Robustness of connectome harmonics to local gray matter and long-range white matter connectivity changes

Sébastien Naze,Timothée Proix,Selen Atasoy,James R Kozloski

doi:10.1016/j.neuroimage.2020.117364

Abstract

Recently, it has been proposed that the harmonic patterns emerging from the brain's structural connectivity underlie the resting state networks of the human brain. These harmonic patterns, termed connectome harmonics, are estimated as the Laplace eigenfunctions of the combined gray and white matters connectivity matrices and yield a connectome-specific extension of the well-known Fourier basis. However, it remains unclear how topological properties of the combined connectomes constrain the precise shape of the connectome harmonics and their relationships to the resting state networks. Here, we systematically study how alterations of the local and long-range connectivity matrices affect the spatial patterns of connectome harmonics. Specifically, the proportion of local gray matter homogeneous connectivity versus long-range white-matter heterogeneous connectivity is varied by means of weight-based matrix thresholding, distance-based matrix trimming, and several types of matrix randomizations. We demonstrate that the proportion of local gray matter connections plays a crucial role for the emergence of wide-spread, functionally meaningful, and originally published connectome harmonic patterns. This finding is robust for several different cortical surface templates, mesh resolutions, or widths of the local diffusion kernel. Finally, using the connectome harmonic framework, we also provide a proof-of-concept for how targeted structural changes such as the atrophy of inter-hemispheric callosal fibers and gray matter alterations may predict functional deficits associated with neurodegenerative conditions.

Highlights

Understanding the structure-function relationships in large-scale brain networks is an active research topic in neuroscience (Sporns et al, 2004; Honey et al, 2010; Mii et al, 2016)
Our results reveal that both local gray matter connectivity and long-distance white matter fiber tracts determine the exact shape of the connectome harmonic patterns, yet the local gray matter connectivity plays a crucial role in the emergence of functionally meaningful spatial patterns on the cortical surface
Our work focuses on the Default Mode Network (DMN), but the Mutual Information (MI) measured between harmonics and other resting state networks (RSN) follows a similar pattern

Summary

Introduction

Understanding the structure-function relationships in large-scale brain networks is an active research topic in neuroscience (Sporns et al, 2004; Honey et al, 2010; Mii et al, 2016). Graph theoretical analysis of brain connectivity has led to new insights about cortical wiring patterns (Jirsa and McIntosh, 2007; Bullmore and Sporns, 2009) such as small-world topology, presence of hubs, hierarchical properties, and enabled the development of quantitative measures of network resilience (Rubinov and Sporns, 2010) These metrics are commonly used to understand the organization of brain function and dysfunction (Fornito et al, 2015), including Alzheimer’s disease (Stam et al, 2006, 2008), dementia (Agosta et al, 2013; Vecchio et al, 2015), schizophrenia (Alexander-Bloch et al, 2013; Gollo et al, 2018; van den Heuvel et al, 2010, 2013; Lynall et al, 2010) and Huntington’s disease (Harrington et al, 2015; McColgan et al, 2015). We discuss implications of the presented connectome alterations possibly relating for existing disease conditions such as Huntington’s and other neurodegenerative disorders

Objectives

Methods

Results

Conclusion