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Default mode network dissociation in depressive and anxiety states

Default mode network dissociation in depressive and anxiety states

Coutinho, Joana Fernandes Pereira;

Fernandes, Sara Catarina da Veiga

;

Soares, José Miguel Montenegro

;

Maia, Liliana Filipa Costa

;

Gonçalves, Óscar F.

; Sampaio, Adriana
| Springer Science+Business Media | 2016 | DOI

Artigo de Jornal

The resting state brain networks, particularly the Default Mode Network (DMN), have been found to be altered in several psychopathological conditions such as depression and anxiety. In this study we hypothesized that cortical areas of the DMN, particularly the anterior regions - medial prefrontal cortex and anterior cingulate cortex - would show an increased functional connectivity associated with both anxiety and depression. Twenty-four healthy participants were assessed using Hamilton Depression and Anxiety Rating Scales and completed a resting-state functional magnetic resonance imaging scan. Multiple regression was performed in order to identify which areas of the DMN were associated with anxiety and depression scores. We found that the functional connectivity of the anterior portions of DMN, involved in self-referential and emotional processes, was positively correlated with anxiety and depression scores, whereas posterior areas of the DMN, involved in episodic memory and perceptual processing were negatively correlated with anxiety and depression scores. The dissociation between anterior and posterior cortical midline regions, raises the possibility of a functional specialization within the DMN in terms of self-referential tasks and contributes to the understanding of the cognitive and affective alterations in depressive and anxiety states.
This research was funded by the Portuguese Foundation for Science and Technology (FCT): PIC/IC/83290/2007, which is supported by FEDER (POFC - COMPETE). Joana Coutinho was funded by a FCT postdoctoral grant (number: SFRH/BPD/75014/2010)- POPH program and Bial Foundation (grant number 87/12)Liliana Maia is supported by the Competitive Factors Operational Programme-COMPETE-, by national funds from the Portuguese Foundation for Science and Technology (grant PTDC/PSI-PCL/115316/2009).
info:eu-repo/semantics/publishedVersion

Publicação

Ano de Publicação: 2016

Editora: Springer Science+Business Media

Identificadores

ISSN: 1931-7557