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.

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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.

<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 &#x3e;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.