Neuroimaging and psychological well-being: Current correlates, limitations, and challenges for biomarker development

Background Psychological well-being is increasingly recognized as a determinant of mental and physical health, yet its assessment remains dominated by subjective self-reports constrained by cultural bias and temporal variability. Neuroimaging offers the potential for identifying objective indicators, although its application to psychological well-being remains at an early stage. Aim To synthesize structural, functional, and molecular neuroimaging evidence of psychological well-being and evaluate its readiness for biomarker development. Methods A narrative review was conducted integrating evidence from structural imaging (MRI, diffusion imaging), functional modalities (fMRI, EEG, MEG), and molecular imaging (PET), alongside psychometric assessments of well-being and affective states. Results Structural and diffusion imaging link white matter integrity, particularly in the corpus callosum and fronto-limbic tracts, with adaptive functioning. Functional MRI and electrophysiological studies reveal connectivity and oscillatory dynamics involving the prefrontal cortex (PFC), insula, and limbic regions that support affect regulation. Molecular imaging highlights neurotransmitter systems, including dopaminergic and serotonergic pathways, underlying motivation and mood. Across modalities, converging evidence identifies the PFC, insula, limbic regions, and corpus callosum as key neural correlates of well-being. However, the evidence is largely based on cross-sectional designs, with small effect sizes, methodological heterogeneity, and substantial overlap with stress and psychopathology, which limits specificity. Conclusion Neuroimaging provides valuable insights into the neural correlates of psychological well-being, but current evidence does not yet meet criteria required for clinically meaningful biomarkers. Progress requires longitudinal multimodal designs, standardised protocols, cross-cultural validation, and improved integration with psychometric and physiological measures to achieve clinically meaningful and predictive biomarkers.