Neuroimaging in Psychiatry: An Overview

Psychiatric diagnoses remain largely reliant on clinical observation and self-report, lacking validated biological markers to ensure reliability and specificity. Neuroimaging has emerged as a critical tool to bridge this gap by enabling in vivo assessment of brain structure, connectivity, and neurochemistry. Structural modalities such as MRI and diffusion tensor imaging (DTI) have illuminated consistent alterations in cortical and white-matter networks across schizophrenia, obsessive-compulsive disorder, bipolar disorder, and major depressive disorder, offering insights into shared and disorder-specific pathophysiology. Functional imaging techniques—including fMRI, PET, and SPECT—have further delineated dysconnectivity in key circuits and neurotransmitter abnormalities, reinforcing a network-based model of mental illness. While neuroimaging currently lacks diagnostic specificity for individual patients, its integration with machine learning, genetics, and multimodal biomarkers holds promise for precision psychiatry. Future directions emphasize large-scale harmonized datasets, multimodal fusion, and AI-assisted analysis to develop clinically meaningful biomarkers that can guide diagnosis, predict treatment response, and inform targeted neuromodulation strategies. Neuroimaging thus represents a transformative frontier linking neuroscience and psychiatric practice.