Functional connectivity of negative emotional processing in adolescent depression

Abstract

BACKGROUND The subgenual anterior cingulate cortex (sgACC) and its connected circuitry have been heavily implicated in emotional functioning in adolescent-onset major depressive disorder (MDD). While several recent studies have examined sgACC functional connectivity (FC) in depressed youth at rest, no studies to date have investigated sgACC FC in adolescent depression during negative emotional processing. METHODS Nineteen medication-naïve adolescents with MDD and 19 matched healthy controls (HCL) performed an implicit fear facial affect recognition task during functional magnetic resonance imaging (fMRI). We defined seeds in bilateral sgACC and assessed FC using the psychophysiological interaction method. We also applied cognitive behavioral modeling to estimate group differences in perceptual sensitivity in this task. Finally, we correlated connectivity strength with clinical data and perceptual sensitivity. RESULTS Depressed adolescents showed increased sgACC-amygdala FC and decreased sgACC-fusiform gyrus, sgACC-precuneus, sgACC-insula, and sgACC-middle frontal gyrus FC compared to HCL (p<0.05, corrected). Among the MDD, sgACC-precuneus FC negatively correlated with depression severity (p<0.05, corrected). Lastly, MDD adolescents exhibited poorer perceptual sensitivity in the task than HCL, and individual differences in perceptual sensitivity significantly correlated with sgACC FC and depression scores (p<0.05, corrected). LIMITATIONS Subjects were clinically homogenous, possibly limiting generalizability of the findings. CONCLUSIONS Adolescent depression is associated with biased processing of negative stimuli that may be driven by sgACC dysregulation and may possibly lead to an imbalance among intrinsic functional brain networks. This work also establishes the use of combining neuroimaging and cognitive behavioral modeling methods to investigate cognitive and neural differences between psychiatric and healthy populations.

Increased Default Mode Network Connectivity in Individuals at High Familial Risk for Depression

“…Antidepressants reduce DMN hyperconnectivity in depressed patients to levels comparable with healthy control participants , and reductions in prefrontal connectivity correlate with symptom improvement (Wang et al, 2015). In adolescents with depression, altered connectivity has been reported between the amygdala and prefrontal cortex (Cullen et al, 2014), as well as between the amygdala and the anterior cingulate cortex (Connolly et al, 2013;Ho et al, 2014). Our findings build upon the prior literature on the DMN and depression by demonstrating that individuals at high familial risk for MDD have increased DMN connectivity.…”

The neuroscience and context of adolescent depression

“…The onset of depression in adolescents has been associated with an increase in amygdala RSFC to the sgACC, which has been suggested to represent heightened reactivity to emotional and social stimuli (35). This finding is consistent with previously described task-based fMRI findings of limbic hyperactivation (30-32). RSFC between the amygdala and hippocampus has also been shown to be impaired (36).…”

“…The amygdala has reciprocal connections with the subgenual anterior cingulate cortex (sgACC), an area that interfaces between affective and cognitive processing, which has also been shown to exhibit hyperactivation in depressed adolescents when compared to well-matched controls (31,32). These results suggest that adolescent depression is characterised by an enhanced amygdala response to emotional stimuli, which may further impede the frontolimbic development of cognitive control mechanisms and contribute to increased emotional and social reactivity in depressed teenagers (33).…”

A generative joint model for spike trains and saccades during perceptual decision-making

“…1a). Through variations on this basic theme, accumulator models of decision-making have explained dozens of robust empirical phenomena (Palmer & Shadlen, 2005;Ratcliff, 1978;Ratcliff & Rouder, 1998;Van Zandt, 2000), and have been used as measurement tools to understand important problems including clinical disorders (Ho et al, 2014), alcohol intoxication (van Ravenzwaaij et al, 2012), sleep deprivation (Ratcliff & Van Dongen, 2011), and many others.…”