Connectome and Depression: Towards Precision Psychiatry Based on Brain Networks

Abstract

In recent decades, the study of the human connectome —the comprehensive map of the brain's neural connections— has redefined our understanding of Major Depressive Disorder (MDD) as a spectrum of functional and structural alterations in specific brain networks. This review explores evidence on functional connectivity patterns in MDD, highlighting the involvement of networks such as the default mode network (DMN), frontoparietal network (FPN), salience network (SN), and reward circuits. We analyze patterns detected using functional magnetic resonance imaging (fMRI) and their potential as biomarkers to predict treatment response to interventions currently included in clinical guidelines and widely used in practice, such as psychotherapy, first-line antidepressants (SSRIs), transcranial magnetic stimulation (TMS), electroconvulsive therapy (ECT), and sub-anesthetic doses of ketamine. For this purpose, we conducted an integrative narrative review of the scientific literature, selecting articles based on clinical relevance and methodological quality (GRADE), including meta-analyses, systematic reviews, and randomized controlled trials. These findings may contribute to a paradigm shift toward precision psychiatry, increasingly centered on the individual. Although methodological challenges persist that limit their clinical application, understanding the connectome and its relationship with MDD pathogenesis is a fundamental step toward truly personalized mental healthcare.