Test-retest reliability of the human functional connectome over consecutive days: identifying highly reliable portions and assessing the impact of methodological choices.

Leonardo Tozzi,Cooper D Raterink,Leanne M Williams,Scott L Fleming,Zachary D Taylor

doi:10.1162/netn_a_00148

Leonardo Tozzi, Cooper D Raterink + Show 3 more

Open Access

https://doi.org/10.1162/netn_a_00148

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Journal: Network Neuroscience	Publication Date: Sep 1, 2020
Citations: 27	License type: CC BY 4.0

Affiliation: Stanford University

Abstract

Countless studies have advanced our understanding of the human brain and its organization by using functional magnetic resonance imaging (fMRI) to derive network representations of human brain function. However, we do not know to what extent these “functional connectomes” are reliable over time. In a large public sample of healthy participants (N = 833) scanned on two consecutive days, we assessed the test-retest reliability of fMRI functional connectivity and the consequences on reliability of three common sources of variation in analysis workflows: atlas choice, global signal regression, and thresholding. By adopting the intraclass correlation coefficient as a metric, we demonstrate that only a small portion of the functional connectome is characterized by good (6–8%) to excellent (0.08–0.14%) reliability. Connectivity between prefrontal, parietal, and temporal areas is especially reliable, but also average connectivity within known networks has good reliability. In general, while unreliable edges are weak, reliable edges are not necessarily strong. Methodologically, reliability of edges varies between atlases, global signal regression decreases reliability for networks and most edges (but increases it for some), and thresholding based on connection strength reduces reliability. Focusing on the reliable portion of the connectome could help quantify brain trait-like features and investigate individual differences using functional neuroimaging.

Highlights

The human brain is an extraordinarily complex network comprising one hundred billion neurons, each connected to an average of 7,000 other neurons
We explore short-term test-retest reliability of functional connectomes in a very large sample of healthy individuals scanned on two consecutive days
Regardless of atlas and without performing global signal regression term (GSR), the majority of edges of the functional connectome were in the “fair” reliability range (Figure 1)

Summary

Introduction

The human brain is an extraordinarily complex network comprising one hundred billion neurons, each connected to an average of 7,000 other neurons. Current research in neuroscience suggests that it is the architecture and dynamic interactions of neurons that give rise to complex phenomena, such as cognition and emotion (Bassett & Sporns, 2017; Lindquist et al, 2012; Mill et al, 2017) This has been called the “functional connectome,” and over the past three decades, several studies have characterized it in vivo (see, for example, Van Essen et al, 2013). Our aim is to explore the short-term reliability (in the order of days) of functional connectomes. We believe this is a fundamental step toward the identification of a persistent representation of brain function, which will facilitate the mapping of cognitive processes in individuals and will be critical for linking connectivity disruptions to brain disorders

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