Distance-independent functional connectivity preferentially develops in associative regions
Poster No:
982
Submission Type:
Abstract Submission
Authors:
Matthew Danyluik1, Olivier Parent2, Yasser Iturria-Medina3, Mallar Chakravarty4
Institutions:
1McGill University, Montreal, Quebec, 2Douglas Mental Health University Institute, Montreal, Quebec, 3McGill, Montreal, Quebec, 4McGill University, Montréal, QC
First Author:
Co-Author(s):
Introduction:
Whole-brain functional dynamics are thought to be governed by cortical geometry, as predicted by neural field theory, which suggests that the interactions between cell populations can be explained by the distance between them (Pang et al., 2023). However, since associative regions have more long-range functional connections than sensory ones, perhaps enabling cross-modality integration (Sepulcre et al., 2010), it is unclear if distance can explain functional coupling equivalently well across the cortical hierarchy. Moreover, since associative systems continue to develop into adulthood, we may expect that adolescence is a critical period where any distance-independent connectivity in high-order regions should emerge, alongside cognitive function.
Methods:
To study the distance-dependence of functional connectivity, we first analyzed 57 healthy controls aged 16-35 from the Human Connectome Project for Early Psychosis. Resting state functional images were mapped to the fsLR 32k surface and parcellated with the Schaefer 400 atlas. We calculated the geodesic distance between region pairs using the surfdist toolbox (Margulies et al., 2016) and participant-level functional connectivity matrices using Pearson's correlation. Next, for each participant, we used region-wise generalized additive models with 8th-order B-splines to predict functional connectivity from distance, giving individual R2 maps quantifying the distance-dependence of each region's functional connectivity profile (Fig. 1A). Further, we labelled each connection according to the assignment of its two regions in Mesulam's cortical hierarchy (sensory, unimodal, associative, or limbic), calculating the distance-connectivity R2 for each possible connection type. We then applied our framework to two developmental datasets curated by the Reproducible Brain Charts initiative (Shafiei et al., 2024): the Philadelphia Neurodevelopmental Cohort (PNC, n = 1188, aged 8-23) and the psychopathology-enriched Healthy Brain Network (HBN, n = 1058, aged 5-21). To evaluate how the distance-connectivity relationship varied throughout development, we used linear models to predict R2 from age while covarying for sex, both for each region and Mesulam connection type. Finally, to gain insights into the features which best explained developmental variability, we spatially correlated regional age effect statistics with annotations provided by the neuromaps toolbox (Markello et al., 2022).
Results:
In controls, the distance-connectivity relationship varied across the cortex: visually, the coupling between sensory regions and the rest of the brain could largely be explained by distance, while associative regions were less distance-dependent (Fig. 1B). When grouping region pairs by their positions in Mesulam's cortical hierarchy, we saw that connections between sensory and unimodal regions were better explained by distance than any involving limbic or associative nodes (Fig. 1B). Further, in both typically and atypically developing samples, age effects on the distance-connectivity relationship resembled a sensory-associative hierarchy (Fig. 2A). Strikingly, distance-independence preferentially emerged with age in associative-associative connections, as well as in regions characterized by lower myelin content and a longer timescale (mainly in the HBN) (Fig. 2B-C).
Conclusions:
Distance alone explained much of the variance in functional connectivity, though mainly in low-order sensory cortex. Conversely, during neurodevelopment, distance-independent functional connectivity selectively emerged within associative regions, as well as in regions inferred to have low myelin content and a long timescale (i.e., greater temporal autocorrelation), two factors thought to favour prolonged plasticity during adolescence (Sydnor et al., 2021). Together, the ability of associative regions to break the constraint of cortical geometry as the brain matures may relate to its developing capacity for high-order function.
Lifespan Development:
Early life, Adolescence, Aging 1
Modeling and Analysis Methods:
Connectivity (eg. functional, effective, structural) 2
Task-Independent and Resting-State Analysis
Keywords:
Development
FUNCTIONAL MRI
Other - Geometry; Connectivity
1|2Indicates the priority used for review
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Provide references using APA citation style.
Markello, R. D. et al. (2022). neuromaps: Structural and functional interpretation of brain maps. Nature Methods, 19(11), 1472–1479. https://doi.org/10.1038/s41592-022-01625-w
Pang, J. C. et al. (2023). Geometric constraints on human brain function. Nature, 1–9. https://doi.org/10.1038/s41586-023-06098-1
Sepulcre, J. et al. (2010). The Organization of Local and Distant Functional Connectivity in the Human Brain. PLOS Computational Biology, 6(6), e1000808. https://doi.org/10.1371/journal.pcbi.1000808
Shafiei, G. et al. (2024). Reproducible Brain Charts: An Open Data Resource for Mapping the Developing Brain and Mental Health. https://doi.org/10.17605/OSF.IO/ER248
Sydnor, V. J. et al. (2021). Neurodevelopment of the association cortices: Patterns, mechanisms, and implications for psychopathology. Neuron, 109(18), 2820–2846. https://doi.org/10.1016/j.neuron.2021.06.016