[Depression is a common disorder with a major public health impact.] Recent research has linked [depression with abnormal function] in the default-mode network (DMN), a network of regions that is typically active at rest, and deactivates during cognitive tasks. [Depression has been linked with increased DMN connectivity] during resting-state fMRI, and a relative failure to suppress DMN when individuals view negative images. In addition, depressed individuals demonstrate enhanced and prolonged amygdala responses to negative images. [This has led to the theory that DMN abnormalities might interfere with recruitment of brain regions to regulate amygdala in depressed individuals.] [These neural markers in depressed individuals have also been related to brooding rumination, a type of maladaptive coping involving repetitive negative thoughts.] This work proposes to test this model using cross-modal comparison of fMRI data in individuals during a resting-state scan and while participants are viewing negative images. Two main hypotheses will be tested: 1) resting-state DMN [function] will predict decreased top-down regulation of emotion during viewing of negative images, and 2) increased resting-state DMN [function], and decreased top-down emotion regulation during negative-image-viewing, will be predicted by increased trait [brooding]. Assessment of top-down emotion regulation during negative-image-viewing will be multimodal and will focus on the time period 6-12s after image offset, capturing recovery from the negative image, while controlling for initial 6 s of activity in response to the image (reactivity). Measures will include amygdala activity, amygdala-prefrontal connectivity, and electromyography of the corrugator supercilii, a muscle that is a reliable indicator of the experience of negative emotion. [In addition, multivariate pattern analysis (MVPA) will be used to classify negative vs. neutral images as an alternative measure of neural responses.] DMN [function] will be assessed in two ways. First, functional connectivity between two major nodes of the DMN (medial prefrontal cortex and posterior cingulate cortex) will be calculated using correlation-based methods. Second, [a metric of DMN dominance over a cognitive control network will be calculated following methods used previously by other researchers. In order to assess how resting-state DMN function predicts top-down emotion regulation, these DMN metrics will be regressed onto all of the above metrics of emotion regulation. In order to assess how these measures correspond to trait brooding, brooding will be assessed using a standardized measure (the Ruminative Responses Scale; RRS) [and also regressed onto the outcome measures above]. This work will elucidate the relationship of DMN activity, [neural correlates of] emotion regulation and [brooding] with implications for risk and treatment of affective disorders.

Public Health Relevance

Depression is a common and devastating disorder with significant morbidity and mortality, but its cognitive and neural bases remain incompletely understood. The proposed study will assess a neurocognitive model of [depression] by modeling fMRI BOLD activity while participants are resting and also while they regulate emotion during a task, allowing us to make cross-modal comparisons of neural activity. [We will additionally assess individual differences in trait brooding, an important risk factor for depression.] Using these data, we will be able to explicate critical hypotheses about the neural basis of depression and its associations with emotional style and emotion regulation, which in turn will afford us further insights relevant to understanding mechanisms of risk and treatment for affective psychopathology.

National Institute of Health (NIH)
National Institute of Mental Health (NIMH)
Individual Predoctoral NRSA for M.D./Ph.D. Fellowships (ADAMHA) (F30)
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Special Emphasis Panel (ZRG1)
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Desmond, Nancy L
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University of Wisconsin Madison
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United States
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Westbrook, Cecilia; Patsenko, Elena G; Mumford, Jeanette A et al. (2018) Frontoparietal processing of stress-relevant information differs in individuals with a negative cognitive style. J Abnorm Psychol 127:437-447