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Extraversion and Neuroticism relate to topological properties of resting-state brain networks
- Source :
- Frontiers in Human Neuroscience, Vol 7 (2013)
- Publication Year :
- 2013
- Publisher :
- Frontiers Media S.A., 2013.
-
Abstract
- With the advent and development of modern neuroimaging techniques, there is an increasing interest in linking extraversion and neuroticism to anatomical and functional brain markers. Here we aimed to test the theoretically derived biological personality model as proposed by Eysenck using graph theoretical analyses. Specifically, the association between the topological organization of whole-brain functional networks and extraversion/neuroticism was explored. To construct functional brain networks, functional connectivity among 90 brain regions was measured by temporal correlation using resting-state functional magnetic resonance imaging (fMRI) data of 71 healthy subjects. Graph theoretical analysis revealed a positive association of extraversion scores and normalized clustering coefficient values. These results suggested a more clustered configuration in brain networks of individuals high in extraversion, which could imply a higher arousal threshold and higher levels of arousal tolerance in the cortex of extraverts. On a local network level, we observed that a specific nodal measure, i.e. betweenness centrality (BC), was positively associated with neuroticism scores in the right precentral gyrus, right caudate nucleus, right olfactory cortex and bilateral amygdala. For individuals high in neuroticism, these results suggested a more frequent participation of these specific regions in information transition within the brain network and, in turn, may partly explain greater regional activation levels and lower arousal thresholds in these regions. In contrast, extraversion scores were positively correlated with BC in the right insula, while negatively correlated with BC in the bilateral middle temporal gyrus, indicating that the relationship between extraversion and regional arousal is not as simple as proposed by Eysenck.
Details
- Language :
- English
- ISSN :
- 16625161
- Volume :
- 7
- Database :
- Directory of Open Access Journals
- Journal :
- Frontiers in Human Neuroscience
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.10981a88cb854a99a5a100bcaf542c50
- Document Type :
- article
- Full Text :
- https://doi.org/10.3389/fnhum.2013.00257