clusters were detected in the long-duration DT compared to short-duration DT (Long＞Short) as well, which included CUN/LG and SFG/MedFG. Finally, the conjunction analysis (see figure 2-2) revealed that the IPL/PoCG was commonly found in the short-duration and long-duration DT.
·Figure 2
Conclusions:
This study revealed that short-duration and long-duration divergent thinking (DT) engaged distinct and shared neural mechanisms. Short-duration DT specifically depended on the caudate and the MFG/IFG. Long-duration DT was primarily supported by the CUN/LG and SFG/MedFG. Additionally, both types of DT processes also relied on the IPL/PoCG. We believe that these findings provided better insights into the neural mechanisms underlying divergent thinking.
Higher Cognitive Functions:
Reasoning and Problem Solving 1
Modeling and Analysis Methods:
Activation (eg. BOLD task-fMRI) 2
Keywords:
Cognition
Meta- Analysis
Other - creativity, duration time
1|2Indicates the priority used for review
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Provide references using APA citation style.
Jia, W., & Zeng, Y. (2021). EEG signals respond differently to idea generation, idea evolution and evaluation in a loosely controlled creativity experiment. Scientific Reports, 11, 2119.
Kuang, C., Chen, J., Chen, J., Shi, Y., Huang, H., Jiao, B., Lin, Q., Rao, Y., Liu, W., Zhu, Y., Mo, L., Ma, L., & Lin, J. (2022). Uncovering neural distinctions and commodities between two creativity subsets: a meta‐analysis of fMRI studies in divergent thinking and insight using activation likelihood estimation. Human Brain Mapping, 43.
Maillet, D., Beaty, R., Kucyi, A., & Schacter, D. (2019). Large-scale network interactions involved in dividing attention between the external environment and internal thoughts to pursue two distinct goals. NeuroImage, 197.
Müller, V., Cieslik, E., Laird, A., Fox, P., Radua, J., Mataix-Cols, D., Tench, C., Yarkoni, T., Nichols, T., Turkeltaub, P., Wager, T., & Eickhoff, S. (2017). Ten simple rules for neuroimaging meta-analysis. Neuroscience & Biobehavioral Reviews, 84.
Oh-Descher, H., Beck, J., Ferrari, S., Sommer, M., & Egner, T. (2017). Probabilistic inference under time pressure leads to a cortical-to-subcortical shift in decision evidence integration. NeuroImage, 162.
Paek, S. H., Abdulla Alabbasi, A., Acar, S., & Runco, M. (2021). Is more time better for divergent thinking? A meta-analysis of the time-on-task effect on divergent thinking. Thinking Skills and Creativity, 41, 1-15.
Page, M., McKenzie, J., Bossuyt, P., Boutron, I., Hoffmann, T., mulrow, c., Shamseer, L., Tetzlaff, J., Akl, E., Brennan, S., Chou, R., Glanville, J., Grimshaw, J., Hróbjartsson, A., Lalu, M., Li, T., Loder, E., Mayo-Wilson, E., McDonald, S., & Moher, D. (2020). The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ (Clinical research ed.), 372, n71.
Rominger, C., Fink, A., Benedek, M., Weber, B., Perchtold-Stefan, C., & Schwerdtfeger, A. (2022). The ambulatory battery of creativity: additional evidence for reliability and validity. Frontiers in Psychology, 13, 964206.
Yuan, H., Lu, K., Yang, C., & Hao, N. (2021). Examples facilitate divergent thinking: the effects of timing and quality. Consciousness and Cognition, 93, 103169.