Effects of an antidepressant on neural correlates of emotional processing in patients with major depression
ABSTRACT We measured brain activation in patients with major depressive disorder when exposed to emotional pictures before and after antidepressant treatment. The participants included 18 first-episode unmedicated patients with current major depressive disorder and 18 age- and gender-matched control subjects. All subjects performed an emotional task during functional magnetic resonance imaging scanning at baseline and after 8 weeks of fluoxetine treatment. Unmedicated depressed patients showed lower accuracy rates (0.53±0.26) than did subjects in the control group (0.71±0.18) while viewing positive pictures. During exposure to positive stimuli, decreased activations were seen in the right insula (BA13) and left anterior cingulate cortex (BA32) in patients after antidepressant treatment. After antidepressant treatment, patients exhibited greater activation in the right middle frontal gyrus (BA8,9) in response to negative stimuli. Our results suggest that the prefrontal cortex, anterior cingulate cortex and insula may play key roles as biological markers for treatment response and as predictors of therapeutic success.
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ABSTRACT: Major Depressive Disorder (MDD) is a leading cause of disability globally. Currently available treatments have limited efficacy and combination strategies are frequently used. Several lines of research have demonstrated that MDD patients experience impairments in various components of affective processing, including regulation of affective states. To identify baseline and 1-week neuroimaging predictors of response to a 6-week trial of fluoxetine/olanzapine combination treatment during an affective processing task. Twenty-one MDD patients and 18 healthy controls were enrolled in the study. MDD patients were treated for 6 weeks with fluoxetine (40-60mg/day) and olanzapine (5-12.5mg/day). All participants viewed images from the International Affective Picture Rating System during a functional magnetic resonance (fMRI) scan at baseline and 1 week. There was a 57% response rate (defined as a 50% decrease in Hamilton Rating Scale for Depression-17 item) at 6 weeks. At baseline, responders had increased premotor activity while viewing negative images compared to non-responders and healthy controls. Higher baseline premotor activity was also predictive of greater percent change on the HAMD-17 and improvement in negative disposition and behavioral drive. Non-responders exhibited increased insular activity at baseline compared to responders. Higher activity in the posterior cingulate cortex was also predictive of greater percent change on the HAMD-17. Change from baseline to 1 week did not produce any significant predictive findings. Treatment with fluoxetine/olanzapine demonstrated similar biomarkers of response to monotherapeutic strategies. In particular, posterior cingulate cortex, anterior insula, and premotor cortex may show predictive differences in their response to affective images prior to treatment. Further research needs to be conducted to determine the utility of early changes in emotion circuitry in predicting antidepressant response.Journal of Affective Disorders 08/2013; 151(2). DOI:10.1016/j.jad.2013.06.050 · 3.71 Impact Factor
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ABSTRACT: Major depressive disorder (MDD) is a serious condition with a lifetime prevalence exceeding 16% worldwide. MDD is a heterogeneous disorder that involves multiple behavioral symptoms on the one hand and multiple neuronal circuits on the other hand. In this review, we integrate the literature on cognitive and physiological biomarkers of MDD with the insights derived from mathematical models of brain networks, especially models that can be used for fMRI datasets. We refer to the recent NIH research domain criteria initiative, in which a concept of "constructs" as functional units of mental disorders is introduced. Constructs are biomarkers present at multiple levels of brain functioning - cognition, genetics, brain anatomy, and neurophysiology. In this review, we propose a new approach which we called circuit to construct mapping (CCM), which aims to characterize causal relations between the underlying network dynamics (as the cause) and the constructs referring to the clinical symptoms of MDD (as the effect). CCM involves extracting diagnostic categories from behavioral data, linking circuits that are causal to these categories with use of clinical neuroimaging data, and modeling the dynamics of the emerging circuits with attractor dynamics in order to provide new, neuroimaging-related biomarkers for MDD. The CCM approach optimizes the clinical diagnosis and patient stratification. It also addresses the recent demand for linking circuits to behavior, and provides a new insight into clinical treatment by investigating the dynamics of neuronal circuits underneath cognitive dimensions of MDD. CCM can serve as a new regime toward personalized medicine, assisting the diagnosis and treatment of MDD.Frontiers in Psychiatry 02/2015; 6:29. DOI:10.3389/fpsyt.2015.00029