The salience network is responsible for switching between the default mode network and the central executive network: Replication from DCM

被引:512
|
作者
Goulden, Nia [1 ]
Khusnulina, Aygul [1 ]
Davis, Nicholas J. [2 ]
Bracewell, Robert M. [1 ]
Bokde, Arun L. [3 ]
McNulty, Jonathan P. [4 ]
Mullins, Paul G. [1 ]
机构
[1] Bangor Univ, Bangor, Gwynedd, Wales
[2] Swansea Univ, Swansea, W Glam, Wales
[3] Univ Dublin Trinity Coll, Dublin 2, Ireland
[4] Univ Coll Dublin, Dublin 2, Ireland
关键词
INDEPENDENT COMPONENT ANALYSIS; DYNAMIC CAUSAL-MODELS; VON ECONOMO NEURONS; OLD-WORLD MONKEY; BRAIN NETWORKS; CONNECTIVITY; FMRI; SELECTION; SYSTEMS; INSULA;
D O I
10.1016/j.neuroimage.2014.05.052
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
With the advent of new analysis methods in neuroimaging that involve independent component analysis (ICA) and dynamic causal modelling (DCM), investigations have focused on measuring both the activity and connectivity of specific brain networks. In this study we combined DCM with spatial ICA to investigate network switching in the brain. Using time courses determined by ICA in our dynamic causal models, we focused on the dynamics of switching between the default mode network (DMN), the network which is active when the brain is not engaging in a specific task, and the central executive network (CEN), which is active when the brain is engaging in a task requiring attention: Previous work using Granger causality methods has shown that regions of the brain which respond to the degree of subjective salience of a stimulus, the salience network, are responsible for switching between the DMN and the CEN (Sridharan et al., 2008). In this work we apply DCM to ICA time courses representing these networks in resting state data. In order to test the repeatability of our work we applied this to two independent datasets. This work confirms that the salience network drives the switching between default mode and central executive networks and that our novel technique is repeatable. Crown Copyright (C) 2014 Published by Elsevier Inc All rights reserved.
引用
收藏
页码:180 / 190
页数:11
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