Feature Review Functional connectomics in depression: insights into therapies

Depression is a common mental disorder characterized by heterogeneous cog-nitive and behavioral symptoms. The emerging research paradigm of functional connectomics has provided a quantitative theoretical framework and analytic tools for parsing variations in the organization and function of brain networks in depression. In this review, we first discuss recent progress in depression -associated functional connectome variations. We then discuss treatment -specific brain network outcomes in depression and propose a hypothetical model highlighting the advantages and uniqueness of each treatment in relation to the modulation of specific brain network connectivity and symptoms of de-pression. Finally, we look to the future promise of combining multiple treatment types in clinical practice, using multisite datasets and multimodal neuroimaging approaches, and identifying biological depression subtypes.

Automated summary

The review discusses the use of functional connectomics in understanding variations in brain networks in depression and its treatment outcomes, proposing a hypothetical model for the advantages and uniqueness of each treatment method. It also explores the potential of combining multiple treatment types and using multisite datasets and multimodal neuroimaging approaches in clinical practice to identify biological depression subtypes.