Normative Modeling of Static and Dynamic Functional Connectivity

= 4705), bypassing the need for intensive reprocessing under an arbitrary unified pipeline. We evaluate the construction of a lifespan normative chart by harmonizing open-access functional MRI data extracted with highly heterogeneous processing pipelines, incorporating study-level random effects within a generalized additive model. From this well-calibrated model we drive normative trajectories of both static and dynamic functional connectivity and quantify their invariance to the choice of metric used to compute the interactions between regions. We observe a key decoupling between static and dynamic connectivity. While static connectivity exhibits a monotonic age-related decline, dynamic connectivity follows a more complex trajectory: decreasing during pediatric stabilization, peaking in mid-adulthood metastability, and ultimately declining into senescent rigidity. Overall, this framework establishes a scalable statistical blueprint for modeling functional brain organization to circumvent massive data homogenization, while preserving sensitivity to both between-subject variability and within-subject temporal dynamics.

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Publication Details

Journal
bioRxiv (Cold Spring Harbor Laboratory)
Published
2026-04-06
DOI
https://doi.org/10.64898/2026.04.03.716292
Primary Topic
Functional Brain Connectivity Studies
Type
article
Field-Weighted Citation Impact
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article

Normative Modeling of Static and Dynamic Functional Connectivity

Nina Baldy, Paul Triebkorn, V. Jirsa, Meysam Hashemi et al.
bioRxiv (Cold Spring Harbor Laboratory)
Functional Brain Connectivity Studies
article

Normative Modeling of Static and Dynamic Functional Connectivity

Nina Baldy, Paul Triebkorn, V. Jirsa, Meysam Hashemi, Spase Petkoski
article en

Abstract

= 4705), bypassing the need for intensive reprocessing under an arbitrary unified pipeline. We evaluate the construction of a lifespan normative chart by harmonizing open-access functional MRI data extracted with highly heterogeneous processing pipelines, incorporating study-level random effects within a generalized additive model. From this well-calibrated model we drive normative trajectories of both static and dynamic functional connectivity and quantify their invariance to the choice of metric used to compute the interactions between regions. We observe a key decoupling between static and dynamic connectivity. While static connectivity exhibits a monotonic age-related decline, dynamic connectivity follows a more complex trajectory: decreasing during pediatric stabilization, peaking in mid-adulthood metastability, and ultimately declining into senescent rigidity. Overall, this framework establishes a scalable statistical blueprint for modeling functional brain organization to circumvent massive data homogenization, while preserving sensitivity to both between-subject variability and within-subject temporal dynamics.

bioRxiv (Cold Spring Harbor Laboratory)
Institut de Neurosciences des Systèmes (FR)
Openalex Percentile: Top 29%
Functional Brain Connectivity Studies
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