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Linking molecular mechanisms with large-scale brain dynamics remains a fundamental challenge in computational psychiatry. Receptor-informed whole-brain models have provided mechanistic insights into pharmacological interventions, yet they have largely relied on single-receptor topographies that cannot explain the collective response of multiple receptor systems. Here, we combined pharmacological resting-state fMRI with a whole-brain model incorporating cortical expression of adrenergic and dopaminergic receptors to investigate the effects of atomoxetine, a norepinephrine reuptake inhibitor that globally elevates catecholaminergic signaling. Using receptor similarity, we first identified a catecholaminergic chemoarchitecture comprising frontal, posterior and temporal networks, providing the neurochemical scaffold for interpreting atomoxetine-induced brain dynamics. Empirically, atomoxetine selectively stabilized functional connectivity dynamics within the posterior catecholaminergic network. Whole-brain modeling revealed that although individual receptor parameters did not differ between conditions, their collective organization converged toward empirical receptor binding affinities. Remarkably, the simulated atomoxetine state was reconstructed from the placebo configuration through a negative reweighting along this receptor-affinity axis. In silico forward modeling showed that this affinity-driven redistribution gave rise to a cortical modulation pattern aligned with a frontal chemoarchitectural gradient, which was sufficient to simulate the observed dynamical and connectivity changes. Together, these findings suggest receptor binding affinity as a key organizing principle linking molecular receptor organization to brain dynamics, providing a model-based, biologically interpretable computational mechanism through which global catecholaminergic perturbations reshape whole-brain function.
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Monge-Asensio et al. (2026) studied this question.
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