The preservation of topography across task conditions is consistent with the resilience and independence of fMRI-RSN across levels of consciousness (Greicius et al., 2008, Larson-Prior et al., 2009 and Vincent et al.,

2007) and behavioral states (Arfanakis et al., 2000, Biswal et al., 1995, Fransson, 2006, Greicius and Menon, 2004, Greicius et al., 2009, Morgan and Price, 2004 and Smith et al., 2009). The increased similarity between fMRI and MEG connectivity during the movie is likely due to increased cortical synchronization across subjects induced by sensory stimulation (Hasson et al., 2004 and Mantini et al., 2012). Interestingly, increased cortical synchronization across subjects is present not just in humans, but also in

nonhuman primates, and this signal has been used to map evolutionarily preserved or modified cortical see more networks across species (Mantini et al., 2013 and Mantini et al., 2012). However, natural vision click here induced a strong reduction of within- and between-network BLP correlation in the α and β bands, especially in the low frequency range (<0.3 Hz). This was shown with an analysis of interdependence (Figures 2, S2, and S3), with a voxel-wise seed based analysis (Figures 3, 4, and S4), and with pairwise regional analysis (Figures 5 and 6). The networks predominantly involved included the visual, auditory, dorsal attention, and the default-mode network. What is the significance of preserved fMRI/MEG topography in lieu of robust frequency specific modulations of BLP connectivity? This important point requires first a brief detour to the neurophysiological basis of the BOLD signal. It is now well established that BOLD signal changes produced by stimuli or tasks best correlate with local changes in

the local field potential (LFP), a signal dominated by the electrical current flowing from all nearby dendritic synaptic activity within a volume of tissue. While stimulus- or task-evoked BOLD signal changes are strongly correlated with LFP changes across all bands, but especially in the γ band (Goense and Logothetis, 2008), spontaneous fluctuations of the signal in the resting state correlate with fluctuations of the slow cortical potentials (SCP) (<4 Hz) and BLP fluctuations of signals at higher frequencies (α, β, and γ bands) (He et al., 2008, Nir et al., 2008 and Schölvinck et al., 2010). The link between not low and high frequency activity, however, is not obligatory, but it can be dissociated with respect to RSN topography between behavioral states. For example, while SCP and fMRI RSN topography remain similar during wakefulness and sleep, γ BLP correlates with fMRI RSN topography only during wakefulness (Breshears et al., 2010 and He et al., 2008). Finally, the phase of SCP may be nested with the power and phase of activity at higher frequencies (so called cross-frequency coupling or phase-power coupling) (Buzsáki and Draguhn, 2004, He et al., 2008, Monto et al., 2008 and Schroeder and Lakatos, 2009).