Introduction
Functional connectivity (FC) derived from MRI has proven effective in estimating brain age [1], an important biomarker of neurological health. However, conventional FC-based models lack neurobiological specificity. This study integrates molecular information from PET/SPECT templates to generate molecular-enriched FC maps, evaluating their predictive power for brain age.

Methods
Resting-state fMRI and anatomical T1-weighted images from 627 healthy participants (315F/312M, mean age 53.76±18.47 years) from the Cam-CAN dataset [2] were analyzed. Preprocessing followed standardized pipelines (fMRIPrep [3], XCP-D [4]), including motion correction, nuisance regression, temporal filtering and smoothing. Molecular-enriched FC maps were derived using the Receptor-Enriched Analysis of functional Connectivity by Targets (REACT) framework [5], incorporating templates for dopamine (DAT), noradrenaline (NET), and serotonin (SERT) transporters. Mean FC values were extracted from 247 cortical, subcortical, and cerebellar regions. Age-related features were identified via stepwise backward regression, and predictive models were trained both using linear regression and Support Vector Regression (SVR) with 10-fold cross-validation.

Results
Molecular-enriched FC explained a substantial portion of age variance (DAT R²=0.68, NET R²=0.68, SERT R²=0.69, Fig. 1). Salience/Ventral Attention network features were most frequently selected across models (Fig. 2). SVR models performed best with DAT features (R²=0.53, mean absolute error =9.98 years), with comparable results for NET and SERT.

Conclusions
The linear regression model reveals that molecular-enriched FC maps explain a significant portion of age variance, consistent with previous FC studies [1], supporting their utility in brain aging research. Future work will incorporate structural imaging to improve prediction accuracy.

Figures

Acknowledgements

This research was funded by the Ministry of University and Research within the Complementary National Plan PNC-I.1, “Research initiatives for innovative technologies and pathways in the health and welfare sector, D.D. 931 of 06/06/2022, PNC0000002 DARE – Digital Lifelong Prevention CUP: B53C22006440001.”

References

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[5]       O. Dipasquale, P. Selvaggi, M. Veronese, A. S. Gabay, F. Turkheimer, and M. A. Mehta, “Receptor-Enriched Analysis of functional connectivity by targets (REACT): A novel, multimodal analytical approach informed by PET to study the pharmacodynamic response of the brain under MDMA,” NeuroImage, vol. 195, pp. 252–260, Jul. 2019, doi: 10.1016/j.neuroimage.2019.04.007.