Major depressive disorder (MDD) is often accompanied by severe impairments in working memory (WM). Neuroimaging studies investigating the mechanisms underlying these impairments have produced conflicting results. It remains unclear whether MDD patients show hyper- or hypoactivity in WM-related brain regions and how potential aberrations in WM processing may contribute to the characteristic dysregulation of cognition-emotion interactions implicated in the maintenance of the disorder. In order to shed light on these questions and to overcome limitations of previous studies, we applied a multivoxel pattern classification approach to investigate brain activity in large samples of MDD patients (N = 57) and matched healthy controls (N = 61) during a WM task that incorporated positive, negative, and neutral stimuli. Results showed that patients can be distinguished from healthy controls with good classification accuracy based on functional activation patterns. ROI analyses based on the classification weight maps showed that during WM, patients had higher activity in the left DLPFC and the dorsal ACC. Furthermore, regions of the default-mode network (DMN) were less deactivated in patients. As no performance differences were observed, we conclude that patients required more effort, indexed by more activity in WM-related regions, to successfully perform the task. This increased effort might be related to difficulties in suppressing task-irrelevant information reflected by reduced deactivation of regions within the DMN. Effects were most pronounced for negative and neutral stimuli, thus pointing toward important implications of aberrations in WM processes in cognition-emotion interactions in MDD.
<b><i>Background/Aims/Methods:</i></b> Electroconvulsive therapy (ECT) is still one of the most potent treatments in the acute phase of major depressive disorder (MDD) and particularly applied in patients considered treatment resistant. However, despite the frequent and widespread use of ECT for >70 years, the exact neurobiological mechanisms underlying its efficacy remain unclear. The present review aims to describe differential antidepressant and cognitive effects of ECT as well as effects on markers of neural activity and connectivity, neurochemistry, and inflammation that might underlie the treatment response and remission. <b><i>Results:</i></b> Region- specific changes in brain function and volume along with changes in concentrations of neurotransmitters and neuroinflammatory cytokines might serve as potential biomarkers for ECT outcomes. <b><i>Conclusions:</i></b> However, as current data is not consistent, future longitudinal investigations should combine modalities such as MRI, MR spectroscopy, and peripheral physiological measures to gain a deeper insight into interconnected time- and modality-specific changes in response to ECT.
Background Growing evidence underscores the utility of ketamine as an effective and rapid acting treatment option for major depressive disorder (MDD). However, clinical outcomes vary between patients. Predicting successful response may enable personalized treatment decisions and increase clinical efficacy. Methods We here explored the potential of pregenual anterior cingulate cortex (pgACC) activity to predict antidepressant effects of ketamine in relation to ketamine-induced changes in glutamatergic metabolism. Prior to a single intravenous infusion of ketamine, 24 patients with MDD underwent functional magnetic resonance imaging (fMRI) during an emotional picture-viewing task and magnetic resonance spectroscopy (MRS). Changes in depressive symptoms were evaluated using the Beck Depression Inventory (BDI), measured 24 hours pre- and post-intervention. A subsample of 17 patients underwent a follow-up MRS scan. Results Antidepressant efficacy of ketamine was predicted by pgACC activity during emotional stimulation. In addition, pgACC activity was associated with glutamate increase 24 hours after the ketamine infusion, which was in turn also related to better clinical outcome. Conclusions Our results add to the growing literature implicating a key role of the pgACC in mediating antidepressant effects and highlighting its potential as a multimodal neuroimaging biomarker of early treatment response to ketamine.
Mid-adolescence is a critical time for the development of stress-related disorders and it is associated with significant social vulnerability. However, little is known about normative neural processes accompanying psychosocial stress at this time. Previous research found that emotion regulation strategies critically influence the relationship between stress and the development of psychiatric symptoms during adolescence. Using functional magnetic resonance imaging (fMRI), we examined neural responses to acute stress and analyzed whether the tendency to use adaptive or maladaptive emotion regulation strategies is related to neural and autonomic stress responses. Results show large linear activation increases from low to medium to high stress levels mainly in medial prefrontal, insulae and temporal areas. Caudate and subgenual anterior cingulate cortex, neural areas related to reward and affective valuations, showed linearly decreasing activation. In line with our hypothesis, the current adolescent neural stress profile resembled social rejection and was characterized by pronounced activation in insula, angular and temporal cortices. Moreover, results point to an intriguing role of the anterior temporal gyrus. Stress-related activity in the anterior temporal gyrus was positively related to maladaptive regulation strategies and stress-induced autonomic activity. Maladaptive coping might increase the social threat and reappraisal load of a stressor, relating to higher stress sensitivity of anterior temporal cortices.
Establishing symptom-based predictors of electroconvulsive therapy (ECT) outcome seems promising, however, findings concerning the predictive value of distinct depressive symptoms or subtypes are limited; previous factor-analytic approaches based on the Montgomery–Åsberg Depression Rating Scale (MADRS) remained inconclusive, as proposed factors varied across samples. In this naturalistic study, we refrained from these previous factor-analytic approaches and examined the predictive value of MADRS single items and their change during the course of ECT concerning ECT outcome. We used logistic and linear regression models to analyze MADRS data routinely assessed at three time points in 96 depressed psychiatric inpatients over the course of ECT. Mean age was 53 years (SD 14.79), gender ratio was 58:38 (F:M), baseline MADRS score was M = 30.20 (SD 5.42). MADRS single items were strong predictors of ECT response, remission and overall symptom reduction, especially items 1 (apparent sadness), 2 (reported sadness) and 8 (inability to feel), assessing affective symptoms. Strongest effects were found for regression models including item 2 (reported sadness) with up to 80% correct prediction of ECT outcome. ROC analyses were performed to estimate the optimal cut-point for treatment response. MADRS single items during the course of ECT might pose simple, reliable, time- and cost-effective predictors of ECT outcome. More severe affective symptoms of depression at baseline and a stronger reduction of these affective symptoms during the course of ECT seem to be positively associated with ECT outcome. Precise cut-off values for clinical use were proposed. Generally, these findings underline the benefits of a symptom-based approach in depression research and treatment in addition to depression sum-scores and generalized diagnoses.
Childhood emotional maltreatment (CEM) is a risk factor for the pathogenesis of depressive disorders. However, it is not clear whether CEM is more strongly related to specific symptoms of depression and whether specific traits or cognitive states may mediate the association between CEM and depressive symptoms. In our cross‐sectional study, including 72 patients with a current depressive episode, we investigated if CEM is specifically related to cognitive symptoms of depression. In addition, we evaluated whether CEM also influences the extent of rumination and hopelessness in adult depression. Using multiple regression analyses, we tested if CEM and rumination could predict cognitive symptoms and hopelessness. A structural equation model (SEM) was used to examine if rumination mediates the relationship between CEM and cognitive symptoms. Correlational analyses revealed that CEM was related to cognitive symptoms, rumination, and hopelessness. The regression analyses showed that only rumination was a significant predictor for cognitive symptoms and hopelessness, whereas CEM could not significantly predict the two constructs. SEM revealed that the association between CEM and cognitive symptoms in adult depression was mediated by rumination. Our results thereby suggest that CEM is a risk factor particularly for the development of cognitive symptoms as well as rumination and hopelessness in adult depression. However, the influence on cognitive symptomatology seems to be indirectly regulated by rumination. These findings may contribute to a better understanding of processes that promote depression, as well as provide guidance for more targeted treatment options.
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