Individual variability in the human connectome maintains selective cross-modal consistency and shares microstructural signatures

Abstract

Individuals are different in their behavioural responses and cognitive abilities. Neural underpinnings of individual differences are largely unknown. Here, by using multimodal imaging data including diffusion MRI, functional MRI and MEG, we show the consistency of interindividual variation of connectivity across modalities. We demonstrated that regional differences in individual variability of structural and functional connectomes is characterized by higher variability in association cortices and lower variability in sensory and visual cortices. This pattern is consistent across all modalities at varying degrees as shown by significant alignment between functional and structural connectome variabilities at several clusters of brain regions. Variability in connectivity is associated with cortical myelin content and microstructural properties of connections. Our findings contribute to understanding of individual differences in functional and structural organization of brain and facilitate fingerprinting applications.

Structural insight into the individual variability architecture of the functional brain connectome

“…First, a relatively large sample size with repeated structural and functional brain scans is needed. Previously, Camberland et al (Chamberland et al, 2017) and Karahan et al (Karahan et al, 2021) both reported no significant correlation between SC and FC variability at a global level, which could be attributable to the small sample sizes of their studies (Chamberland et al, 2017;Karahan et al, 2021) or the confounds of intrasubject variations (Karahan et al, 2021). In this study, we found that the correlation between FC variability maps before and after regressing intraindividual variance was only 0.41 (0.94 for principal SC variability), highlighting the necessity of removing intraindividual FC variance when studying the relationship between FC and SC variability.…”

“…To date, only three studies have examined the relationship between interindividual FC and SC variability patterns. Of them, two studies reported nonsignificant spatial correlations between FC variability and tractography-based SC variability (Chamberland et al, 2017; Karahan et al, 2021), which could be attributable to a relatively small sample size (n = 9 (Chamberland et al, 2017) and n = 29 (Karahan et al, 2021)) and confounds of intraindividual variation (Karahan et al, 2021). A very recent study reported a significant correlation between interindividual variability patterns of FC and tractography-based SC (Mansour et al, 2021).…”

Population heterogeneity in clinical cohorts affects the predictive accuracy of brain imaging

“…Less myelination might enable greater plasticity in association areas both during development and adulthood [ 114 – 116 ]. Neural circuits with less myelinated regions have previously been shown to exhibit increased functional and structural variability [ 117 ]. Taken together, these factors might be related to, at least partly, the high susceptibility of our predictive models to population diversity in the default mode network, and other associative cortical regions.…”

The Cost of Untracked Diversity in Brain-Imaging Prediction

“…Less myelination might enable greater plasticity in association areas both during development and adulthood (Glasser & Van Essen, 2011; Timmler & Simons, 2019; Turner, 2019). Neural circuits with less myelinated regions have previously been shown to exhibit increased functional and structural variability (Karahan et al, 2021). Taken together, these factors might be related to, at least partly, the high susceptibility of our predictive models to population diversity in the default mode network, and other associative cortical regions.…”