Functional connectomics in depression: insights into therapies

Ya Chai; Yvette I Sheline; Desmond J Oathes; Nicholas L Balderston; Hengyi Rao; Meichen Yu

doi:10.1016/j.tics.2023.05.006

Functional connectomics in depression: insights into therapies

Trends Cogn Sci. 2023 Sep;27(9):814-832. doi: 10.1016/j.tics.2023.05.006. Epub 2023 Jun 5.

Authors

Ya Chai¹, Yvette I Sheline², Desmond J Oathes³, Nicholas L Balderston⁴, Hengyi Rao⁵, Meichen Yu⁶

Affiliations

¹ Key Laboratory of Brain-Machine Intelligence for Information Behavior (Ministry of Education and Shanghai), School of Business and Management, Shanghai International Studies University, Shanghai, China; Center for Functional Neuroimaging, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
² Center for Neuromodulation in Depression and Stress (CNDS), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. Electronic address: [email protected].
³ Center for Neuromodulation in Depression and Stress (CNDS), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Penn Brain Science, Translation, Innovation and Modulation Center (brainSTIM), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. Electronic address: [email protected].
⁴ Center for Neuromodulation in Depression and Stress (CNDS), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
⁵ Key Laboratory of Brain-Machine Intelligence for Information Behavior (Ministry of Education and Shanghai), School of Business and Management, Shanghai International Studies University, Shanghai, China; Center for Functional Neuroimaging, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. Electronic address: [email protected].
⁶ Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA; Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA; Indiana University Network Science Institute, Bloomington, IN, USA. Electronic address: [email protected].

Abstract

Depression is a common mental disorder characterized by heterogeneous cognitive 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 depression. 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.

Keywords: antidepressant treatments; connectome; depression; functional magnetic resonance imaging; resting-state networks; therapy-specific network connectivity.

Publication types

Review
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't

MeSH terms

Brain / diagnostic imaging
Connectome* / methods
Depression / therapy
Humans
Magnetic Resonance Imaging / methods
Neuroimaging

Abstract

Publication types

MeSH terms

Grants and funding