Based on multivariate pattern classification, this study demonstrated that depressed patients can be distinguished from healthy controls with good classification accuracy and sensitivity based on functional activation patterns during an emotional WM task. In particular, our prediction results outperform both a majority class and random chance prediction. Thus, our results are in line with a recent meta-analysis showing that MDD patients can be distinguished from healthy controls using different magnetic resonance imaging-based modalities [33]. Moreover, the majority of functionally aberrant regions with discriminative power were located in the DMN, regions involved in cognitive control, and the DLPFC. Highest classification accuracies were achieved for neutral and negative stimuli. However, differential activations between neutral and emotional stimuli did not reveal significant classification results.

In left DLPFC, MDD patients showed higher BOLD responses during task conditions compared to HC. This finding is in accordance with results of a recently published meta-analysis of WM-related brain activity in MDD, which reported hyperactivation exclusively in the left DLPFC [12]. Importantly, even though this meta-analysis included data from 13 different WM experiments and therefore a wide range of stimuli, left DLPFC hyperactivation in MDD remained significant when task performance for predominantly verbal WM demands was matched to that of HC. Since our data do not indicate impaired task performance in MDD, our finding of left DLPFC hyperactivation would rather support the hypothesis that hyperfrontality during WM tasks reflects the need for greater activation to maintain a similar level of performance as HC [6,7,8]. With regard to cognition–emotion interaction, the DLPFC plays a major role in executive control processes, i.e., directing attention away from task-irrelevant emotional distractors during WM [34], which is a key sub-process implicated in effortful voluntary emotion regulation [35]. Greater recruitment of the DLPFC might therefore reflect increased resources to perform the WM task, while inhibiting the allocation of attention toward the processing of emotional stimuli. Interestingly, our data revealed that only left, but not right DLPFC was hyperactive in MDD patients during the WM task. However, the WM task utilized in our study included only verbal stimuli, which are predominantly processed in the left hemisphere [2]. While numerous behavioral studies have shown biases toward negative emotional stimuli in MDD [19, 36] and accordingly reduced activity in left DLFPC for positive stimuli [37], others reported no differences in task performance and functional activity [6, 7]. The MVPC and ROI results presented here also argue against valence-specific effects with regard to left DLPFC activation. Rather, hyperfrontality in MDD might occur to compensate for a lack of deactivation in regions of the DMN [9, 22], in order to keep an effective functional loop between the respective regions and to maintain behavioral performance. Consistently, our data show stronger PCC activation in MDD during rest and diminished deactivation during task conditions. PCC is an important hub in the DMN and characterized by increased activity at rest and deactivations during various emotional–cognitive tasks [9, 38]. It might also play a direct role in regulating the focus of attention by controlling the balance between internally and externally focused thought [39]. In the healthy brain, a failure of appropriate deactivation is associated with inefficient cognitive function [40]. It has been suggested that a failure to suppress PCC activity might reflect the intrusion of internal mentation into task performance [41]. Accordingly, increased PCC activation at rest and decreased deactivation during emotional and cognitive tasks have been reported in MDD [9, 42] and might indicate a generally limited potential for adaptive adjustment of this region in MDD patients [43]. It has to be noted that based on the COPE (WM > fixation) patients showed stronger deactivation in the PCC. This result was reversed when looking at the RPE. This apparent contradiction is based on large resting state PCC activation in patients that leads to relatively stronger deactivation during the task conditions.

MDD patients showed higher BOLD responses than HC during the WM task in dACC extending to the supplementary motor area (SMA). The cognitive subdivision of dACC shows strong connections with DLPFC regions, SMA, and parietal cortex, and has been implicated in response selection and processing of cognitively demanding information. Activity in this region during WM tasks is often described in relation to increased effort, complexity, or attention [4, 5]. Higher activation in MDD patients regardless of valence as observed here might assure intact WM performance. On the other hand, abnormal dACC functioning has also been associated with biased attention to negative stimuli and rumination [44]. Accordingly, our association analysis revealed a significant correlation between rumination and dACC activation.

In right IPL, MDD patients showed higher activation at rest, but diminished BOLD responses during task conditions compared to HC. This region is relevant for visual-spatial processing, usually recruited during n-back tasks and an intermediate node between cognitive control and default-mode networks [45]. Decreased BOLD responses in IPL may be reflective of inadequate communication between these networks, such that larger areas of local cortex need to be recruited in order to shift internal resources from internal (i.e., DMN-related) to external (i.e., cognitive control) functions during WM [46]. While results showed decreased BOLD responses regardless of emotional valence, our data nevertheless suggest that these might be associated with rumination and result in higher reaction times for negative and neutral stimuli, possibly because rumination disrupts allocation of cognitive resources and increases recall of negative life events [47].

A cluster differentiating MDD from HC extended from STG to anterior insula, which is viewed as an interface of cognitive, affective, and homeostatic mechanisms, and is suggested to represent an integral structure for stimulus-driven processing and monitoring of the internal milieu [48]. Previous work by Gu et al. [49] suggested that anterior insula is incorporated in a network integrating cognition and emotion [15]. Within this network, anterior insula represents interoceptive changes of unique relevance to subjective experience, whereas control regions, such as DLPFC, maintain online representations of cognitive demand and stimulus features as well as goal-directed implementation [50], all of which are operations required in cognition–emotion integration. When comparing rest and task within the MDD group, our data show higher activation during rest than during task, which is consistent with previous findings [6, 12, 43] and might indicate increased interoceptive awareness or salience of internal stimuli, while salience of external stimuli is diminished, thereby impairing cognitive processing. This idea is supported by previous findings by Delaveau et al. [51], showing that symptom reduction induced by antidepressant medication increases insula activation during task-related conditions.

Our findings regarding the effect of emotional content on WM performance in HC are in accordance with previous results from several studies that found no impact of emotion on WM performance [24, 25, 52]. In MDD patients, however, we found slower reaction times for negative stimuli, while WM accuracy did not differ between MDD patients and HC. One could hypothesize that reaction times may be more sensitive to small modulations by emotional content than accuracy and therefore emotional content may be more likely to modulate the efficiency with which information is processed as compared with the accuracy with which it is held online. The recruitment of neural networks implicated in emotion processing might result in additional inputs to the WM system [53]. Therefore, it may be that many additional facets of information must be inhibited to allow for processing of only the task-relevant information in the context of the WM task. This increased demand on inhibition may slow the response times in MDD patients, which would be especially true for negative stimuli. The failure of MDD patients to inhibit or discard mood-congruent negative information might increase rumination, and thereby underlie cognitive slowness and attentional deficits [54]. This is also supported by our findings of increased reaction times for negative stimuli in MDD patients and the association between rumination and WM accuracy.

Although the present study overcomes some of the crucial shortcomings of previous reports with respect to sample size and applied statistics, some limitations should be acknowledged. Probably, the most important limitation is that MDD is a very heterogeneous disease and different subtypes might result in different effects on cognitive processes. Our misclassification rate of ~30% may be due in part to this heterogeneity. Further research may build on the current classification results to investigate disease subtypes and relevance to treatment–response prediction. Furthermore, some of the MDD patients (N = 22) took different types of antidepressant medication during the study, which might have posed an additional source of variance. Although the applied MVPC approach inherently takes into account confounding factors and noise in the data, it has to be noted that this study did not focus on the effects of antidepressant medication. We performed control analyses (data not shown) between medicated and unmedicated patients that did not reveal significant group differences, but medication types were considered too diverse to draw definite conclusions from these analyses. Upcoming studies should investigate the effects of specific antidepressants on brain activations during WM. From a methodological point of view, it should be noted that the classification model was evaluated on a single dataset only. Therefore dataset-specific effects might have influenced the results. The validation of the current findings in a different sample is the next step, which is considered as future work.

To conclude, by applying MVPC, the present study demonstrates that functional activation patterns during an emotional WM task can be used to distinguish MDD patients from controls with good accuracy and sensitivity. While adequate WM performance in MDD is associated with frontal hyperactivation, patients show a lack of deactivation in regions of the DMN. This effect is most pronounced for negative and neutral stimuli and associated with rumination, suggesting an important role of aberrations in WM processing for cognition–emotion interactions in MDD.