Neuronal Networks Observed with Resting State Functional Magnetic Resonance Imaging in Clinical Populations

Abstract

Functional Magnetic resonance imaging (fMRI, (Ogawa et al., 1990)) in the absence of experimental tasks and behavioral responses, performed with the patient in a relaxed “resting” state (rs-fMRI), takes advantage of the neural origin of spontaneous blood-oxygenlevel-dependent (BOLD) signal fluctuations (Biswal et al., 1995) to represent the rate and timing of activity synchronization across the entire brain (Damoiseaux et al., 2006; Mantini et al., 2007; van de Ven et al., 2004). Independent component analysis (ICA) (Hyvarinen et al., 2001), when applied to wholebrain rs-fMRI, allows extracting from each individual patient data set a series of activation images describing the BOLD signal temporal correlations within and between functionally connected brain regions, forming highly reproducible neural networks called resting state networks (RSN) (Damoiseaux et al., 2006; Mantini et al., 2007). Particularly, ICA transforms individual patient rs-fMRI data sets into series of RSN maps, allowing for a voxel-based population analysis of whole-brain functional connectivity without the need to specify “a priori” the regions of interest constituting the layout of the neural network (McKeown et al., 1998; van de Ven et al., 2004). In normal volunteers there are at least six RSNs consistently found whose neurological significance has been established according to the functional specialization and anatomical connectivity of the constituent regions (Greicius et al., 2009; van den Heuvel et al., 2009) as well as to the possible association with neuro-electrical rhythms (Mantini et al., 2007). Altogether the functional connectivity of these RSNs represents a basic physiological condition of the human resting brain (Gusnard & Raichle, 2001). While the number, role, meaning and potential of RSNs in representing and interpreting the functional architecture of the human brain is still debated and sometimes controversial (Morcom & Fletcher, 2007), a number of voxel-based population rs-fMRI studies have uncovered significant differences between normal and clinical populations in various neurological disorders, and a particular attention has been given to cognitive decline as a