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Young-Ah Rho. 1 Physics Department, Center for Complex Systems & Brain Sciences, Florida Atlantic University, Boca Raton, Florida.
Randy Anthony McIntosh. 2 Department of Psychology, Rotman Research Institute of Baycrest Center, University of Toronto, Toronto, Ontario.
Viktor K. Jirsa. 1 Physics Department, Center for Complex Systems & Brain Sciences, Florida Atlantic University, Boca Raton, Florida. 3 Theoretical Neuroscience Group, UMR6233 Institut des Sciences du Mouvement CNRS, France.
Address correspondence to: Viktor K. Jirsa, Université de la Méditerranée, Institut des Sciences du Mouvement Etienne-Jules Marey UMR 6233, 163 av. de Luminy, CP910, F-13288 Marseille cedex 09, France, E-mail: [email protected]
Introduction
Functional neuroimaging studies have reported the dynamical characteristics of blood oxygen level dependent (BOLD) signals characterized by slow frequency (<0.1 Hz) fluctuations during rest, which are organized into specific cortical networks (Damoiseaux et al., 2006; Fox et al., 2005; Fransson et al., 2007; Greicius et al., 2003; Shulman et al., 1997). Several studies have reported a significant correlation between the power of fluctuations of neural activities in the gamma range and BOLD signal fluctuations during simultaneous local field potential (LFP)/functional magnetic resonance imaging (fMRI) measures in the monkey (Nir et al., 2008; Shmuel and Leopold, 2008). In humans, simultaneous electroencephalogram (EEG)/fMRI studies have shown that BOLD signal changes are related to spontaneous EEG power fluctuations in the alpha (de Munck et al., 2007; Goncalves et al., 2006; Laufs et al., 2003a) and the beta rhythm (Laufs et al., 2003b). Further, Mantini et al. (2007) have shown that BOLD signal fluctuations are correlated with EEG power variations of delta, theta, alpha, beta, and gamma rhythms, suggesting that the spontaneous ongoing oscillatory activity is related to the dynamic interplay between distinct functional networks characterized by a specific electrophysiological signature. However, the underlying mechanisms linking fast scale rhythms in neural activity and low frequency coherent fluctuations of the BOLD signal are not yet clear.
Computational studies (Chawla et al., 1999, 2000; Lumer et al., 1997) have established some of the biophysical mechanisms that link fast neuronal synchronization to slow variations in population firing rates reported by BOLD signals. In brief, there is a circular causality that requires fast discharge rates to suppress effective membrane time constants, which sensitize the neuron to synchronized presynaptic inputs. This is referred to...