Weak reward source memory in depression reflects blunted activation of VTA/SN and parahippocampus

Uncovering the Neural Correlates of Anhedonia Subtypes in Major Depressive Disorder: Implications for Intervention Strategies

Major depressive disorder (MDD) represents a serious public health concern, negatively affecting individuals' quality of life and making a substantial contribution to the global burden of disease. Anhedonia is a core symptom of MDD and is associated with poor treatment outcomes. Variability in anhedonia components within MDD has been observed, suggesting heterogeneity in psychopathology across subgroups. However, little is known about anhedonia subgroups in MDD and their underlying neural correlates across subgroups. To address this question, we employed a hierarchical cluster analysis based on Temporal Experience of Pleasure Scale subscales in 60 first-episode, drug-naive MDD patients and 32 healthy controls. Then we conducted a connectome-wide association study and whole-brain voxel-wise functional analyses for identified subgroups. There were three main findings: (1) three subgroups with different anhedonia profiles were identified using a data mining approach; (2) several parts of the reward network (especially pallidum and dorsal striatum) were associated with anticipatory and consummatory pleasure; (3) different patterns of within- and between-network connectivity contributed to the disparities of anhedonia profiles across three MDD subgroups. Here, we show that anhedonia in MDD is not uniform and can be categorized into distinct subgroups, and our research contributes to the understanding of neural underpinnings, offering potential treatment directions. This work emphasizes the need for tailored approaches in the complex landscape of MDD. The identification of homogeneous, stable, and neurobiologically valid MDD subtypes could significantly enhance our comprehension and management of this multifaceted condition.

Neurofeedback and Affect Regulation Circuitry in Depressed and Healthy Adolescents

Neurodevelopmental psychopathology seeks to understand higher-order emotion regulation circuitry to develop new therapies for adolescents with depression. Depressed (N = 34) and healthy youth (N = 19) completed neurofeedback (NF) training and exhibited increased bilateral amygdala and hippocampus activity in the region of interest (ROI) analyses by recalling positive autobiographical memories. We tested factors supportive of the engagement of emotion regulation's neural areas during NF (i.e., parental support, medication, and gender effects upon anterior cingulate cortex (ACC) engagement). Whole-brain analyses yielded effects of NF vs. control condition and effects of diagnosis. Youth showed higher amygdala and hippocampus (AMYHIPPO) activity during the NF vs. control condition, particularly in the left hippocampus. ACC's activity was also higher during NF vs. control. Higher average ACC activity was linked to better parental support, absent depression, female gender, and absent medication. Control youth showed higher average AMYHIPPO and ACC activity throughout the task and a faster decline in activity vs. depressed youths. Whole-brain level analyses showed higher activity in the frontotemporal network during the NF vs. control conditions, suggesting targeting their connectivity in future neurofeedback trials.

Degeneracy and disordered brain networks in psychiatric patients using multivariate structural covariance analyzes

Introduction

In this study, we applied multivariate methods to identify brain regions that have a critical role in shaping the connectivity patterns of networks associated with major psychiatric diagnoses, including schizophrenia (SCH), major depressive disorder (MDD) and bipolar disorder (BD) and healthy controls (HC). We used T1w images from 164 subjects: Schizophrenia (n = 17), bipolar disorder (n = 25), major depressive disorder (n = 68) and a healthy control group (n = 54).

Methods

We extracted regions of interest (ROIs) using a method based on the SHOOT algorithm of the SPM12 toolbox. We then performed multivariate structural covariance between the groups. For the regions identified as significant in t term of their covariance value, we calculated their eigencentrality as a measure of the influence of brain regions within the network. We applied a significance threshold of p = 0.001. Finally, we performed a cluster analysis to determine groups of regions that had similar eigencentrality profiles in different pairwise comparison networks in the observed groups.

Results

As a result, we obtained 4 clusters with different brain regions that were diagnosis-specific. Cluster 1 showed the strongest discriminative values between SCH and HC and SCH and BD. Cluster 2 had the strongest discriminative value for the MDD patients, cluster 3 - for the BD patients. Cluster 4 seemed to contribute almost equally to the discrimination between the four groups.

Discussion

Our results suggest that we can use the multivariate structural covariance method to identify specific regions that have higher predictive value for specific psychiatric diagnoses. In our research, we have identified brain signatures that suggest that degeneracy shapes brain networks in different ways both within and across major psychiatric disorders.

Abnormal evidence accumulation underlies the positive memory deficit in depression

Healthy adults show better memory for low-arousal positive versus negative stimuli, but depression compromises this positive memory advantage. Existing studies are limited by small samples or analyses that provide limited insight into underlying mechanisms. Our study addresses these concerns by using a multistaged analysis, including diffusion modeling, to identify precise psychological processes underlying the positive memory advantage and its disruption by depression in a large sample. A total of 1,358 participants completed the BDI-II (Beck et al., 1996) and an emotional memory task. At encoding, participants judged whether positive and negative words were positive or self-descriptive. After a free recall test, participants viewed an equal mix of studied and unstudied words and judged whether each was "old" or "new"; if judged "old," they indicated whether the study source was a valence or self-reference judgment. We replicate the positive memory advantage and its decrease in depression in recall, recognition, and source accuracy. The hierarchical drift diffusion model (HDDM; Wiecki et al., 2013) revealed that higher BDI-II scores are associated with more efficient evidence accumulation for negative words in the recognition and source memory tasks. By contrast, evidence accumulation for positive words is unaffected by BDI-II during the recognition task but becomes less efficient with increased BDI-II during the source memory task. In conclusion, in a well-controlled design with a large sample, we find that depression reduces the positive memory advantage. HDDM analyses suggest that this reflects differential effects of depression on the speed of evidence accumulation during the retrieval of positive versus negative memories. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Sluggish retrieval of positive memories in depressed adults

Although depression is associated with poor memory for positive material, the underlying mechanisms remain unclear. We used the Hierarchical Drift Diffusion Model (HDDM) to determine whether slow evidence accumulation at retrieval contributes to depressed individuals' difficulty remembering positive events. Participants completed the Beck Depression Inventory-II and were stratified into High BDI (HBDI; BDI-II > 20, n = 49) and Low BDI (LBDI; BDI-II < 6, n = 46) groups. Next, participants completed an oddball task in which neutral, negative, and positive pictures served as rare targets. One day later, recognition memory was tested by presenting the encoded ("old") pictures along with closely matched ("new") lures. Recognition accuracy was analyzed with a generalized linear model, and choice and response time data were analyzed with the HDDM. Recognition accuracy for old positive pictures was lower in HBDI versus LBDI participants, and the HDDM highlighted slow evidence accumulation during positive memory retrieval in the HBDI group. Impaired memory for positive material in depressed adults was related to slow evidence accumulation at retrieval. Because oddballs should elicit prediction errors that normally strengthen memory formation, these retrieval findings may reflect weak positive prediction errors, at encoding, in depressed adults.

The effects of perceived stress and anhedonic depression on mnemonic similarity task performance

Previous research has demonstrated hippocampal alterations in individuals experiencing elevated stress. The Mnemonic Similarity Task (MST) is a hippocampal-dependent task sensitive to age-related hippocampal decline, but it is unknown how performance on this task is related to one's experience of daily stress. We conducted separate discovery and replication analyses in 510 participants who completed the MST across four different Mechanical Turk studies. We hypothesized that higher scores on the Perceived Stress Scale would be associated with poorer discrimination of "lure" items from previously seen targets - a behavioral index of pattern separation - but not with recognition memory. The zero-order relationship between perceived stress and lure discrimination was not significant in the discovery or replication sample. Exploratory analyses involving anhedonic depression symptoms (from the Mood and Anxiety Symptoms Questionnaire) revealed a robust perceived stress*anhedonic depression interaction in the discovery sample that was confirmed in the replication sample. In both samples, individuals with low but not high anhedonic depression symptoms showed an inverse association between perceived stress and lure discrimination ability. Contrary to hypotheses, a similar interaction was observed for recognition memory. The novel association between perceived stress and behavioral pattern separation suggests a candidate behavioral process associated with stress-related hippocampal deficits. The specificity of this effect for individuals with low anhedonic depression symptoms - and the lack of behavioral specificity - highlight the need for additional research to unpack the clinical and neurobiological significance of these findings.

Win, lose, or draw: Examining salience, reward memory, and depression with the reward positivity

The reward positivity (RewP) is a putative biomarker of depression. Careful control of stimulus properties and manipulation of both stimulus valence and salience could facilitate interpretation of the RewP. RewP interpretation could further be improved by investigating functional outcomes of a blunted RewP in depression, such as reduced memory for rewarding outcomes. This study sought to advance RewP interpretation first by advancing task design through use of neutral (i.e., draw) control trials and counterbalanced feedback stimuli. Second, we examined the RewP's association with memory and the impact of depression. Undergraduates completed self-report measures of depression and anhedonia prior to a modified doors task in which words were displayed in colored fonts that indicated win, loss, or draw feedback. Memory of the feedback associated with each word (i.e., source memory) was tested. Results showed that RewP response to wins was more positive than to losses, which was more positive than to draws. The RewP was not associated with depression or anhedonia. The low depression group showed a source memory advantage for win words, but the high depression group did not. Source memory showed small relations to the RewP, but these did not survive Bonferroni correction. Results suggest the RewP is sensitive to salience and highlight challenges in detecting an association between the RewP and depression in modified doors tasks. Findings indicate that depression is related to dysfunctional source memory for reward but not loss and that future research should probe the possible associations between the RewP and memory in depression.

Males are more sensitive to reward and less sensitive to loss than females among people with internet gaming disorder: fMRI evidence from a card-guessing task

BACKGROUND

Many studies have found an interesting issue in the Internet gaming disorder (IGD): males are always observed to be the majority. However, there are little research to exploring the differences in the neural mechanisms between males and females in decision-making process among people with IGD. Therefore, explore the reward/loss processing between different gender with IGD could help in understanding the underlying neural mechanism of IGD.

METHODS

Data from functional magnetic resonance imaging (fMRI) were collected from 111 subjects (IGD: 29 males, 25 females; recreational internet game user (RGU): 36 males, 21 females) while they were performing a card-guessing task. We collected and compared their brain features when facing the win and loss conditions in different groups.

RESULTS

For winning conditions, IGD group showed hypoactivity in the lingual gyrus than RGU group, male players showed hyperactivity in the left caudate nucleus, bilateral cingulate gyrus, right middle frontal gyrus (MFG), right precuneus and inferior parietal lobule relative to the females. And significant sex-by-group interactions results showed higher brain activities in the thalamus, parahippocampal gyrus and lower brain activities in Inferior frontal gyrus (IFG) were observed in males with IGD than females. For losing conditions, IGD group showed hypoactivity in the left lingual gyrus, parahippocampal gyrus and right anterior cingulate cortex (ACC) compared to the RGU group, male players showed hyperactive left caudate nucleus and hypoactive right middle occipital gyrus relative to females. And significant sex-by-group interactions results showed that compared to females with IGD, males with IGD showed decreased brain activities in the IFG and lingual gyrus.

CONCLUSIONS

First, there appeared to be no difference in reward processing between the IGD and RGU group, but IGD showed less sensitivity to loss. Secondly, male players showed more sensitivity to rewards and less sensitivity to losses. Last but not least, males and females showed opposite activation patterns in IGD degree and rewards/losses processing. And male IGD subjects are more sensitive to reward and less sensitive to loss than females, which might be the reason for the gender different rates on IGD.

Dissecting the impact of depression on decision-making

BACKGROUND

Cognitive deficits in depressed adults may reflect impaired decision-making. To investigate this possibility, we analyzed data from unmedicated adults with Major Depressive Disorder (MDD) and healthy controls as they performed a probabilistic reward task. The Hierarchical Drift Diffusion Model (HDDM) was used to quantify decision-making mechanisms recruited by the task, to determine if any such mechanism was disrupted by depression.

METHODS

Data came from two samples (Study 1: 258 MDD, 36 controls; Study 2: 23 MDD, 25 controls). On each trial, participants indicated which of two similar stimuli was presented; correct identifications were rewarded. Quantile-probability plots and the HDDM quantified the impact of MDD on response times (RT), speed of evidence accumulation (drift rate), and the width of decision thresholds, among other parameters.

RESULTS

RTs were more positively skewed in depressed v. healthy adults, and the HDDM revealed that drift rates were reduced-and decision thresholds were wider-in the MDD groups. This pattern suggests that depressed adults accumulated the evidence needed to make decisions more slowly than controls did.

CONCLUSIONS

Depressed adults responded slower than controls in both studies, and poorer performance led the MDD group to receive fewer rewards than controls in Study 1. These results did not reflect a sensorimotor deficit but were instead due to sluggish evidence accumulation. Thus, slowed decision-making-not slowed perception or response execution-caused the performance deficit in MDD. If these results generalize to other tasks, they may help explain the broad cognitive deficits seen in depression.

Neurocognitive predictors of self-reported reward responsivity and approach motivation in depression: A data-driven approach

BACKGROUND

Individual differences in reward-related processes, such as reward responsivity and approach motivation, appear to play a role in the nature and course of depression. Prior work suggests that cognitive biases for valenced information may contribute to these reward processes. Yet there is little work examining how biased attention, processing, and memory for positively and negatively valenced information may be associated with reward-related processes in samples with depression symptoms.

METHODS

We used a data-driven, machine learning (elastic net) approach to identify the best predictors of self-reported reward-related processes using multiple tasks of attention, processing, and memory for valenced information measured across behavioral, eye tracking, psychophysiological, and computational modeling approaches (n = 202). Participants were adults (ages 18-35) who ranged in depression symptom severity from mild to severe.

RESULTS

Models predicted between 5.0-12.2% and 9.7-28.0% of held-out test sample variance in approach motivation and reward responsivity, respectively. Low self-referential processing of positively valenced information was the most robust, albeit modest, predictor of low approach motivation and reward responsivity.

CONCLUSIONS

Self-referential processing of positive information is the strongest predictor of reward responsivity and approach motivation in a sample ranging from mild to severe depression symptom severity. Experiments are now needed to clarify the causal relationship between self-referential processing of positively valenced information and reward processes in depression.

The anhedonia is differently modulated by structural covariance network of NAc in bipolar disorder and major depressive disorder

During depressive episode, bipolar disorder (BD) patients share indistinguishable depression symptoms with major depressive disorder (MDD).However, whether neural correlates underlying the anhedonia, a core feature of depression, is different between BD and MDD remains unknown. To explore neural correlates underlying the anhedonia in BD and MDD, structural T1-weighted images from 36 depressed BD patients, 40 depressed MDD patients matched for depression severity and 34 health controls (HCs) were scanned. Considering the vital role of nucleus accumbens (NAc) in the anhedonia, we constructed the structural covariance network of NAc for each subject. Then, we explored altered structural covariance network of NAc and its interaction with the anhedonia severity in BD and MDD patients. As a result, BD and MDD patients shared decreased structural covariance of NAc connected to prefrontal gyrus, bilateral striatum extending to bilateral anterior insula. Apart from these regions, BD patients presented specifically increased structural covariance of NAc connected to left hippocampus extending to thalamus. The interaction between structural covariance network of NAc and the anhedonia severity in MDD was mainly associated anterior insula (AIC), amygdala, anterior cingulate cortex (ACC)and caudate while that in BD was mainly located in striatum and prefrontal cortex. Our results found that BD and MDD patients presented commonly and distinctly altered structural covariance network of NAc. What is more, the neural correlates underlying the anhedonia in BD and MDD might be different.

Depressive symptoms bias the prediction-error enhancement of memory towards negative events in reinforcement learning

RATIONALE

Depression is a disorder characterized by sustained negative affect and blunted positive affect, suggesting potential abnormalities in reward learning and its interaction with episodic memory.

OBJECTIVES

This study investigated how reward prediction errors experienced during learning modulate memory for rewarding events in individuals with depressive and non-depressive symptoms.

METHODS

Across three experiments, participants learned the average values of two scene categories in two learning contexts. Each learning context had either high or low outcome variance, allowing us to test the effects of small and large prediction errors on learning and memory. Participants were later tested for their memory of trial-unique scenes that appeared alongside outcomes. We compared learning and memory performance of individuals with self-reported depressive symptoms (N = 101) to those without (N = 184).

RESULTS

Although there were no overall differences in reward learning between the depressive and non-depressive group, depression severity within the depressive group predicted greater error in estimating the values of the scene categories. Similarly, there were no overall differences in memory performance. However, in depressive participants, negative prediction errors enhanced episodic memory more so than did positive prediction errors, and vice versa for non-depressive participants who showed a larger effect of positive prediction errors on memory. These results reflected differences in memory both within group and across groups.

CONCLUSIONS

Individuals with self-reported depressive symptoms showed relatively intact reinforcement learning, but demonstrated a bias for encoding events that accompanied surprising negative outcomes versus surprising positive ones. We discuss a potential neural mechanism supporting these effects, which may underlie or contribute to the excessive negative affect observed in depression.

Impaired reward-related learning signals in remitted unmedicated patients with recurrent depression

One of the core symptoms of major depressive disorder is anhedonia, an inability to experience pleasure. In patients with major depressive disorder, a dysfunctional reward-system may exist, with blunted temporal difference reward-related learning signals in the ventral striatum and increased temporal difference-related (dopaminergic) activation in the ventral tegmental area. Anhedonia often remains as residual symptom during remission; however, it remains largely unknown whether the abovementioned reward systems are still dysfunctional when patients are in remission. We used a Pavlovian classical conditioning functional MRI task to explore the relationship between anhedonia and the temporal difference-related response of the ventral tegmental area and ventral striatum in medication-free remitted recurrent depression patients (n = 36) versus healthy control subjects (n = 27). Computational modelling was used to obtain the expected temporal difference errors during this task. Patients, compared to healthy controls, showed significantly increased temporal difference reward learning activation in the ventral tegmental area (PFWE,SVC = 0.028). No differences were observed between groups for ventral striatum activity. A group × anhedonia interaction [t(57) = -2.29, P = 0.026] indicated that in patients, higher anhedonia was associated with lower temporal difference activation in the ventral tegmental area, while in healthy controls higher anhedonia was associated with higher ventral tegmental area activation. These findings suggest impaired reward-related learning signals in the ventral tegmental area during remission in patients with depression. This merits further investigation to identify impaired reward-related learning as an endophenotype for recurrent depression. Moreover, the inverse association between reinforcement learning and anhedonia in patients implies an additional disturbing influence of anhedonia on reward-related learning or vice versa, suggesting that the level of anhedonia should be considered in behavioural treatments.

Separate Memory-Enhancing Effects of Reward and Strategic Encoding

Memory encoding for important information can be enhanced both by reward anticipation and by intentional strategies. These effects are hypothesized to depend on distinct neural mechanisms, yet prior work has provided only limited evidence for their separability. We aimed to determine whether reward-driven and strategic mechanisms for prioritizing important information are separable, even if they may also interact. We examined the joint operation of both mechanisms using fMRI measures of brain activity. Participants learned abstract visual images in a value-directed recognition paradigm. On each trial, two novel images were presented simultaneously in different screen quadrants, one arbitrarily designated as high point value and one as low value. Immediately after each block of 16 study trials, the corresponding point rewards could be obtained in a test of item recognition and spatial location memory. During encoding trials leading to successful subsequent memory, especially of high-value images, increased activity was observed in dorsal frontoparietal and lateral occipitotemporal cortex. Furthermore, activity in a network associated with reward was higher during encoding when any image, of high or low value, was subsequently remembered. Functional connectivity between right medial temporal lobe and right ventral tegmental area, measured via psychophysiological interaction, was also greater during successful encoding regardless of value. Strategic control of memory, as indexed by successful prioritization of the high-value image, affected activity in dorsal posterior parietal cortex as well as connectivity between this area and right lateral temporal cortex. These results demonstrate that memory can be strengthened by separate neurocognitive mechanisms for strategic control versus reward-based enhancement of processing.

Functional connectomics of affective and psychotic pathology

Historically, most research on the biological origins of psychiatric illness has focused on individual diagnostic categories, studied in isolation. Mounting evidence indicates that nominally distinct psychiatric diagnoses are not separated by clear neurobiological boundaries. Here, we derive functional connectomic signatures in over 1,000 individuals, including patients presenting with different categories of impairment (psychosis), clinical diagnoses, and severity of illness as reflected in treatment seeking. Our analyses reveal features of connectome functioning that are commonly disrupted across distinct forms of pathology, scaling with clinical severity. Conversely, other aspects of network connectivity were preferentially disrupted in patients with psychotic illness. These data have important implications for the establishment of functional connectome fingerprints of severe mental disease.

Converging evidence indicates that groups of patients with nominally distinct psychiatric diagnoses are not separated by sharp or discontinuous neurobiological boundaries. In healthy populations, individual differences in behavior are reflected in variability across the collective set of functional brain connections (functional connectome). These data suggest that the spectra of transdiagnostic symptom profiles observed in psychiatric patients may map onto detectable patterns of network function. To examine the manner through which neurobiological variation might underlie clinical presentation, we obtained fMRI data from over 1,000 individuals, including 210 diagnosed with a primary psychotic disorder or affective psychosis (bipolar disorder with psychosis and schizophrenia or schizoaffective disorder), 192 presenting with a primary affective disorder without psychosis (unipolar depression, bipolar disorder without psychosis), and 608 demographically matched healthy comparison participants recruited through a large-scale study of brain imaging and genetics. Here, we examine variation in functional connectomes across psychiatric diagnoses, finding striking evidence for disease connectomic “fingerprints” that are commonly disrupted across distinct forms of pathology and appear to scale as a function of illness severity. The presence of affective and psychotic illnesses was associated with graded disruptions in frontoparietal network connectivity (encompassing aspects of dorsolateral prefrontal, dorsomedial prefrontal, lateral parietal, and posterior temporal cortices). Conversely, other properties of network connectivity, including default network integrity, were preferentially disrupted in patients with psychotic illness, but not patients without psychotic symptoms. This work allows us to establish key biological and clinical features of the functional connectomes of severe mental disease.

Reward Processing in Depression: A Conceptual and Meta-Analytic Review Across fMRI and EEG Studies

OBJECTIVE

A role for aberrant reward processing in the pathogenesis of depression has long been proposed. However, no review has yet examined its role in depression by integrating conceptual and quantitative findings across functional MRI (fMRI) and EEG methodologies. The authors quantified these effects, with an emphasis on development.

METHOD

A total of 38 fMRI and 12 EEG studies were entered into fMRI and EEG meta-analyses. fMRI studies primarily examined reward anticipation and reward feedback. These were analyzed using the activation likelihood estimation method. EEG studies involved mainly the feedback-related negativity (FRN) event-related potential, and these studies were analyzed using random-effects meta-analysis of the association between FRN and depression.

RESULTS

Analysis of fMRI studies revealed significantly reduced striatal activation in depressed compared with healthy individuals during reward feedback. When region-of-interest analyses were included, reduced activation was also observed in reward anticipation, an effect that was stronger in individuals under age 18. FRN was also significantly reduced in depression, with pronounced effects in individuals under age 18. In longitudinal studies, reduced striatal activation in fMRI and blunted FRN in EEG were found to precede the onset of depression in adolescents.

CONCLUSIONS

Taken together, the findings show consistent neural aberrations during reward processing in depression, namely, reduced striatal signal during feedback and blunted FRN. These aberrations may underlie the pathogenesis of depression and have important implications for development of new treatments.

Depression Detection Using Relative EEG Power Induced by Emotionally Positive Images and a Conformal Kernel Support Vector Machine

Electroencephalography (EEG) can assist with the detection of major depressive disorder (MDD). However, the ability to distinguish adults with MDD from healthy individuals using resting-state EEG features has reached a bottleneck. To address this limitation, we collected EEG data as participants engaged with positive pictures from the International Affective Picture System. Because MDD is associated with blunted positive emotions, we reasoned that this approach would yield highly dissimilar EEG features in healthy versus depressed adults. We extracted three types of relative EEG power features from different frequency bands (delta, theta, alpha, beta, and gamma) during the emotion task and resting state. We also applied a novel classifier, called a conformal kernel support vector machine (CK-SVM), to try to improve the generalization performance of conventional SVMs. We then compared CK-SVM performance with three machine learning classifiers: linear discriminant analysis (LDA), conventional SVM, and quadratic discriminant analysis. The results from the initial analyses using the LDA classifier on 55 participants (24 MDD, 31 healthy controls) showed that the participant-independent classification accuracy obtained by leave-one-participant-out cross-validation (LOPO-CV) was higher for the EEG recorded during the positive emotion induction versus the resting state for all types of relative EEG power. Furthermore, the CK-SVM classifier achieved higher LOPO-CV accuracy than the other classifiers. The best accuracy (83.64%; sensitivity = 87.50%, specificity = 80.65%) was achieved by the CK-SVM, using seven relative power features extracted from seven electrodes. Overall, combining positive emotion induction with the CK-SVM classifier proved useful for detecting MDD on the basis of EEG signals. In the future, this approach might be used to develop a brain–computer interface system to assist with the detection of MDD in the clinic. Importantly, such a system could be implemented with a low-density electrode montage (seven electrodes), highlighting its practical utility.

Depression is associated with dimensional and categorical effects on white matter pathways

BACKGROUND

Diffusion tensor imaging (DTI) studies report reduced fractional anisotropy (FA) in major depressive disorder (MDD). However, whether FA covaries with key depressive symptoms, such as anhedonia, is unclear.

METHODS

Magnetic resonance imaging data were acquired from 38 unmedicated adults with MDD and 52 healthy controls. DTI metrics were extracted from regions of interest that have consistently shown reduced FA in MDD. Analyses focused first on identifying group differences, and then determining whether reduced FA in depressed adults was related to individual differences in anhedonia and depressive severity. To establish specificity to depression, these analyses controlled for symptoms of anxiety.

RESULTS

Relative to controls, depressed adults showed reduced FA in the genu of the corpus callosum, the anterior limb of the internal capsule (ALIC), the cingulum bundle near the anterior cingulate cortex, and the uncinate fasciculus (UF). In the depressed group, anhedonia negatively correlated with FA in the genu, cingulum, and UF, but positively correlated with radial diffusivity (RD)-a metric previously linked to demyelination-in the genu and ALIC. Depressive severity positively correlated with RD in the ALIC. These relationships remained significant after accounting for anxiety.

CONCLUSION

Anhedonia was positively correlated with reduced FA and increased RD in white matter pathways that connect regions critical for value coding, representing stimulus-reward associations, and guiding value-based action selection. Thus, a cardinal symptom of MDD-anhedonia-was lawfully related to abnormalities in reward network connectivity.

Mechanisms of Memory Disruption in Depression

Depressed individuals typically show poor memory for positive events, potentiated memory for negative events, and impaired recollection. These phenomena are clinically important but poorly understood. Compelling links between stress and depression suggest promising candidate mechanisms. Stress can suppress hippocampal neurogenesis, inhibit dopamine neurons, and sensitize the amygdala. We argue that these phenomena may impair pattern separation, disrupt the encoding of positive experiences, and bias retrieval toward negative events, respectively, thus recapitulating core aspects of memory disruption in depression. Encouragingly, optogenetic reactivation of cells engaged during the encoding of positive memories rapidly reduces depressive behavior in preclinical models. Thus, many memory deficits in depression appear to be downstream consequences of chronic stress, and addressing memory disruption can have therapeutic value.

An ERP study of multidimensional source retrieval in depression

We collected event-related potentials (ERPs) from 24 unmedicated adults with Major Depressive Disorder (MDD) and 24 controls during source memory retrieval. Words were encoded on the left or right during animacy and mobility judgments. Mobility judgments were slower than animacy judgments, suggesting deeper encoding. Participants then recalled the encoding judgment (Question cue) and position (Side cue) for each word. Depressed adults, but not controls, showed better accuracy for words from the mobility task presented under the Question vs. Side Cue. Furthermore, depressed adults showed larger left parietal ERPs to words from the mobility task presented under the Question vs. the Side Cue from 400 to 800 ms and 800-1400 ms. This ERP effect was negatively correlated with sleep quality. Thus, deep encoding followed by retrieval of the encoding judgment supported memory in MDD and augmented left parietal ERPs that have been linked to recollection and that appear sensitive to sleep disturbance.

Altered reward learning and hippocampal connectivity following psychosocial stress

Acute stress has a profound influence on learning, as has been demonstrated in verbal learning or fear conditioning. However, its effect on appetitive conditioning is still unclear. Fear conditioning research suggests the possibility of overgeneralization of conditioning to the CS- under acute stress due to its effect on prefrontal and hippocampal processing. In this study, participants (N = 56 males) were subjected to the Trier Social Stress Test or a placebo version. After that, all participants underwent an appetitive conditioning paradigm in the fMRI, in which one neutral cue (CS+) was repeatedly paired with reward, while another (CS-) was not. Importantly, the stress-group revealed overgeneralization of conditioning to the CS- on the behavioral level. On the neural level, stressed participants showed increased connectivity between the hippocampus and amygdala, vACC, and OFC, which maintain specificity of conditioning and also showed reduced differential activation. The results indicate overgeneralization of appetitive conditioning promoted by maladaptive balancing of pattern separation and pattern completion in the hippocampus under acute stress and are discussed with respect to clinical implications.

Neural mechanisms underlying the reward-related enhancement of motivation when remembering episodic memories with high difficulty

The motivation to receive rewards enhances episodic memories, and the motivation is modulated by task difficulty. In episodic retrieval, however, functional neuroimaging evidence regarding the motivation that mediates interactions between reward and task difficulty is scarce. The present fMRI study investigated this issue. During encoding performed without fMRI, participants encoded Japanese words using either deep or shallow strategies, which led to variation in difficulty level during subsequent retrieval. During retrieval with fMRI, participants recognized the target words in either high or low monetary reward conditions. In the behavioral results, a reward-related enhancement of memory was found only when the memory retrieval was difficult, and the rewarding effect on subjective motivation was greater in the retrieval of memories with high difficulty than those with low difficulty. The fMRI data showed that reward-related increases in the activation of the substantia nigra/ventral tegmental area (SN/VTA), medial temporal lobe (MTL), dorsomedial prefrontal cortex (dmPFC), and dorsolateral prefrontal cortex (dlPFC) were greater during the retrieval of memories with high difficulty than those with low difficulty. Furthermore, reward-related enhancement of functional connectivity between the SN/VTA and MTL and between the SN/VTA and dmPFC during the retrieval of memories with high difficulty was significantly correlated with reward-related increases of retrieval accuracy and subjective motivation. The reward-related enhancement of episodic retrieval and retrieval-related motivation could be most effective when the level of retrieval difficulty is optimized. Such reward-related enhancement of memory and motivation could be modulated by a network including the reward-related SN/VTA, motivation-related dmPFC, and memory-related MTL. Hum Brain Mapp 38:3428-3443, 2017. © 2017 Wiley Periodicals, Inc.

Increased Loss Aversion in Unmedicated Patients with Obsessive-Compulsive Disorder

INTRODUCTION

Obsessive-compulsive disorder (OCD) patients show abnormalities in decision-making and, clinically, appear to show heightened sensitivity to potential negative outcomes. Despite the importance of these cognitive processes in OCD, few studies have examined the disorder within an economic decision-making framework. Here, we investigated loss aversion, a key construct in the prospect theory that describes the tendency for individuals to be more sensitive to potential losses than gains when making decisions.

METHODS

Across two study sites, groups of unmedicated OCD patients (n = 14), medicated OCD patients (n = 29), and healthy controls (n = 34) accepted or rejected a series of 50/50 gambles containing varying loss/gain values. Loss aversion was calculated as the ratio of the likelihood of rejecting a gamble with increasing potential losses to the likelihood of accepting a gamble with increasing potential gains. Decision times to accept or reject were also examined and correlated with loss aversion.

RESULTS

Unmedicated OCD patients exhibited significantly more loss aversion compared to medicated OCD or controls, an effect that was replicated across both sites and remained significant even after controlling for OCD symptom severity, trait anxiety, and sex. Post hoc analyses further indicated that unmedicated patients' increased likelihood to reject a gamble as its loss value increased could not be explained solely by greater risk aversion among patients. Unmedicated patients were also slower to accept than reject gambles, effects that were not found in the other two groups. Loss aversion was correlated with decision times in unmedicated patients but not in the other two groups.

DISCUSSION

These data identify abnormalities of decision-making in a subgroup of OCD patients not taking psychotropic medication. The findings help elucidate the cognitive mechanisms of the disorder and suggest that future treatments could aim to target abnormalities of loss/gain processing during decision-making in this population.

Reactivation of Reward-Related Patterns from Single Past Episodes Supports Memory-Based Decision Making

Rewarding experiences exert a strong influence on later decision making. While decades of neuroscience research have shown how reinforcement gradually shapes preferences, decisions are often influenced by single past experiences. Surprisingly, relatively little is known about the influence of single learning episodes. Although recent work has proposed a role for episodes in decision making, it is largely unknown whether and how episodic experiences contribute to value-based decision making and how the values of single episodes are represented in the brain. In multiple behavioral experiments and an fMRI experiment, we tested whether and how rewarding episodes could support later decision making. Participants experienced episodes of high reward or low reward in conjunction with incidental, trial-unique neutral pictures. In a surprise test phase, we found that participants could indeed remember the associated level of reward, as evidenced by accurate source memory for value and preferences to re-engage with rewarded objects. Further, in a separate experiment, we found that high-reward objects shown as primes before a gambling task increased financial risk taking. Neurally, re-exposure to objects in the test phase led to significant reactivation of reward-related patterns. Importantly, individual variability in the strength of reactivation predicted value memory performance. Our results provide a novel demonstration that affect-related neural patterns are reactivated during later experience. Reactivation of value information represents a mechanism by which memory can guide decision making.

Transcutaneous Vagus Nerve Stimulation Modulates Default Mode Network in Major Depressive Disorder

BACKGROUND

Depression is the most common form of mental disorder in community and health care settings and current treatments are far from satisfactory. Vagus nerve stimulation (VNS) is a Food and Drug Administration approved somatic treatment for treatment-resistant depression. However, the involvement of surgery has limited VNS only to patients who have failed to respond to multiple treatment options. Transcutaneous VNS (tVNS) is a relatively new, noninvasive VNS method based on the rationale that there is afferent/efferent vagus nerve distribution on the surface of the ear. The safe and low-cost characteristics of tVNS have the potential to significantly expand the clinical application of VNS.

METHODS

In this study, we investigated how tVNS can modulate the default mode network (DMN) functional connectivity (FC) in mild or moderate major depressive disorder (MDD) patients. Forty-nine MDD patients were recruited and received tVNS or sham tVNS (stVNS) treatments.

RESULTS

Thirty-four patients completed the study and were included in data analysis. After 1 month of tVNS treatment, the 24-item Hamilton Depression Rating Scale score reduced significantly in the tVNS group as compared with the stVNS group. The FC between the DMN and anterior insula and parahippocampus decreased; the FC between the DMN and precuneus and orbital prefrontal cortex increased compared with stVNS. All these FC increases are also associated with 24-item Hamilton Depression Rating Scale reduction.

CONCLUSIONS

tVNS can significantly modulate the DMN FC of MDD patients; our results provide insights to elucidate the brain mechanism of tVNS treatment for MDD patients.

The neuroscience of positive memory deficits in depression

Adults with unipolar depression typically show poor episodic memory for positive material, but the neuroscientific mechanisms responsible for this deficit have not been characterized. I suggest a simple hypothesis: weak memory for positive material in depression reflects disrupted communication between the mesolimbic dopamine pathway and medial temporal lobe (MTL) memory systems during encoding. This proposal draws on basic research showing that dopamine release in the hippocampus is critical for the transition from early- to late-phase long-term potentiation (LTP) that marks the conversion of labile, short-term memories into stable, long-term memories. Neuroimaging and pharmacological data from healthy humans paint a similar picture: activation of the mesolimbic reward circuit enhances encoding and boosts retention. Unipolar depression is characterized by anhedonia-loss of pleasure-and reward circuit dysfunction, which is believed to reflect negative effects of stress on the mesolimbic dopamine pathway. Thus, I propose that the MTL is deprived of strengthening reward signals in depressed adults and memory for positive events suffers accordingly. Although other mechanisms are important, this hypothesis holds promise as an explanation for positive memory deficits in depression.

Common and Dissociable Dysfunction of the Reward System in Bipolar and Unipolar Depression

Unipolar and bipolar depressive episodes have a similar clinical presentation that suggests common dysfunction of the brain's reward system. Here, we evaluated the relationship of both dimensional depression severity and diagnostic category to reward system function in both bipolar and unipolar depression. In total, 89 adults were included, including 27 with bipolar depression, 25 with unipolar depression, and 37 healthy comparison subjects. Subjects completed both a monetary reward task and a resting-state acquisition during 3T BOLD fMRI. Across disorders, depression severity was significantly associated with reduced activation for wins compared with losses in bilateral ventral striatum, anterior cingulate cortex, posterior cingulate cortex, and right anterior insula. Resting-state connectivity within this reward network was also diminished in proportion to depression severity, most notably connectivity strength in the left ventral striatum. In addition, there were categorical differences between patient groups: resting-state connectivity at multiple reward network nodes was higher in bipolar than in unipolar depression. Reduced reward system task activation and resting-state connectivity therefore appear to be a brain phenotype that is dimensionally related to depression severity in both bipolar and unipolar depression. In contrast, categorical differences in reward system resting connectivity between unipolar and bipolar depression may reflect differential risk of mania. Reward system dysfunction thus represents a common brain mechanism with relevance that spans categories of psychiatric diagnosis.

Resting-state connectivity predictors of response to psychotherapy in major depressive disorder

Despite the heterogeneous symptom presentation and complex etiology of major depressive disorder (MDD), functional neuroimaging studies have shown with remarkable consistency that dysfunction in mesocorticolimbic brain systems are central to the disorder. Relatively less research has focused on the identification of biological markers of response to antidepressant treatment that would serve to improve the personalized delivery of empirically supported antidepressant interventions. In the present study, we investigated whether resting-state functional brain connectivity (rs-fcMRI) predicted response to Behavioral Activation Treatment for Depression, an empirically validated psychotherapy modality designed to increase engagement with rewarding stimuli and reduce avoidance behaviors. Twenty-three unmedicated outpatients with MDD and 20 matched nondepressed controls completed rs-fcMRI scans after which the MDD group received an average of 12 sessions of psychotherapy. The mean change in Beck Depression Inventory-II scores after psychotherapy was 12.04 points, a clinically meaningful response. Resting-state neuroimaging data were analyzed with a seed-based approach to investigate functional connectivity with four canonical resting-state networks: the default mode network, the dorsal attention network, the executive control network, and the salience network. At baseline, the MDD group was characterized by relative hyperconnectivity of multiple regions with precuneus, anterior insula, dorsal anterior cingulate cortex (dACC), and left dorsolateral prefrontal cortex seeds and by relative hypoconnectivity with intraparietal sulcus, anterior insula, and dACC seeds. Additionally, connectivity of the precuneus with the left middle temporal gyrus and connectivity of the dACC with the parahippocampal gyrus predicted the magnitude of pretreatment MDD symptoms. Hierarchical linear modeling revealed that response to psychotherapy in the MDD group was predicted by pretreatment connectivity of the right insula with the right middle temporal gyrus and the left intraparietal sulcus with the orbital frontal cortex. These results add to the nascent body of literature investigating pretreatment rs-fcMRI predictors of antidepressant treatment response and is the first study to examine rs-fcMRI predictors of response to psychotherapy.

Reinforcement learning in depression: A review of computational research

Despite being considered primarily a mood disorder, major depressive disorder (MDD) is characterized by cognitive and decision making deficits. Recent research has employed computational models of reinforcement learning (RL) to address these deficits. The computational approach has the advantage in making explicit predictions about learning and behavior, specifying the process parameters of RL, differentiating between model-free and model-based RL, and the computational model-based functional magnetic resonance imaging and electroencephalography. With these merits there has been an emerging field of computational psychiatry and here we review specific studies that focused on MDD. Considerable evidence suggests that MDD is associated with impaired brain signals of reward prediction error and expected value ('wanting'), decreased reward sensitivity ('liking') and/or learning (be it model-free or model-based), etc., although the causality remains unclear. These parameters may serve as valuable intermediate phenotypes of MDD, linking general clinical symptoms to underlying molecular dysfunctions. We believe future computational research at clinical, systems, and cellular/molecular/genetic levels will propel us toward a better understanding of the disease.

Peril and pleasure: an rdoc-inspired examination of threat responses and reward processing in anxiety and depression

As a step toward addressing limitations in the current psychiatric diagnostic system, the National Institute of Mental Health recently developed the Research Domain Criteria (RDoC) to stimulate integrative research-spanning self-report, behavior, neural circuitry, and molecular/genetic mechanisms-on core psychological processes implicated in mental illness. Here, we use the RDoC conceptualization to review research on threat responses, reward processing, and their interaction. The first section of the manuscript highlights the pivotal role of exaggerated threat responses-mediated by circuits connecting the frontal cortex, amygdala, and midbrain-in anxiety, and reviews data indicating that genotypic variation in the serotonin system is associated with hyperactivity in this circuitry, which elevates the risk for anxiety and mood disorders. In the second section, we describe mounting evidence linking anhedonic behavior to deficits in psychological functions that rely heavily on dopamine signaling, especially cost/benefit decision making and reward learning. The third section covers recent studies that document negative effects of acute threats and chronic stress on reward responses in humans. The mechanisms underlying such effects are unclear, but the fourth section reviews new optogenetic data in rodents indicating that GABAergic inhibition of midbrain dopamine neurons, driven by activation of the habenula, may play a fundamental role in stress-induced anhedonia. In addition to its basic scientific value, a better understanding of interactions between the neural systems that mediate threat and reward responses may offer relief from the burdensome condition of anxious depression.