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. 2015 Feb 1:172:8-17.
doi: 10.1016/j.jad.2014.09.028. Epub 2014 Sep 26.

A systematic review of relations between resting-state functional-MRI and treatment response in major depressive disorder

Gabriel S Dichter  1 , Devin Gibbs  2 , Moria J Smoski  3
Affiliations

A systematic review of relations between resting-state functional-MRI and treatment response in major depressive disorder

Gabriel S Dichter et al. J Affect Disord. .

Abstract

Background: Resting-state functional magnetic resonance imaging (fMRI) is a promising predictor of treatment response in major depressive disorder (MDD).

Methods: A search for papers published in English was conducted using PubMed with the following words: depression, treatment, resting-state, connectivity, and fMRI. Findings from 21 studies of relations between resting-state fMRI and treatment response in MDD are presented, and common findings and themes are discussed.

Results: The use of resting-state fMRI in research on MDD treatment response has yielded a number of consistent findings that provide a basis for understanding the potential mechanisms of action of antidepressant treatment response. These included (1) associations between response to antidepressant medications and increased functional connectivity between frontal and limbic brain regions, possibly resulting in greater inhibitory control over neural circuits that process emotions; (2) connectivity of visual recognition circuits in studies that compared treatment resistant and treatment sensitive patients; (3) response to TMS was consistently predicted by subcallosal cortex connectivity; and (4) hyperconnectivity of the default mode network and hypoconnectivity of the cognitive control network differentiated treatment-resistant from treatment-sensitive MDD patients.

Limitations: There was also considerable variability between studies with respect to study designs and analytic strategies that made direct comparisons across all studies difficult.

Conclusions: Continued standardization of study designs and analytic strategies as well as aggregation of larger datasets will allow the field to better elucidate the potential mechanisms of action of treatment response in patients with MDD to ultimately generate algorithms to predict which patients will respond to which antidepressant treatments.

Keywords: Connectivity; Default-mode; Depression; Resting state; Treatment; fMRI.

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