Multilayer Network Analysis across Cortical Depths in Resting-State 7T fMRI

Abstract

In graph theory, “multilayer networks” represent systems involving several interconnected topological levels. A neuroscience example is the hierarchy of connections between different cortical depths or “lamina”. This hierarchy is becoming non-invasively accessible in humans using ultra-high-resolution functional MRI (fMRI). Here, we applied multilayer graph theory to examine functional connectivity across different cortical depths in humans, using 7T fMRI (1-mm3voxels; 30 participants). Blood oxygenation level dependent (BOLD) signals were derived from five depths between the white matter and pial surface. We then compared networks where the inter-regional connections were limited to a single cortical depth only (“layer-by-layer matrices”) to those considering all possible connections between regions and cortical depths (“multilayer matrix”). We utilized global and local graph theory features that quantitatively characterize network attributes such as network composition, nodal centrality, path-based measures, and hub segregation. Detecting functional differences between cortical depths was improved using multilayer connectomics compared to the layer-by-layer versions. Superficial aspects of the cortex dominated information transfer and deeper aspects clustering. These differences were largest in frontotemporal and limbic brain regions. fMRI functional connectivity across different cortical depths may contain neurophysiologically relevant information. Multilayer connectomics could provide a methodological framework for studies on how information flows across this hierarchy.

On the influence of the vascular architecture on Gradient Echo and Spin Echo BOLD fMRI signals across cortical depth: a simulation approach based on realistic 3D vascular networks

“…The BOLD fMRI signal is a mixture of effects related to hemodynamic changes induced by neurovascular coupling, the vascular architecture within the sampled volume, and the biophysical interaction of oxygenated blood and tissue. Because BOLD fMRI measures neuronal activity through hemodynamics, its ultimate resolution relies on the spatial extent of neuronal-evoked hemodynamic changes, along with how these changes evolve over time [19][20][21] .…”