Neural mechanisms of subclinical depressive symptoms in women: a pilot functional brain imaging study
1 Carolina Institute for Developmental Disabilities, University of North Carolina at Chapel Hill School of Medicine, CB# 3366, 101 Manning Drive, Chapel Hill, NC, 27599-7160, USA
2 Department of Psychiatry and Behavioral Sciences, Duke University Medical Center, Durham, NC, USA
3 Department of Psychiatry, University of North Carolina at Chapel Hill School of Medicine, Chapel Hill, NC, USA
4 Duke-UNC Brain Imaging and Analysis Center, Duke University Medical Center, Durham, NC, USA
5 Department of Psychology and Neuroscience, University of Colorado Boulder, UCB 345, Boulder, CO, 80309-0345, USA
BMC Psychiatry 2012, 12:152 doi:10.1186/1471-244X-12-152Published: 21 September 2012
Studies of individuals who do not meet criteria for major depressive disorder (MDD) but with subclinical levels of depressive symptoms may aid in the identification of neurofunctional abnormalities that possibly precede and predict the development of MDD. The purpose of this study was to evaluate relations between subclinical levels of depressive symptoms and neural activation patterns during tasks previously shown to differentiate individuals with and without MDD.
Functional magnetic resonance imaging (fMRI) was used to assess neural activations during active emotion regulation, a resting state scan, and reward processing. Participants were twelve females with a range of depressive symptoms who did not meet criteria for MDD.
Increased depressive symptom severity predicted (1) decreased left midfrontal gyrus activation during reappraisal of sad stimuli; (2) increased right midfrontal gyrus activation during distraction from sad stimuli; (3) increased functional connectivity between a precuneus seed region and left orbitofrontal cortex during a resting state scan; and (4) increased paracingulate activation during non-win outcomes during a reward-processing task.
These pilot data shed light on relations between subclinical levels of depressive symptoms in the absence of a formal MDD diagnosis and neural activation patterns. Future studies will be needed to test the utility of these activation patterns for predicting MDD onset in at-risk samples.