Literature DB >> 24881884

Functional network organizations of two contrasting temperament groups in dimensions of novelty seeking and harm avoidance.

Sunghyon Kyeong1, Eunjoo Kim2, Hae-Jeong Park3, Dong-Uk Hwang4.   

Abstract

Novelty seeking (NS) and harm avoidance (HA) are two major dimensions of temperament in Cloninger׳s neurobiological model of personality. Previous neurofunctional and biological studies on temperament dimensions of HA and NS suggested that the temperamental traits have significant correlations with cortical and subcortical brain regions. However, no study to date has investigated the functional network modular organization as a function of the temperament dimension. The temperament dimensions were originally proposed to be independent of one another. However, a meta-analysis based on 16 published articles found a significant negative correlation between HA and NS (Miettunen et al., 2008). Based on this negative correlation, the current study revealed the whole-brain connectivity modular architecture for two contrasting temperament groups. The k-means clustering algorithm, with the temperamental traits of HA and NS as an input, was applied to divide the 40 subjects into two temperament groups: 'high HA and low NS' versus 'low HA and high NS'. Using the graph theoretical framework, we found a functional segregation of whole brain network architectures derived from resting-state functional MRI. In the 'high HA and low NS' group, the regulatory brain regions, such as the prefrontal cortex (PFC), are clustered together with the limbic system. In the 'low HA and high NS' group, however, brain regions lying on the dopaminergic pathways, such as the PFC and basal ganglia, are partitioned together. These findings suggest that the neural basis of inhibited, passive, and inactive behaviors in the 'high HA and low NS' group was derived from the increased network associations between the PFC and limbic clusters. In addition, supporting evidence of topological differences between the two temperament groups was found by analyzing the functional connectivity density and gray matter volume, and by computing the relationships between the morphometry and function of the brain.
Copyright © 2014 Elsevier B.V. All rights reserved.

Keywords:  Functional modular organization; Gray matter volume; Harm avoidance; Novelty seeking; Temperament

Mesh:

Year:  2014        PMID: 24881884     DOI: 10.1016/j.brainres.2014.05.037

Source DB:  PubMed          Journal:  Brain Res        ISSN: 0006-8993            Impact factor:   3.252


  7 in total

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2.  Individuality manifests in the dynamic reconfiguration of large-scale brain networks during movie viewing.

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Review 5.  Network Neuroscience and Personality.

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6.  Bayesian estimation of maximum entropy model for individualized energy landscape analysis of brain state dynamics.

Authors:  Jiyoung Kang; Seok-Oh Jeong; Chongwon Pae; Hae-Jeong Park
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7.  Gait pattern analysis and clinical subgroup identification: a retrospective observational study.

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  7 in total

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