Brain Structural Signatures and Functional Connectivity in Creative Thinking: A Meta-Analysis Study
Poster No:
788
Submission Type:
Abstract Submission
Authors:
qiutong Long1, JiaBao Lin1
Institutions:
1School of Public Health and Management, Guangzhou University of Chinese Medicine, Guangzhou, Guangdong Province
First Author:
qiutong Long
School of Public Health and Management, Guangzhou University of Chinese Medicine
Guangzhou, Guangdong Province
School of Public Health and Management, Guangzhou University of Chinese Medicine
Guangzhou, Guangdong Province
Co-Author:
JiaBao Lin
School of Public Health and Management, Guangzhou University of Chinese Medicine
Guangzhou, Guangdong Province
School of Public Health and Management, Guangzhou University of Chinese Medicine
Guangzhou, Guangdong Province
Introduction:
With the development of cognitive neuroscience, researchers have done many fMRI studies on the neural mechanisms of creative activities (Fink et al., 2009). For example, Benedek et al. (2012) found the inferior frontal gyrus was significantly activated during creative thinking. Shah et al. (2013) showed the dorsolateral prefrontal cortex play a crucial role in generating novel stories. It's evident that the frontal lobe is a brain area with relatively consistent activation in relevant fMRI studies. The brain structure, serving as the bedrock of brain function, can offer insights into creative activities by delving deeply into the characteristics of brain structures related to creative thinking. In recent years, some studies have explored brain structural mechanisms underlying creative thinking. Jung et al. (2010) found the thickness of the right posterior cingulate cortex was positively correlated with divergent thinking scores. However, Gansler et al. (2011) indicated the gray matter volume of the right superior parietal lobe was positively correlated with creativity. However, findings on the brain structures of creativity aren't quite consistent. Thus, the present study plans to perform a meta-analysis with the method of Seed-based d Mapping via permutation of subject images (SDM-PSI) to explore the brain structure related to creative activities.
Methods:
Guided by the PRISMA flow diagram, we carried out the identification and review of the literature (Page et al., 2014). The search was conducted using databases such as Web of Science, PubMed, Elsevier, PLOS, APA, and SAGE, spanning from 2003 to 2023. The retrieval keywords fall into three categories: creative, structural magnetic resonance imaging, and brain structure. The inclusion criteria were as follows: (1) the participants were healthy individuals, (2) the research theme focused on creativity, (3) the article uses structural MRI and includes whole-brain voxel-based analysis data, (4) the activation coordinates in the report should comply with the standardization of either Montreal Neurological Institute or Talairach space, and (5) the morphological data of brain structure should be gray matter volume or gray matter density. After the preliminary retrieval, a total of 1,462 articles were obtained. Then, strict screening was carried out according to the inclusion and exclusion criteria, and finally 23 studies were included. (Fig. 1). A Meta analysis was performed via SDM-PSI version 6.21, with a significance level of Ρ<.05 (Zhang et al., 2014). Based on the results of the meta-analysis, we carried out meta-analytic connectivity modeling (MACM) analyses and resting-state functional connectivity (RSFC) analyses to identify co-activation patterns (Li et al., 2014). Eventually, we used the online Neurosynth image decoder (Rubin et al., 2017) for a meta-analytic decoding analysis to identify the cognitive themes linked to the meta-analysis results.
Results:
The SDM meta-analysis showed that increased gray matter in right anterior thalamus, right rolandic operculum and the right middle cingulate are related to creative activities (Fig. 2, Table 1). The MACN analysis showed that the right anterior thalamus produced functional connectivity patterns with precentral gyrus (PG), middle frontal gyrus (MFG), superior frontal gyrus and so on (Fig. 3, Table 2). For the right rolandic operculum, it was found that it had connectivity patterns with medial frontal gyrus, inferior frontal gyrus, MFG and so on (Fig. 4, Table 3). The right middle cingulate was revealed to have functional connectivity with lingual gyrus, MFG, PG and so on (Fig. 5, Table 4). Results from RSFC analyses and their conjunctions for each ROI are displayed in Fig. 6 and Table 5.
Conclusions:
The present meta-analysis suggested that , increased gray matter in the thalamus, cingulate and rolandic operculum were associated with creative processing . Furthermore, the functional connectivity analysis outcomes mainly overlapped with the default network.
Higher Cognitive Functions:
Reasoning and Problem Solving 1
Modeling and Analysis Methods:
Connectivity (eg. functional, effective, structural) 2
Keywords:
Cognition
Meta- Analysis
STRUCTURAL MRI
1|2Indicates the priority used for review
Abstract Information
By submitting your proposal, you grant permission for the Organization for Human Brain Mapping (OHBM) to distribute your work in any format, including video, audio print and electronic text through OHBM OnDemand, social media channels, the OHBM website, or other electronic publications and media.
The Open Science Special Interest Group (OSSIG) is introducing a reproducibility challenge for OHBM 2025. This new initiative aims to enhance the reproducibility of scientific results and foster collaborations between labs. Teams will consist of a “source” party and a “reproducing” party, and will be evaluated on the success of their replication, the openness of the source work, and additional deliverables. Click here for more information. Propose your OHBM abstract(s) as source work for future OHBM meetings by selecting one of the following options:
Please indicate below if your study was a "resting state" or "task-activation” study.
Healthy subjects only or patients (note that patient studies may also involve healthy subjects):
Was this research conducted in the United States?
Were any human subjects research approved by the relevant Institutional Review Board or ethics panel? NOTE: Any human subjects studies without IRB approval will be automatically rejected.
Were any animal research approved by the relevant IACUC or other animal research panel? NOTE: Any animal studies without IACUC approval will be automatically rejected.
Please indicate which methods were used in your research:
For human MRI, what field strength scanner do you use?
Which processing packages did you use for your study?
Provide references using APA citation style.
2.Benedek, M., Franz, F., Heene, M., & Neubauer, A. C. (2012). Differential effects of cognitive inhibition and intelligence on creativity. Personality and individual differences, 53-334(4), 480–485. https://doi.org/10.1016/j.paid.2012.04.014
3.Shah, C., Erhard, K., Ortheil, H. J., Kaza, E., Kessler, C., & Lotze, M. (2013). Neural correlates of creative writing: an fMRI study. Human brain mapping, 34(5), 1088–1101. https://doi.org/10.1002/hbm.21493
4.Jung, R. E., Segall, J. M., Jeremy Bockholt, H., Flores, R. A., Smith, S. M., Chavez, R. S., & Haier, R. J. (2010). Neuroanatomy of creativity. Human brain mapping, 31(3), 398–409. https://doi.org/10.1002/hbm.20874
5.Gansler, D. A., Moore, D. W., Susmaras, T. M., Jerram, M. W., Sousa, J., & Heilman, K. M. (2011). Cortical morphology of visual creativity. Neuropsychologia, 49(9), 2527–2532. https://doi.org/10.1016/j.neuropsychologia.2011.05.001
6.Page,M.J.and J.E.McKenzie,et al.(2021). The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. PLoS medicine, 18(3), e1003583. https://doi.org/10.1371/journal.pmed.1003583
7.Zhang, J., Liu, Y., Lan, K., Huang, X., He, Y., Yang, F., Li, J., Hu, Q., Xu, J., & Yu, H. (2021). Gray Matter Atrophy in Amnestic Mild Cognitive Impairment: A Voxel-Based Meta-Analysis. Frontiers in aging neuroscience, 13, 627919. https://doi.org/10.3389/fnagi.2021.627919
8.Li, S., Krueger, F., Camilleri, J. A., Eickhoff, S. B., & Qu, C. (2021). The neural signatures of social hierarchy-related learning and interaction: A coordinate- and connectivity-based meta-analysis. NeuroImage, 245, 118731. https://doi.org/10.1016/j.neuroimage.2021.118731
9.Rubin, T. N., Koyejo, O., Gorgolewski, K. J., Jones, M. N., Poldrack, R. A., & Yarkoni, T. (2017). Decoding brain activity using a large-scale probabilistic functional-anatomical atlas of human cognition. PLoS computational biology, 13(10), e1005649. https://doi.org/10.1371/journal.pcbi.1005649