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Clinical neuroprediction: Amygdala reactivity predicts depressive symptoms 2 years later
Author(s) -
Whitney I. Mattson,
Luke W. Hyde,
Daniel S. Shaw,
Erika E. Forbes,
Christopher S. Monk
Publication year - 2016
Publication title -
social cognitive and affective neuroscience
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.229
H-Index - 103
eISSN - 1749-5024
pISSN - 1749-5016
DOI - 10.1093/scan/nsw018
Subject(s) - amygdala , psychology , reactivity (psychology) , facial expression , depressive symptoms , depression (economics) , clinical psychology , developmental psychology , audiology , cognition , psychiatry , neuroscience , medicine , alternative medicine , communication , pathology , economics , macroeconomics
Depression is linked to increased amygdala activation to neutral and negatively valenced facial expressions. Amygdala activation may be predictive of changes in depressive symptoms over time. However, most studies in this area have focused on small, predominantly female and homogenous clinical samples. Studies are needed to examine how amygdala reactivity relates to the course of depressive symptoms dimensionally, prospectively and in populations diverse in gender, race and socioeconomic status. A total of 156 men from predominately low-income backgrounds completed an fMRI task where they viewed emotional facial expressions. Left and right amygdala reactivity to neutral, but not angry or fearful, facial expressions relative to a non-face baseline at age 20 predicted greater depressive symptoms 2 years later, controlling for age 20 depressive symptoms. Heightened bilateral amygdala reactivity to neutral facial expressions predicted increases in depressive symptoms 2 years later in a large community sample. Neutral facial expressions are affectively ambiguous and a tendency to interpret these stimuli negatively may reflect to cognitive biases that lead to increases in depressive symptoms over time. Individual differences in amygdala reactivity to neutral facial expressions appear to identify those at most risk for a more problematic course of depressive symptoms across time.

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