Analyses of FC at rest have supported the hypothesis that the brain is spatially organized into large-scale intrinsic networks –, e.g. These advances have enabled investigators to estimate interactions in the brain by measuring functional connectivity (FC) from resting-state functional MRI (rs-fMRI). The study of such patterns of synchronization has known important developments due to recent methodological advances in brain imaging data acquisition and analysis.
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Even at rest, in the absence of direct environmental stimulations, these interactions drive the synchronization of spontaneous activity across brain systems, shedding light on the large-scale anatomo-functional organization of the brain.
We also reveal the critical importance of specific anatomical connections in shaping the global anatomo-functional structure of this dynamical regime, notably connections between hemispheres.Ĭoherent behavior and cognition involve synergies between neuronal populations in interaction –. In this study, we demonstrate the existence (and quantify the contribution) of a dynamical regime in the brain, coined ‘stationary’, that appears to be largely induced and shaped by the underlying anatomy. Various hypotheses have been proposed and tested using modern neuroimaging techniques combined with mathematical models of brain activity. While anatomy and dynamics are organically intertwined (anatomy contributes to shape dynamics), the nature and strength of this relation remain largely mysterious. We also show that homotopic connections across cerebral hemispheres, which are typically improperly estimated, play a strong role in shaping all aspects of FC, notably indirect connections and the topographic organization of brain networks.īy analogy with the road network, the human brain is defined both by its anatomy (the ‘roads’), that is, the way neurons are shaped, clustered together and connected to each others and its dynamics (the ‘traffic’): electrical and chemical signals of various types, shapes and strength constantly propagate through the brain to support its sensorimotor and cognitive functions, its capacity to learn and adapt to disease, and to create consciousness. We showed that anatomical connectivity alone accounts for up to 15% of FC variance that there is a stationary regime accounting for up to an additional 20% of variance and that this regime can be associated to a stationary FC that a simple stationary model of FC better explains FC than more complex models and that there is a large remaining variance (around 65%), which must contain the non-stationarities of FC evidenced in the literature. We hypothesized that FC reflects the interplay of at least three types of components: (i) a backbone of anatomical connectivity, (ii) a stationary dynamical regime directly driven by the underlying anatomy, and (iii) other stationary and non-stationary dynamics not directly related to the anatomy.
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We addressed this issue by systematically comparing functional connectivity (FC) from resting-state functional magnetic resonance imaging data with simulations from increasingly complex computational models, and by manipulating anatomical connectivity obtained from fiber tractography based on diffusion-weighted imaging. In particular, the existence and relative contributions of anatomical constraints and dynamical physiological mechanisms of different types remain to be established. Yet, the mechanisms shaping this relationship largely remain to be elucidated and are highly debated. Investigating the relationship between brain structure and function is a central endeavor for neuroscience research.