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Brain Connect. 2017 Oct;7(8):491-503. doi: 10.1089/brain.2017.0539.

On the Origin of Individual Functional Connectivity Variability: The Role of White Matter Architecture.

Author information

1
1 Department of Nuclear Medicine and Radiobiology, Faculty of Medicine and Health Science, University of Sherbrooke , Sherbrooke, Canada .
2
2 Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University , Cardiff, United Kingdom .
3
3 Sherbrooke Connectivity Imaging Lab (SCIL), Computer Science Department, Faculty of Science, University of Sherbrooke , Sherbrooke, Canada .
4
4 Signal Processing Lab (LTS5) , Ecole Polytechnique Federale de Lausanne, Lausanne, Switzerland .
5
5 Division of Neurosurgery and Neuro-Oncology, Faculty of Medicine and Health Science, University of Sherbrooke , Sherbrooke, Canada .

Abstract

Fingerprint patterns derived from functional connectivity (FC) can be used to identify subjects across groups and sessions, indicating that the topology of the brain substantially differs between individuals. However, the source of FC variability inferred from resting-state functional magnetic resonance imaging remains unclear. One possibility is that these variations are related to individual differences in white matter structural connectivity (SC). However, directly comparing FC with SC is challenging given the many potential biases associated with quantifying their respective strengths. In an attempt to circumvent this, we employed a recently proposed test-retest approach that better quantifies inter-subject variability by first correcting for intra-subject nuisance variability (i.e., head motion, physiological differences in brain state, etc.) that can artificially influence FC and SC measures. Therefore, rather than directly comparing the strength of FC with SC, we asked whether brain regions with, for example, low inter-subject FC variability also exhibited low SC variability. From this, we report two main findings: First, at the whole-brain level, SC variability was significantly lower than FC variability, indicating that an individual's structural connectome is far more similar to another relative to their functional counterpart even after correcting for noise. Second, although FC and SC variability were mutually low in some brain areas (e.g., primary somatosensory cortex) and high in others (e.g., memory and language areas), the two were not significantly correlated across all cortical and sub-cortical regions. Taken together, these results indicate that even after correcting for factors that may differently affect FC and SC, the two, nonetheless, remain largely independent of one another. Further work is needed to understand the role that direct anatomical pathways play in supporting vascular-based measures of FC and to what extent these measures are dictated by anatomical connectivity.

KEYWORDS:

connectivity; diffusion MRI; inter-subject variability; resting-state fMRI; tractography

PMID:
28825322
DOI:
10.1089/brain.2017.0539
[Indexed for MEDLINE]

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