Abstract

While the extant literature has focused on major depressive disorder (MDD) as being characterized by abnormalities in processing affective stimuli (e.g., facial expressions), little is known regarding which specific aspects of cognition influence the evaluation of affective stimuli, and what are the underlying neural correlates. To investigate these issues, we assessed 26 adolescents diagnosed with MDD and 37 well-matched healthy controls (HCL) who completed an emotion identification task of dynamically morphing faces during functional magnetic resonance imaging (fMRI). We analyzed the behavioral data using a sequential sampling model of response time (RT) commonly used to elucidate aspects of cognition in binary perceptual decision making tasks: the Linear Ballistic Accumulator (LBA) model. Using a hierarchical Bayesian estimation method, we obtained group-level and individual-level estimates of LBA parameters on the facial emotion identification task. While the MDD and HCL groups did not differ in mean RT, accuracy, or group-level estimates of perceptual processing efficiency (i.e., drift rate parameter of the LBA), the MDD group showed significantly reduced responses in left fusiform gyrus compared to the HCL group during the facial emotion identification task. Furthermore, within the MDD group, fMRI signal in the left fusiform gyrus during affective face processing was significantly associated with greater individual-level estimates of perceptual processing efficiency. Our results therefore suggest that affective processing biases in adolescents with MDD are characterized by greater perceptual processing efficiency of affective visual information in sensory brain regions responsible for the early processing of visual information. The theoretical, methodological, and clinical implications of our results are discussed.

Highlights

  • Major depressive disorder (MDD) is a prevalent condition that is associated negative mood and emotional dysregulation, with an onset that increases dramatically during adolescence (Merikangas et al, 2009; Kessler et al, 2010)

  • We examined the relationship between perceptual processing efficiency—as ascertained from response time (RT) distributions subjected to a cognitive-behavioral model of RT—and brain activation in adolescents with MDD and well-matched healthy controls (HCL) during performance of a facial emotion identification task

  • We found that while adolescents with MDD and HCL did not differ in group-level estimates of perceptual processing efficiency (Figure 3), adolescents with MDD exhibited abnormal activation to emotional faces throughout the face processing network, including early visual processing regions, limbic and paralimbic regions, and top–down frontal regions (Figure 4)

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Summary

Introduction

Major depressive disorder (MDD) is a prevalent condition that is associated negative mood and emotional dysregulation, with an onset that increases dramatically during adolescence (Merikangas et al, 2009; Kessler et al, 2010). Prior research examining the neurobiological mechanisms of individuals with MDD have used facial emotion processing tasks in conjunction with functional magnetic resonance imaging (fMRI) to probe how MDD is related to neural systems supporting affective processing (Fusar-Poli et al, 2009; Stuhrmann et al, 2011) In these fMRI studies of facial emotion processing, adults with MDD compared to healthy controls exhibit brain activation differences at multiple levels in the information processing: from visual areas such as the fusiform gyrus and the middle occipital cortex involved in early visual processing of affective stimuli, to limbic and paralimbic regions such as the amygdala and insula involved in evaluating and integrating sensory and affective information, to prefrontal areas such as dorsolateral prefrontal cortex and ventromedial prefrontal cortex involved in top-down emotion regulation (Haxby et al, 2000; Stuhrmann et al, 2011). Relating biases in the processing of emotional information to neural substrates in adolescents with MDD is critical if we are to understand how these cognitive processes may contribute to the early development of depressive symptoms

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