Common micro- and macroscale principles of connectivity in the human brain

Abstract

The brain requires efficient information transfer between neurons and between large-scale brain regions. Brain connectivity follows predictable organizational principles: at the cellular level, larger supragranular pyramidal neurons have larger dendritic trees, more synapses, more complex branching and perform more complex neuronal computations; at the macro-scale, region-to-region connections are suggested to display a diverse architecture with highly connected hub-areas facilitating complex information integration and computation. Here, we explore the hypothesis that the branching structure of large-scale region-to-region connectivity follows similar organizational principles as known for the neuronal scale. We examine microscale connectivity of basal dendritic trees of supragranular pyramidal neurons (300+) across ten cortical areas in five human donor brains (1M/4F). Dendritic complexity was quantified as the number of branch points, tree length, spine count, spine density and overall branching complexity. High-resolution diffusion-weighted MRI was used to construct white matter trees of cortico-cortical wiring. Examining the complexity of the resulting white matter trees using the same measures as for dendritic trees shows multimodal association areas to have larger, more complexly branched white matter trees than primary areas (all p<0.0001) and regional macroscale complexity to run in parallel with microscale measures, in terms of number of inputs (r=0.677, p=0.032), branch points (r=0.790, p=0.006), total tree length (r=0.664, p=0.036) and branching complexity (r=0.724, p=0.018). Our findings support the integrative theory that brain connectivity is structured following similar principles of connectivity at the neuronal and macroscale level, and provide a framework to study connectivity changes in brain conditions at multiple levels of brain organization.