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Clinical Trial Summary

Major depressive disorder (MDD) continues to have a profound impact on individuals, families, and the health care system. Despite marked success in treating active individual episodes of unipolar depression, our understanding of the neural and cognitive mechanisms involved in the return of symptoms remains extremely limited, and few interventions exist that specifically target factors involved in prophylaxis. The research being proposed is among the first that is designed to examine neurocognitive markers for depressive relapse vulnerability and link them directly to clinical prognosis.

Hypothesis 1: Cortical midline structures (CMS) network recruitment will be associated with behavioural and neural indices of a reflexive attentional bias towards dysphoric stimuli in a divided attention task.

Hypothesis 2: Behavioural and neural indices of dysphoric attentional bias following mood challenge will predict depression relapse in prospective 18-month follow up.

Hypothesis 3: Relative to CBT, Mindfulness Based Cognitive Therapy (MBCT) will normalize CMS and right insular/fronto-opercular cortices (INS-FO) network imbalance.

Hypothesis 4: Relative to CBT, MBCT will normalize to healthy control levels, behavioural and neural indices of dysphoric attentional bias, which will be predictive of reduced relapse risk across a 24 month follow up.


Clinical Trial Description

Relapse and recurrence following recovery from Major Depressive Disorder (MDD) are common and debilitating outcomes that carry enormous social costs [1-3]. Our CIHR funded program of research has studied the nature of psychological vulnerability in affective disorder. We have recently identified the activation of a depressive cognitive mode triggered by temporary dysphoric states as a reliable risk marker for depressive relapse [4, see attached]. In parallel, functional imaging studies have increased our understanding of the neural mechanisms underlying normative affective responses [5] and have begun to examine their dysregulation in affective disorder [6-8]. Our research has identified potential brain biomarkers that predict episode relapse in unipolar depression. However, it remains unknown how these potential biomarkers are related to dysphoria-triggered information processing modes that also predict relapse, and whether these neurocognitive vulnerabilities are amenable to intervention, resulting in more lasting prophylaxis. The present proposal employs a cognitive neuroscience approach to examine whether our previously identified neural markers of depression relapse and prophylaxis are associated with a dysphoric information processing mode. In particular, we will use functional magnetic resonance imaging (fMRI) and behavioural probes to undertake a finely tuned examination of mood linked biases in attention toward dysphoric stimulus events (i.e., sad faces) to link our previously identified neural markers with a specific information processing mode. Further, our preliminary data presented here demonstrate a correlation between these mood linked neural markers and relapse, but we cannot demonstrate that these markers are causally related to relapse or prophylaxis. To address this, we will examine whether these markers and associated dysphoric attentional biases are 1) modifiable via attentional training designed to overcome reflexive modes of thought and perception and 2) are predictive of relapse status across an 24-month prospective follow up of treated patients. This research will elucidate the neural and information processing correlates that may signal relapse risk in recovered depressed patients. This knowledge will increase our limited understanding of the mechanisms underlying enduring depressive relapse vulnerability as well as assess potentially efficient strategies for relapse prophylaxis. ;


Study Design


Related Conditions & MeSH terms


NCT number NCT01178424
Study type Interventional
Source Centre for Addiction and Mental Health
Contact
Status Completed
Phase N/A
Start date August 2010
Completion date December 2017

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