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Dynamic network participation of functional connectivity hubs assessed by resting-state fMRI

MPS-Authors
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Schäfer,  Alexander
Department Neurology, MPI for Human Cognitive and Brain Sciences, Max Planck Society;

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Margulies,  Daniel S.
Max Planck Research Group Neuroanatomy and Connectivity, MPI for Human Cognitive and Brain Sciences, Max Planck Society;

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Gorgolewski,  Krzysztof J.
Max Planck Research Group Neuroanatomy and Connectivity, MPI for Human Cognitive and Brain Sciences, Max Planck Society;

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Kiebel,  Stefan J.
Department Neurology, MPI for Human Cognitive and Brain Sciences, Max Planck Society;
Department of Neurology, Biomagnetic Center, Jena University Hospital, Germany;

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Villringer,  Arno
Department Neurology, MPI for Human Cognitive and Brain Sciences, Max Planck Society;
Berlin School of Mind and Brain, Humboldt University Berlin, Germany;
Clinic for Cognitive Neurology, University of Leipzig, Germany;
Center for Stroke Research, Charité University Medicine Berlin, Germany;

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Schaefer_DynamicNetwork.pdf
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Citation

Schäfer, A., Margulies, D. S., Lohmann, G., Gorgolewski, K. J., Smallwood, J., Kiebel, S. J., et al. (2014). Dynamic network participation of functional connectivity hubs assessed by resting-state fMRI. Frontiers in Human Neuroscience, 8: 195. doi:10.3389/fnhum.2014.00195.


Cite as: http://hdl.handle.net/11858/00-001M-0000-0019-B564-A
Abstract
Network studies of large-scale brain connectivity have demonstrated that highly connected areas, or “hubs,” are a key feature of human functional and structural brain organization. We use resting-state functional MRI data and connectivity clustering to identify multi-network hubs and show that while hubs can belong to multiple networks their degree of integration into these different networks varies dynamically over time. The extent of the network variation was related to the connectedness of the hub. In addition, we found that these network dynamics were inversely related to positive self-generated thoughts reported by individuals and were further decreased with older age. Moreover, the left caudate varied its degree of participation between a default mode subnetwork and a limbic network. This variation was predictive of individual differences in the reports of past-related thoughts. These results support an association between ongoing thought processes and network dynamics and offer a new approach to investigate the brain dynamics underlying mental experience.