Article

FMRI resting state networks define distinct modes of long-distance interactions in the human brain

Oxford Centre for Functional Magnetic Resonance Imaging of the Brain, UK.
NeuroImage (Impact Factor: 6.36). 03/2006; 29(4):1359-67. DOI: 10.1016/j.neuroimage.2005.08.035
Source: PubMed

ABSTRACT

Functional magnetic resonance imaging (fMRI) studies of the human brain have suggested that low-frequency fluctuations in resting fMRI data collected using blood oxygen level dependent (BOLD) contrast correspond to functionally relevant resting state networks (RSNs). Whether the fluctuations of resting fMRI signal in RSNs are a direct consequence of neocortical neuronal activity or are low-frequency artifacts due to other physiological processes (e.g., autonomically driven fluctuations in cerebral blood flow) is uncertain. In order to investigate further these fluctuations, we have characterized their spatial and temporal properties using probabilistic independent component analysis (PICA), a robust approach to RSN identification. Here, we provide evidence that: i. RSNs are not caused by signal artifacts due to low sampling rate (aliasing); ii. they are localized primarily to the cerebral cortex; iii. similar RSNs also can be identified in perfusion fMRI data; and iv. at least 5 distinct RSN patterns are reproducible across different subjects. The RSNs appear to reflect "default" interactions related to functional networks related to those recruited by specific types of cognitive processes. RSNs are a major source of non-modeled signal in BOLD fMRI data, so a full understanding of their dynamics will improve the interpretation of functional brain imaging studies more generally. Because RSNs reflect interactions in cognitively relevant functional networks, they offer a new approach to the characterization of state changes with pathology and the effects of drugs.

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Available from: Paul M Matthews, Jan 11, 2015
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    • "The functional images were band-pass filtered for low frequencies fluctuations (hz 0.01-0.08) to reduce the interference of physiological noise, such as respiratory and cardiac artifacts – occurring at higher frequencies (0.3-0.5 Hz) (Birn, Diamond et al. 2006, Van Dijk, Hedden et al. 2010). Lowfrequency fluctuations below 0.1 Hz have been demonstrated to predominate in the crosscorrelation coefficients for functionally related regions (Biswal, Yetkin et al. 1995, Cordes, Haughton et al. 2000, De Luca, Beckmann et al. 2006), with the most consistent correlations occurring within a range of 0.01-0.08 Hz (Van Dijk, Hedden et al. 2010, Cong, Puoliväli et al. 2014). "
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    • "The procedure identifies synchronized spontaneous lowfrequency (<0.1 Hz) fluctuation of blood oxygen leveldependent (BOLD) signals across the brain in the resting state (Biswal et al. 1995; Lowe et al. 1998; Cordes et al. 2000 ). Based on consistent patterns across healthy subjects (Beckmann and Smith 2005; Damoiseaux et al. 2006; De Luca et al. 2006; Fox and Raichle 2007), resting-state FC procedures have been applied widely in various functional brain network studies, ranging from psychiatric disorders to neurological conditions (Fox and Greicius 2010), as well as in exploration of human brain functions (Smith et al. 2009; Laird et al. 2013; Sadaghiani and Kleinschmidt 2013). The procedures may be useful in assessing functional brain networks in OSA subjects, since the condition is accompanied by severe behavioral and physiological sequelae. "
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