Reversed frontotemporal connectivity during emotional face processing in remitted depression

Abstract

Background: Vulnerability to relapse persists after remission of an acute episode of major depressive disorder. This has been attributed to abnormal biases in the processing of emotional stimuli in limbic circuits. However, neuroimaging studies have not so far revealed consistent evidence of abnormal responses to emotional stimuli in limbic structures, such as the amygdala, in remitted depression. This suggests the problem might lie in the integrated functioning of emotion processing circuits.

Methods: We recruited 22 unmedicated patients in remission from major depressive disorder (rMDD) and 21 age-matched healthy control subjects. Functional magnetic resonance imaging was performed during a face emotion processing task. Dynamic causal modeling was used with Bayesian model selection to determine the most likely brain networks and valence-specific modulation of connectivity in healthy control subjects and rMDD.

Results: In healthy volunteers, sad faces modulated bi-directional connections between amygdala and orbitofrontal cortex and between fusiform gyrus and orbitofrontal cortex. Happy faces modulated unidirectional connections from fusiform gyrus to orbitofrontal cortex. In rMDD, the opposite pattern was observed, with evidence of happy faces modulating bidirectional frontotemporal connections and sad faces modulating unidirectional fusiform-orbitofrontal connections.

Conclusions: Participants with rMDD have abnormal modulation of frontotemporal effective connectivity in response to happy and sad face emotions, despite normal activations within each region. Specifically, processing of mood incongruent happy information was associated with a more richly modulated frontotemporal brain network, whereas mood congruent sad information was associated with less network modulation. This supports a hypothesis of dysfunction within cortico-limbic connections in individuals vulnerable to depression.

Figure 1

The models tested with Bayesian model selection. (A) Fully connected model of intrinsic connectivity with feedforward and feedback connections for each part of the network; (B) the patterns of modulatory influences of emotion on connectivity among fusiform gyrus (FG), amygdala (Amyg), and lateral orbitofrontal cortex (LOFC). These 21 models belong to one of seven model “families” (see Methods). V1, visual cortex.

Figure 2

Results of Bayesian Model Selection for identification of the most likely family (F1–F7) and, within the winning family, the most likely network models (Models 1–3 in Family F7, Models 1–6 in Family F1). Results are shown separately for: (A) Healthy Control Group Happy Condition; families and models; (B) Healthy Control Group Sad Condition; families and models; (C) Remitted Depressed Group Happy Condition; families and models; and (D) Remitted Depressed Group Sad Condition; families and models. For each of A–D, the differences in log-evidences between the first- and second-place models within Families 1 and 7 are highly significant (very strong evidence for a difference), with standard Bayesian thresholds (50), as can most easily be seen from the differences in the posterior probabilities of each family/model.

Figure 3

Results of psychophysiological interaction analysis. (A) Relative strengths of connectivity from the amygdala for processing sad versus neutral faces in remitted major depressive disorder (rMDD) and healthy control subjects (HC). (B) Relative amygdala connection strengths for processing happy versus neutral faces. OFC, orbitofrontal cortex.