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Functional Connectivity of Brain Structures Correlates with Treatment Outcome in Major Depressive Disorder

Overview
Specialty Psychiatry
Date 2011 May 11
PMID 21556277
Citations 33
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Abstract

Identifying biosignatures to assess the probability of response to an antidepressant for patients with major depressive disorder (MDD) is critically needed. Functional connectivity MRI (fcMRI) offers the promise to provide such a measure. Previous work with fcMRI demonstrated that the correlation in signal from one region to another is a measure of functional connectivity. In this pilot work, a baseline non-task fcMRI was acquired in 14 adults with MDD who were free of all medications. Participants were then treated for 8 weeks with an antidepressant and then clinically re-evaluated. Probabilistic anatomic regions of interest (ROI) were defined for 16 brain regions (eight for each hemisphere) previously identified as being important in mood disorders. These ROIs were used to determine mean time courses for each individual's baseline non-task fcMRI. The correlations in time courses between 16 brain regions were calculated. These calculated correlations were considered to signify measures of functional connectivity. The degree of connectivity for each participant was correlated with treatment outcome. Among 13 participants with 8 weeks follow-up data, connectivity measures in several regions, especially the subcallosal cortex, were highly correlated with treatment outcome. These connectivity measures could provide a means to evaluate how likely a patient is to respond to an antidepressant treatment. Further work using larger samples is required to confirm these findings and to assess if measures of functional connectivity can be used to predict differential outcomes between antidepressant treatments.

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References
1.
Rush A, Carmody T, Ibrahim H, Trivedi M, Biggs M, Shores-Wilson K . Comparison of self-report and clinician ratings on two inventories of depressive symptomatology. Psychiatr Serv. 2006; 57(6):829-37. DOI: 10.1176/ps.2006.57.6.829. View

2.
Folstein M, Folstein S, McHugh P . "Mini-mental state". A practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res. 1975; 12(3):189-98. DOI: 10.1016/0022-3956(75)90026-6. View

3.
Irwin W, Anderle M, Abercrombie H, Schaefer S, Kalin N, Davidson R . Amygdalar interhemispheric functional connectivity differs between the non-depressed and depressed human brain. Neuroimage. 2004; 21(2):674-86. DOI: 10.1016/j.neuroimage.2003.09.057. View

4.
Rush A, Gullion C, Basco M, Jarrett R, Trivedi M . The Inventory of Depressive Symptomatology (IDS): psychometric properties. Psychol Med. 1996; 26(3):477-86. DOI: 10.1017/s0033291700035558. View

5.
Taylor S, Liberzon I . Neural correlates of emotion regulation in psychopathology. Trends Cogn Sci. 2007; 11(10):413-8. DOI: 10.1016/j.tics.2007.08.006. View