Functional magnetic resonance imaging using blood oxygenation level dependent (BOLD) contrast is well established as one of the most powerful methods for mapping human brain function. Numerous studies have measured how low-frequency BOLD signal fluctuations from the brain are correlated between voxels in a resting state, and have exploited these signals to infer functional connectivity within specific neural circuits. However, to date there have been no previous substantiated reports of resting state correlations in the spinal cord. In a cohort of healthy volunteers, we observed robust functional connectivity between left and right ventral (motor) horns, and between left and right dorsal (sensory) horns. Our results demonstrate that low-frequency BOLD fluctuations are inherent in the spinal cord as well as the brain, and by analogy to cortical circuits, we hypothesize that these correlations may offer insight into the execution and maintenance of sensory and motor functions both locally and within the cerebrum.DOI: http://dx.doi.org/10.7554/eLife.02812.001

We recently reported our findings of resting state functional connectivity in the human spinal cord: in a cohort of healthy volunteers we observed robust functional connectivity between left and right ventral (motor) horns and between left and right dorsal (sensory) horns (Barry et al., 2014). Building upon these results, we now quantify the within-subject reproducibility of bilateral motor and sensory networks (intraclass correlation coefficient = 0.54–0.56) and explore the impact of including frequencies up to 0.13 Hz. Our results suggest that frequencies above 0.08 Hz may enhance the detectability of these resting state networks, which would be beneficial for practical studies of spinal cord functional connectivity.

Neurobiological theories of awareness propose divergent accounts of the spatial extent of brain changes that support conscious perception. Whereas focal theories posit mostly local regional changes, global theories propose that awareness emerges from the propagation of neural signals across a broad extent of sensory and association cortex. Here we tested the scalar extent of brain changes associated with awareness using graph theoretical analysis applied to functional connectivity data acquired at ultra-high field while subjects performed a simple masked target detection task. We found that awareness of a visual target is associated with a degradation of the modularity of the brain's functional networks brought about by an increase in intermodular functional connectivity. These results provide compelling evidence that awareness is associated with truly global changes in the brain's functional connectivity.awareness | graph theory | functional connectivity | consciousness T hree broad classes of models have been proposed to explain the neural basis of awareness, with these classes primarily differing on the predicted extent of neural information changes associated with conscious perception. According to focal theories, awareness results from local changes in neural activity in either the perceptual substrates (1-3) or in higher-level nodes of information processing pathways (4). By contrast, network-level theories posit that awareness is tightly associated with activation of parietofrontal attention networks of the brain (5-11). Finally, global models propose that awareness results from widespread changes in the activation state (12-15) and functional connectivity (16-19) of the brain. Though there is strong experimental support for network-level theories, there is scant experimental evidence in favor of truly sweeping, widespread changes in brain activity with conscious perception despite the fact that global scale models have recently come to prominence in the theoretical landscape of this field.Using a graph theoretical approach applied to ultra-high-field fMRI data, here we experimentally tested a key tenet of global theories: the widespread emergence of large-scale functional connectivity with awareness. Graph theory analyses are ideal tools to test global models of awareness because they can provide concise measures of the integration and segregation of interconnected nodes of a system (20). Applied to functional imaging data, we treat individual brain regions of interest (ROIs) as nodes, functional connectivity between ROIs as edges, and functional brain networks as interconnected modules of nodes. When examining a large set of ROIs that encompass the different networks of the human cerebral cortex (21, 22), we can apply graph theory analyses to estimate the extent to which key measures of global information processing are altered by the state of awareness. This approach has been previously applied to study differences in cognitive states (23)(24)(25)(26)(27)(28)(29)(30)(31). Although recent studies have t...