Abstract
Resting-state networks (RSNs) in fMRI are ‘activation-like’, spatially structured maps of grey matter brain areas exhibiting temporally correlated signal changes, which are believed to reflect neuronal activities of the ‘resting’ brain and which robustly and consistently appear in both resting and task data. They are purported to reflect the intrinsic energy demands of neuron populations that fire together with a common functional purpose. This chapter introduces the concept of RSNs and why they are of interest to neuroscience, describes their characteristics, reviews the methods used for their analysis, and discusses a few areas of application.
The most merciful thing in the world, I think, is the inability of the human mind to correlate all its contents. (H.P. Lovecraft, 1890–1937)
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Notes
- 1.
See Cole et al. (2010b) for further details.
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Niazy, R., Cole, D., Beckmann, C., Smith, S. (2015). Resting-State Networks. In: Uludag, K., Ugurbil, K., Berliner, L. (eds) fMRI: From Nuclear Spins to Brain Functions. Biological Magnetic Resonance, vol 30. Springer, Boston, MA. https://doi.org/10.1007/978-1-4899-7591-1_14
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