Analytical Operations Relate Structural and Functional Connectivity in the Brain

Abstract

Resting-state large-scale brain models vary in the amount of biological elements they incorporate and in the way they are being tested. One might expect that the more realistic the model is, the closer it should reproduce real functional data. It has been shown, instead, that when linear correlation across long BOLD fMRI time-series is used as a measure for functional connectivity (FC) to compare simulated and real data, a simple model performs just as well, or even better, than more sophisticated ones. The model in question is a simple linear model, which considers the physiological noise that is pervasively present in our brain while it diffuses across the white-matter connections, that is structural connectivity (SC). We deeply investigate this linear model, providing an analytical solution to straightforwardly compute FC from SC without the need of computationally costly simulations of time-series. We provide a few examples how this analytical solution could be used to perform a fast and detailed parameter exploration or to investigate resting-state non-stationarities. Most importantly, by inverting the analytical solution, we propose a method to retrieve information on the anatomical structure directly from functional data. This simple method can be used to complement or guide DTI/DSI and tractography results, especially for a better assessment of inter-hemispheric connections, or to provide an estimate of SC when only functional data are available.

Cognitive decline in metabolic syndrome is linked to microstructural white matter abnormalities

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Individual structural features constrain the mouse functional connectome

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Mapping complementary features of cross‐species structural connectivity to construct realistic “Virtual Brains”

“…In turn, spatially continuous neural field models require realistic spatial mapping of extended brain regions on top of the aforementioned neural mass model [Bojak et al, 2010]. These requirements arise from multiple sources of evidence confirming a direct yet implicit link between brain structure and function, originating from the early studies of Camillo Golgi, Santiago Ram on y Cajal, and Charles Scott Sherrington, and continuing to be supported by a number of modern neuroimaging studies [Berlucchi, 1999;Glasser et al, 2016;Hagmann et al, 2010;Margulies et al, 2016;Reid et al, 2016;Saggio et al, 2016;Shen et al, 2012;Zimmermann et al, 2016].…”