Generative models of the human connectome

Richard F Betzel,Andrea Avena-Koenigsberger,Joaquín Goñi,Ye He,Marcel A De Reus,Alessandra Griffa,Petra E Vértes,Bratislav Mišic,Jean-Philippe Thiran,Patric Hagmann,Martijn Van Den Heuvel,Xi-Nian Zuo,Edward T Bullmore,Olaf Sporns

doi:10.1016/j.neuroimage.2015.09.041

Abstract

The human connectome represents a network map of the brain's wiring diagram and the pattern into which its connections are organized is thought to play an important role in cognitive function. The generative rules that shape the topology of the human connectome remain incompletely understood. Earlier work in model organisms has suggested that wiring rules based on geometric relationships (distance) can account for many but likely not all topological features. Here we systematically explore a family of generative models of the human connectome that yield synthetic networks designed according to different wiring rules combining geometric and a broad range of topological factors. We find that a combination of geometric constraints with a homophilic attachment mechanism can create synthetic networks that closely match many topological characteristics of individual human connectomes, including features that were not included in the optimization of the generative model itself. We use these models to investigate a lifespan dataset and show that, with age, the model parameters undergo progressive changes, suggesting a rebalancing of the generative factors underlying the connectome across the lifespan.

Highlights

The human connectome represents a network map of the brain in which regions and inter-regional connections are rendered into the nodes and edges of a graph
We first sought to test the extent to which cost conservation shapes the topology of the human connectome by implementing a pure geometric model (i.e. K(u, v) = 1)
We found that E, KSe, and KSc all increased with age (Fig. 5), indicating that the matching index (MI) model does an increasingly poor job capturing the organization of older connectomes compared to younger connectomes

Summary

Introduction

The human connectome represents a network map of the brain in which regions and inter-regional connections are rendered into the nodes and edges of a graph. In this format, the connectome can be analyzed using tools from network science and graph theory (Bullmore and Sporns, 2009; Sporns, 2014). Despite the importance of conserving connection cost, previous work in model organisms has shown that wiring minimization alone cannot account for all the connectome's topological features (Kaiser and Hilgetag, 2006; Costa et al, 2007a). Connectome networks strike a balance wherein the formation of costly features like hubs and rich clubs trades off with a drive to reduce the total cost of wiring

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Conclusion