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Brain activity and connectivity during poetry composition: Toward a multidimensional model of the creative process.

Liu S, Erkkinen MG, Healey ML, Xu Y, Swett KE, Chow HM, Braun AR - Hum Brain Mapp (2015)

Bottom Line: Distinct activation patterns were associated with generation and revision, two major phases of the creative process.Experts showed significantly stronger deactivation of DLPFC/IPS during generation, suggesting that they may more effectively suspend cognitive control.Quality of poetry, assessed by an independent panel, was associated with divergent connectivity patterns in experts and novices, centered upon MPFC (for technical facility) and DLPFC/IPS (for innovation), suggesting a mechanism by which experts produce higher quality poetry.

View Article: PubMed Central - PubMed

Affiliation: Language Section, National Institute on Deafness and Other Communication Disorders, National Institutes of Health, Bethesda, Maryland, 20892.

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Related in: MedlinePlus

Brain network connections associated with generation and revision phases.(A) In functional network connectivity (FNC) analyses, the group ICA decomposition was first used to divide the whole brain into 53 spatially independent components (ICs), each representing a self‐organized functional network with homogenous temporal dynamics. In this data‐driven way, we are able to examine the whole brain systematically while avoiding the random nature of seed selection. The hierarchical clustering of these ICs yielded the dendrogram displayed here. On the basis of statistical similarities in temporal dynamics, ICs were organized into the 5 clusters shown. Cluster 2 (red) and cluster 4 (purple) were respectively centered on the MPFC and the DLPFC/IPS. Clusters 1, 3, and 5 include ICs representing auditory‐somatosensory‐motor, visual and retrosplenial areas, respectively (all five clusters are depicted in Supporting Information Fig. 3). In this dendrogram, the x axis represents ICs and the y axis indicates distance between two linked objects, that is, either ICs or sub‐clusters (see Methods for detail). (B) Selected ICs from clusters 2 (red) and 4 (purple) are displayed. The MPFC was grouped together with an extensive set of regions including perisylvian cortices and the caudate nucleus. Only paramedian areas of the precuneus and posterior cingulate cortex (PCC) were grouped with the DLPFC/IPS. (C) Inter‐cluster correlation was calculated between the averaged time series of all ICs in cluster 2 and 4. Significant anticorrelation between cluster 2 and 4 during the generation phase was reversed in the revision phase (N = 27, mean ± standard error, ** indicates P < 0.01).
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hbm22849-fig-0003: Brain network connections associated with generation and revision phases.(A) In functional network connectivity (FNC) analyses, the group ICA decomposition was first used to divide the whole brain into 53 spatially independent components (ICs), each representing a self‐organized functional network with homogenous temporal dynamics. In this data‐driven way, we are able to examine the whole brain systematically while avoiding the random nature of seed selection. The hierarchical clustering of these ICs yielded the dendrogram displayed here. On the basis of statistical similarities in temporal dynamics, ICs were organized into the 5 clusters shown. Cluster 2 (red) and cluster 4 (purple) were respectively centered on the MPFC and the DLPFC/IPS. Clusters 1, 3, and 5 include ICs representing auditory‐somatosensory‐motor, visual and retrosplenial areas, respectively (all five clusters are depicted in Supporting Information Fig. 3). In this dendrogram, the x axis represents ICs and the y axis indicates distance between two linked objects, that is, either ICs or sub‐clusters (see Methods for detail). (B) Selected ICs from clusters 2 (red) and 4 (purple) are displayed. The MPFC was grouped together with an extensive set of regions including perisylvian cortices and the caudate nucleus. Only paramedian areas of the precuneus and posterior cingulate cortex (PCC) were grouped with the DLPFC/IPS. (C) Inter‐cluster correlation was calculated between the averaged time series of all ICs in cluster 2 and 4. Significant anticorrelation between cluster 2 and 4 during the generation phase was reversed in the revision phase (N = 27, mean ± standard error, ** indicates P < 0.01).

Mentions: To explore the interactions between brain regions, we applied group ICA‐based functional network connectivity (FNC) analyses to the generation and revision phases together. In doing so, we were able to quantitatively compare the connectivity patterns of these two phases in a data‐driven way. The FNC method permits an unbiased examination of functional connections throughout the whole brain (the advantages of this approach are explained in the Methods section and the legend to Fig. 3A). In the dendrogram summarizing these results (Fig. 3A), the brain regions with high temporal correlations are grouped into one cluster. Interestingly, the MPFC and DLPFC/IPS, highlighted in the GLM analysis, naturally fell into two separate clusters, consistent with the central roles played by these two components in both generation and revision phases, as outlined above. Moreover, the MPFC was tightly coupled to many language related areas and the caudate nucleus (Cluster 2 in Fig. 3B), while the DLPFC/IPS operated in a more isolated mode (Cluster 4 in Fig. 3B).


Brain activity and connectivity during poetry composition: Toward a multidimensional model of the creative process.

Liu S, Erkkinen MG, Healey ML, Xu Y, Swett KE, Chow HM, Braun AR - Hum Brain Mapp (2015)

Brain network connections associated with generation and revision phases.(A) In functional network connectivity (FNC) analyses, the group ICA decomposition was first used to divide the whole brain into 53 spatially independent components (ICs), each representing a self‐organized functional network with homogenous temporal dynamics. In this data‐driven way, we are able to examine the whole brain systematically while avoiding the random nature of seed selection. The hierarchical clustering of these ICs yielded the dendrogram displayed here. On the basis of statistical similarities in temporal dynamics, ICs were organized into the 5 clusters shown. Cluster 2 (red) and cluster 4 (purple) were respectively centered on the MPFC and the DLPFC/IPS. Clusters 1, 3, and 5 include ICs representing auditory‐somatosensory‐motor, visual and retrosplenial areas, respectively (all five clusters are depicted in Supporting Information Fig. 3). In this dendrogram, the x axis represents ICs and the y axis indicates distance between two linked objects, that is, either ICs or sub‐clusters (see Methods for detail). (B) Selected ICs from clusters 2 (red) and 4 (purple) are displayed. The MPFC was grouped together with an extensive set of regions including perisylvian cortices and the caudate nucleus. Only paramedian areas of the precuneus and posterior cingulate cortex (PCC) were grouped with the DLPFC/IPS. (C) Inter‐cluster correlation was calculated between the averaged time series of all ICs in cluster 2 and 4. Significant anticorrelation between cluster 2 and 4 during the generation phase was reversed in the revision phase (N = 27, mean ± standard error, ** indicates P < 0.01).
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hbm22849-fig-0003: Brain network connections associated with generation and revision phases.(A) In functional network connectivity (FNC) analyses, the group ICA decomposition was first used to divide the whole brain into 53 spatially independent components (ICs), each representing a self‐organized functional network with homogenous temporal dynamics. In this data‐driven way, we are able to examine the whole brain systematically while avoiding the random nature of seed selection. The hierarchical clustering of these ICs yielded the dendrogram displayed here. On the basis of statistical similarities in temporal dynamics, ICs were organized into the 5 clusters shown. Cluster 2 (red) and cluster 4 (purple) were respectively centered on the MPFC and the DLPFC/IPS. Clusters 1, 3, and 5 include ICs representing auditory‐somatosensory‐motor, visual and retrosplenial areas, respectively (all five clusters are depicted in Supporting Information Fig. 3). In this dendrogram, the x axis represents ICs and the y axis indicates distance between two linked objects, that is, either ICs or sub‐clusters (see Methods for detail). (B) Selected ICs from clusters 2 (red) and 4 (purple) are displayed. The MPFC was grouped together with an extensive set of regions including perisylvian cortices and the caudate nucleus. Only paramedian areas of the precuneus and posterior cingulate cortex (PCC) were grouped with the DLPFC/IPS. (C) Inter‐cluster correlation was calculated between the averaged time series of all ICs in cluster 2 and 4. Significant anticorrelation between cluster 2 and 4 during the generation phase was reversed in the revision phase (N = 27, mean ± standard error, ** indicates P < 0.01).
Mentions: To explore the interactions between brain regions, we applied group ICA‐based functional network connectivity (FNC) analyses to the generation and revision phases together. In doing so, we were able to quantitatively compare the connectivity patterns of these two phases in a data‐driven way. The FNC method permits an unbiased examination of functional connections throughout the whole brain (the advantages of this approach are explained in the Methods section and the legend to Fig. 3A). In the dendrogram summarizing these results (Fig. 3A), the brain regions with high temporal correlations are grouped into one cluster. Interestingly, the MPFC and DLPFC/IPS, highlighted in the GLM analysis, naturally fell into two separate clusters, consistent with the central roles played by these two components in both generation and revision phases, as outlined above. Moreover, the MPFC was tightly coupled to many language related areas and the caudate nucleus (Cluster 2 in Fig. 3B), while the DLPFC/IPS operated in a more isolated mode (Cluster 4 in Fig. 3B).

Bottom Line: Distinct activation patterns were associated with generation and revision, two major phases of the creative process.Experts showed significantly stronger deactivation of DLPFC/IPS during generation, suggesting that they may more effectively suspend cognitive control.Quality of poetry, assessed by an independent panel, was associated with divergent connectivity patterns in experts and novices, centered upon MPFC (for technical facility) and DLPFC/IPS (for innovation), suggesting a mechanism by which experts produce higher quality poetry.

View Article: PubMed Central - PubMed

Affiliation: Language Section, National Institute on Deafness and Other Communication Disorders, National Institutes of Health, Bethesda, Maryland, 20892.

Show MeSH
Related in: MedlinePlus