Test–retest reliability and predictive utility of a macroscale principal functional connectivity gradient

Abstract

Mapping individual differences in brain function has been hampered by poor reliability as well as limited interpretability. Leveraging patterns of brain‐wide functional connectivity (FC) offers some promise in this endeavor. In particular, a macroscale principal FC gradient that recapitulates a hierarchical organization spanning molecular, cellular, and circuit level features along a sensory‐to‐association cortical axis has emerged as both a parsimonious and interpretable measure of individual differences in behavior. However, the measurement reliabilities of this FC gradient have not been fully evaluated. Here, we assess the reliabilities of both global and regional principal FC gradient measures using test–retest data from the young adult Human Connectome Project (HCP‐YA) and the Dunedin Study. Analyses revealed that the reliabilities of principal FC gradient measures were (1) consistently higher than those for traditional edge‐wise FC measures, (2) higher for FC measures derived from general FC (GFC) in comparison with resting‐state FC, and (3) higher for longer scan lengths. We additionally examined the relative utility of these principal FC gradient measures in predicting cognition and aging in both datasets as well as the HCP‐aging dataset. These analyses revealed that regional FC gradient measures and global gradient range were significantly associated with aging in all three datasets, and moderately associated with cognition in the HCP‐YA and Dunedin Study datasets, reflecting contractions and expansions of the cortical hierarchy, respectively. Collectively, these results demonstrate that measures of the principal FC gradient, especially derived using GFC, effectively capture a reliable feature of the human brain subject to interpretable and biologically meaningful individual variation, offering some advantages over traditional edge‐wise FC measures in the search for brain–behavior associations.

Functional gradients reveal cortical hierarchy changes in multiple sclerosis

“…Instead, the secondary gradient showed a gradual axis of connectivity variation, with the visual network on one end and the DMN on the other, with intermediary networks in between, similar to the principal gradient previously identified in (Margulies et al, 2016 ). This discrepancy has been previously observed and attributed to different factors, including preprocessing strategies (Hong et al, 2020 ; Knodt et al, 2023 ), age range of the studied population (Bethlehem et al, 2020 ; Hu et al, 2022 ), and sample size (Zang et al, 2023 ), whereas it should be independent from parcellation resolution (Vos de Wael et al, 2020 ). In this study, participants were relatively young, thus suggesting that age should not significantly affect FGs; on the other hand, the sample size was not as small as in other works reporting the canonical FGs (Lee et al, 2023 ; Zhang et al, 2022 ).…”

Improving Predictability, Test-Retest Reliability and Generalisability of Brain-Wide Associations for Cognitive Abilities via Multimodal Stacking

“…Here the researchers examined test-retest reliability of Task Contrasts in certain areas, known to be strongly elicited in each task, across two-time points and found a poor level of test-retest reliability across different tasks and two datasets: the Human Connectome Project Young Adult (HCP Young Adults) 18 , and the Dunedin Multidisciplinary Health and Development Study (Dunedin Study) 17 . This poor level of test-retest reliability from Task Contrasts is concerning, especially when compared to the higher levels of test-retest reliability found from structural MRI, Rest FC and Task FC 8,37,38 . In fact, structural MRI provided reliability that was almost at the ceiling 8 .…”

Exploring sex-specific neuroendocrine influences on the sensorimotor-association axis in single individuals

“…However, we explicitly made methodological decisions aimed at reducing biases and noise particularly pertaining to daily variability and endocrine effects. First, we used the S-A axis as our measure of functional cortical organization, which -through its low dimensionality and thresholding-has been shown to have greater test-retest reliability than more commonly used measures of unthresholded edge-wise functional connectivity [61,62]. In terms of data design, study sessions were time-locked, and food and caffeine intake prior to study sessions was strictly controlled through abstinence in order to limit confounding physiological effects [46,47].…”

“…Conceptually, the S-A axis has been shown to reflect both developmental [4] and evolutionary [55,56] mechanisms, aligning with microstructural variation [55,[57][58][59], as well as capturing organizational differences between the sexes [60]. Methodologically, the S-A axis has demonstrated suitable levels of reproducibility, predictive validity, and test-retest reliability [61,62]. As such, studying daily intra-individual variability along the S-A axis as well as associated sex-specific neuroendocrine factors would allow to contextualize subtle intra-individual changes in the functional connectome at a meaningful organizational level.…”