Skip to main content
NIHPA Author Manuscripts logoLink to NIHPA Author Manuscripts
. Author manuscript; available in PMC: 2025 Dec 2.
Published in final edited form as: Curr Top Behav Neurosci. 2022;58:111–127. doi: 10.1007/7854_2022_323

Anhedonia in Depression and Bipolar Disorder

Alexis E Whitton 1, Diego A Pizzagalli 2
PMCID: PMC12665610  NIHMSID: NIHMS2117233  PMID: 35397065

Abstract

Anhedonia is a hallmark feature of depression and is highly prevalent among individuals with mood disorders. The history and neurobiology of anhedonia has been most extensively studied in the context of unipolar Major Depressive Disorder (MDD), with converging lines of evidence indicating that marked anhedonia heralds a more chronic and treatment-refractory illness course. Furthermore, findings from neuroimaging studies suggest that anhedonia in MDD is associated with aberrant reward-related activation in key brain reward regions, particularly blunted reward anticipation-related activation in the ventral striatum. However, the ongoing clinical challenge of treating anhedonia in the context of Bipolar Disorder (BD) also highlights important gaps in our understanding of anhedonia’s prevalence, severity and pathophysiology along the entire mood disorder spectrum. In addition, although current theoretical models posit a key role for reward hyposensitivity in BD depression, unlike studies in MDD, studies in BD do not clearly show evidence for reduced reward-related activation in striatal or other brain regions. Although further research is needed, the evidence to date hints at a divergent pathophysiology for anhedonia in unipolar and bipolar mood disorders, which, if better understood, could lead to significant improvements the diagnosis and treatment of MDD and BD.

Keywords: Anhedonia, Epidemiology, Phenomenology, Major depressive disorder, Bipolar disorder, Reward processing, Neuroimaging

5.1. Introduction

Although anhedonia is present across many psychiatric conditions, depression is perhaps its most paradigmatic disorder. This chapter provides a historical overview of the role of anhedonia in depression and its prevalence across Major Depressive Disorder (MDD) and Bipolar Disorder (BD). Complementing these epidemiological studies, we highlight qualitative studies describing the phenomenology of anhedonia, focusing on how the subjective experience of anhedonia in individuals with mood disorders extends beyond the loss of pleasure described in current diagnostic classification systems. Drawing upon these separate lines of evidence, we also highlight quantitative and qualitative differences in anhedonia in unipolar and bipolar mood disorders. Next, we provide a critical review of studies outlining the clinical significance of anhedonia, focusing on whether anhedonia and markers of its underlying neural circuitry hold utility for predicting mood disorder trajectory and treatment response. Finally, we briefly outline the current understanding of the neurobiological underpinnings of anhedonia in the context of mood disorders, focusing on how functioning in neural reward pathways goes awry in MDD and BD. Importantly, we comment on the degree to which a shared or distinct pathophysiology may underpin anhedonia in unipolar relative to bipolar mood disorders. Taken together, this overview will provide the reader with a broad knowledge of where the field stands in terms of our ability to better understand, identify, and treat anhedonia in the context of mood disorders.

5.2. History, Epidemiology and Phenomenology of Anhedonia in Mood Disorders

5.2.1. Anhedonia as a Diagnostic Criterion for Depression

Descriptions of anhedonia have featured prominently in clinical texts on depression (or “melancholia”), dating back to the 19th century. In 1889, English physiologist William Bevan Lewis published A Text-Book of Mental Diseases (W. B. Lewis, 1889), which included an analysis of four thousand cases of mental illness treated at the West Riding Asylum, where he worked as Medical Director. In describing states of depression, he noted that “The patient exhibits a growing indifference to his former pursuits and pleasures: the ordinary duties of life and business become irksome and devoid of interest.” (pp. 143–144). Around this time, the term anhedonia was formally defined by French psychologist Théodule-Armand Ribot as the “inability to experience pleasure”, and proposed as a state antithetical to analgesia (i.e., the absence of pain; Ribot, 1896). The marked impact of anhedonia on patients’ quality of life is also evident in these early texts. In 1934, prominent psychiatrist Aubrey J. Lewis published a detailed analysis of 61 cases of mental illness treated at the Maudsley Hospital in London, where he was an Assistant Medical Officer. He observed how frequently depressed patients who had travelled from picturesque regions across Europe “…mention this failure to enjoy the sight of their fields, the sky and the trees and the flowers as one of the most distressing of their symptoms, a deprivation most keenly felt.” (A. J. Lewis, 1934 p. 331).

Although anhedonia was common in accounts of depression, several prominent clinicians noted the marked variability in how anhedonia manifested from patient-to-patient. In the early 20th century, there was a growing interest in describing ‘subtypes’ of depression that were more homogeneous in their clinical presentation. In The Varieties of Religious Experience, American psychologist William James described a particular form of depression characterized by a “passive joylessness” and “loss of appetite for all life’s values.” (James, 1902). The notion of depressive subtypes was later formalized by American psychiatrist Donald F. Klein, who proposed the existence of ‘endogenomorphic depression’, a unique type of depression characterized by a “sharp, unreactive, pervasive impairment of the capacity to experience pleasure or to respond effectively to the anticipation of pleasure” (Klein, 1974, p. 449).

Despite descriptions of anhedonia featuring prominently in early psychiatric texts, it was not until Klein’s work on endogenomorphic depression that anhedonia was included in the formal diagnostic criteria for depression. The symptom first appeared in the DSM-III (APA, 1980), where it was listed among the diagnostic criteria for melancholia. With the release of the DSM-IV (APA, 1994), a specifier was added to denote a subtype of depression ‘With Melancholic Features’, which described individuals with a “near-complete absence of the capacity for pleasure, not entirely diminution”. In the current DSM-5 (APA, 2013) the melancholic specifier has been retained, with the intended purpose of identifying a more homogeneous subgroup of depressed individuals who experience marked impairments in hedonic capacity. However, the degree to which this specifier serves its intended purpose remains a topic of debate. Using criteria from the DSM-5, Fried and colleagues (2020) calculated 10,377 unique symptom combinations that could yield a diagnosis of MDD. However, they found that there were as many as 341,737 different symptom combinations that could yield a diagnosis of MDD with Melancholic Features, challenging the notion that the melancholic specifier identifies a more homogeneous subgroup of depressed individuals.

In contrast to the rich descriptions of anhedonia documented in accounts of individuals with unipolar MDD, much less is known about the history of anhedonia in the context of BD. This may in part reflect an emphasis on the unique qualities of BD mania, as well as an assumption that depressive episodes across unipolar and bipolar mood disorders are of the same nature and kind. However, research into the neurobiology of mood disorders highlights several important points of divergence between unipolar and bipolar mood pathology. Accordingly, although the DSM criteria for a Major Depressive Episode is identical across MDD and BD, more thorough descriptive accounts of BD depression may yield important insights into the degree to which hedonic disturbances overlap and diverge across the mood disorder spectrum.

5.2.2. Epidemiology of Anhedonia in Mood Disorders

5.2.2.1. Prevalence of Anhedonia in Mood Disorders

Anhedonia is highly prevalent among individuals with mood disorders. When defined using the cut-off for clinical anhedonia on the Snaith-Hamilton Pleasure Scale (≥ 3), anhedonia prevalence is approximately 70% in individuals with MDD (Cao et al., 2019) and 52% in individuals with BD depression (Mazza, Squillacioti, Pecora, Janiri, & Bria, 2009). Anhedonic symptoms often persist when other symptoms remit, contributing to increased inter-episode functional impairment. For example, in a study comparing the prevalence of anhedonia in euthymic individuals with BD, individuals in remission from MDD, and healthy controls, Di Nicola and colleagues (2013) found that one fifth of individuals with BD and one quarter of individuals with MDD had clinically significant anhedonia, despite scoring in the non-clinical range on measures of depression and mania. Although current diagnostic criteria conceptualize anhedonia as a state-like feature of a Major Depressive Episode, evidence of significant inter-episode anhedonia in individuals with mood disorders suggests that it may have a more enduring, trait-like quality.

5.2.2.2. Severity of Anhedonia Across Distinct Mood Disorder Diagnoses

To date, the findings from studies comparing self-reported or clinician-assessed anhedonia severity in MDD and BD samples have been mixed. Some studies report equivalent levels of anhedonia in individuals with BD and MDD in either depressed (Mula et al., 2010; Perlis, Brown, Baker, & Nierenberg, 2006) or euthymic (Di Nicola et al., 2013) states. In contrast, others have reported more severe anhedonia in adults with MDD than in adults with BD (Souery et al., 2012), whereas others report more severe anhedonia in youth with BD than in youth with MDD (Diler et al., 2017). The findings from studies comparing different forms of anhedonia across BD and MDD samples are also inconsistent, with some showing differences in anticipatory pleasure (Mitchell, 2001), and others showing differences in consummatory pleasure (Zou et al., 2020) between the two disorders.

An important factor that likely underpins these discrepant findings is that MDD and BD samples are rarely matched on overall illness severity. Studies demonstrating more severe anhedonia in youth with BD compared to youth with MDD may reflect the fact that younger-onset BD tends to be a more severe form of the illness (Perlis et al., 2004). Similarly, evidence of more severe anhedonia in BD type II compared to BD type I (e.g., Dimick, Hird, Fiksenbaum, Mitchell, & Goldstein, 2021) may reflect the more pervasive depressive symptomatology observed in BD type II (Karanti et al., 2020). Studies using MDD and BD samples that are matched in terms of illness severity are needed to better understand differences in anhedonia severity between the two conditions.

5.2.3. Anhedonia Phenomenology

In the DSM-5, anhedonia is defined as a “Markedly diminished interest or pleasure in all, or almost all, activities” (APA, 2013). Although this definition has changed very little since the term was first introduced by Ribot (Ribot, 1896), findings from phenomenological studies suggest that the actual experience of anhedonia likely encompasses a broader array of hedonic impairments, as well as their sequelae. Phenomenological studies focus on the lived experience of individuals with mental illness and provide rich insights into the features of psychiatric disorders that are most salient and/or disabling. In addition to loss of pleasure, phenomenological studies highlight the important role of loss of drive, connection, and purpose in the subjective experience of anhedonia. Watson and colleagues (2020) recently highlighted four key themes related to anhedonia, which emerged from a series of interviews with depressed adolescents. Two primary themes centered on the loss of joy and flattening of emotions, and difficulty with motivation and active engagement. Specifically, participants described feelings of boredom, monotony, and indifference to events happening around them. Two secondary themes also emerged: losing a sense of connection and belonging, and questioning sense of self and purpose. In particular, participants noted feeling disconnected from their social world and losing their sense of what was important in life. Similar themes were described in a recent qualitative study in depressed adults, where “…inertia, the lack of motivation, the lack of meaning in life…” was identified as one of the most distressing aspects of living with depression (Chevance et al., 2020).

Findings from phenomenological studies are interesting for several reasons. First, they illustrate the breadth of anhedonic experiences that may need to be addressed in the clinical management of mood disorders. In particular, they demonstrate that reductions in motivational drive are a salient feature of depression that have marked impacts on daily functioning. Whether reductions in motivational drive are a consequence of reduced capacity for pleasure or reflect a primary disturbance distinct from other aspects of hedonic functioning remains an important unanswered question. Furthermore, themes emerging from phenomenological research highlight important links between loss of pleasure and other aspects of depression that, despite having a significant impact on quality of life, do not feature prominently in the modern discourse on mood disorders. One such example is depersonalization, a common feature of depression characterized by a sense of detachment from oneself and the world. Individuals experiencing depersonalization often describe themselves as functioning on autopilot without purpose, and as if the world and those around them have taken on an unfamiliar quality. Watson et al.’s (2020) findings hint at the important links between anhedonia and an individual’s feelings of connection to their physical and social world, and the impact this may have on their sense of meaning and purpose in life. Gaining a better understanding of these links may help to shed light on the processes that underpin some of depression’s more complex and nebulous features.

5.3. Clinical Significance of Anhedonia in Mood Disorders

5.3.1. Association with Illness Course

Converging lines of evidence suggest that anhedonia is associated with a more severe and recurrent illness course in the context of mood disorders. Cross-sectional studies show that increasing levels of anhedonia in adolescents with MDD are associated with a greater number of prior depressive episodes, longer depressive episode duration, and greater overall illness severity (Gabbay et al., 2015). Similarly, longitudinal studies in adults with MDD indicate that more severe levels of anhedonia predict a greater likelihood of depression still being present 12 months later (Spijker, Bijl, De Graaf, & Nolen, 2001). These effects are not limited to unipolar MDD. For example, in youth with BD, severe lifetime anhedonia has been found to predict more severe lifetime mania (Dimick et al., 2021). These studies indicate that the presence of marked anhedonia may herald a more severe illness course across the mood disorder spectrum.

Anhedonia has also been linked to greater risk for suicidality, rendering it a potential indicator of patients who may require more intensive treatment and monitoring. Heightened levels of anhedonia have been found to be associated with increased suicidal ideation cross-sectionally (Ballard et al., 2017; Ducasse et al., 2018) and longitudinally in mood disordered samples (Ducasse et al., 2021), with some studies showing that associations also extend to increased risk for suicide attempts (Fawcett et al., 1990; Sagud et al., 2020). Importantly, these associations remain significant when controlling for overall depression severity, suggesting that anhedonia may a risk factor of suicidality independent from depression more generally.

5.3.2. Association with Treatment Response

Studies examining anhedonia’s links with treatment response typically focus on one of two questions: (1) Does pre-treatment anhedonia severity predict treatment responsiveness? (2) Does treatment improve anhedonic symptoms? Here we review studies addressing the first of these questions, while the second is addressed in detail in Chapters 20–22.

Several studies have shown that in individuals with MDD, greater levels of anhedonia at the outset of treatment predict poorer responsiveness to a range of interventions, including antidepressant pharmacotherapy (Dunlop et al., 2020; Uher et al., 2012), cognitive behavioral therapy (Craske, Meuret, Ritz, Treanor, & Dour, 2016), and repetitive transcranial magnetic stimulation (Downar et al., 2014). The most consistent findings have emerged for selective serotonin reuptake inhibitors (SSRIs), where pre-treatment anhedonia predicts longer time to remission and fewer depression-free days following SSRI treatment (McMakin et al., 2012). These findings are corroborated by studies showing that behavioral and neural indices of reward processing predict treatment response in individuals with MDD. For example, studies using behavioral reward learning tasks have found that poorer pre-treatment reward learning or reward sensitivity is associated with poorer response to psychotherapy and/or pharmacotherapy (Ang et al., 2020; Vrieze et al., 2013; Whitton et al., 2020). Similarly, studies examining patterns of reward-related brain activation either using electroencephalography or fMRI have observed associations between blunted pre-treatment neural reward responsiveness and poorer response to psychotherapy (Webb et al., 2021) and pharmacotherapy (Whitton et al., 2020). Similar patterns have been observed for studies examining functional connectivity of corticostriatal circuits (An et al., 2019; Downar et al., 2014; Walsh et al., 2017). An important caveat is that few studies have included multiple active treatment arms, making it difficult to determine whether pre-treatment anhedonia/reward processing predicts response to a specific treatment or the persistence of depressive symptoms more generally. One of the few studies that has used multiple comparator treatments provides initial evidence that anhedonia/reward processing measures may predict responsiveness to dopaminergic pharmacotherapy (e.g., Ang et al., 2020), consistent with the critical role that dopaminergic abnormalities are thought to play in reward processing. Specifically, this study showed that more normative pre-treatment reward learning and resting state corticostriatal functional connectivity predicted response to the atypical antidepressant bupropion after failing 8-weeks of SSRI treatment (Ang et al., 2020).

In contrast, little is known about the relationship between pre-treatment anhedonia and response to BD-specific psychotherapy or pharmacotherapy (e.g., interpersonal and social rhythm therapy or mood stabilizers). The majority of the studies examining anhedonia as a predictor of treatment response have focused solely on samples with unipolar MDD, or mixed MDD and BD depression samples (e.g., Downar et al., 2014), and comprehensive studies of treatment response indicators in BD have not examined anhedonia and/or reward processing as separate predictors (e.g., Hui et al., 2019; Kleindienst, Engel, & Greil, 2005). To date, the literature in BD has focused more closely on other clinical features, such as increased emotional reactivity and lability, as being predictive of treatment outcomes. For example, in a recent multisite study examining predictors of response to lithium in individuals with BD, Lin and colleagues (2021) found that treatment responsiveness was most closely related to pre-treatment anxiety and the presence of mixed episodes (i.e., mood episodes characterized by both depression and (hypo)manic symptoms). It is possible that distinct aspects of affective dysfunction relate to treatment outcome in MDD and BD, with anhedonia playing a prominent role in MDD and mood lability being more relevant in the case of BD. However, given the paucity of studies examining anhedonia as a predictor of treatment response in BD, future studies comparing distinct predictors in the same cohort are required to confirm this.

5.4. Neurobiology of Anhedonia in Mood Disorders

Research into the neurobiology of anhedonia in mood disorders has focused most closely on dysfunction in the domains of reward anticipation, reward consumption, and reward learning. Reward anticipation describes the ability to represent future incentives, while reward consumption captures the ability to compute the value of a reward as a function of its magnitude, predictability, time to expected delivery, and the effort required to obtain it. Reward learning integrates anticipatory and consummatory processes and encompasses mechanisms involved in learning about reward-predictive cues and how outcomes shape subsequent behavior.

Each of these processes maps onto overlapping yet partially distinct neural circuitry (for reviews, see Der-Avakian & Markou, 2012; Husain & Roiser, 2018). Although a comprehensive review of the neural circuitry implicated in various reward subdomains is beyond the scope of this chapter (for reviews, see Borsini, Wallis, Zunszain, Pariante, & Kempton, 2020; Haber & Knutson, 2010; Höflich, Michenthaler, Kasper, & Lanzenberger, 2019; Russo & Nestler, 2013), it is important to emphasize the key role of the dopaminergic mesolimbic pathway. This pathway originates in the ventral tegmental area (VTA), and projects to the ventral (e.g., nucleus accumbens) and dorsal (e.g., caudate, putamen) striatum, and subsequently the prefrontal cortex (PFC), including the medial PFC and anterior cingulate cortex (ACC), among other regions. Relevant to our discussion, ventral striatal regions have been found to be critically implicated in incentive motivation and reward prediction errors (RPEs; i.e., evaluating that an outcome is different than expected), whereas dorsal striatal regions have been involved in stimulus-response-reward learning (i.e., linking incentives to actions); medial PFC and orbitofrontal cortex (OFC) regions have been implicated in stimulus-reinforcement representations, including updating such representations to guide behavior; finally, the dorsal ACC has been involved in integrating reward probabilities over time.

5.4.1. Neural Correlates of Reward Processing in MDD

5.4.1.1. Blunted Anticipation-Related Activation in the Ventral Striatum as a Trait-Like Feature of MDD

Reduced striatal activation during reward anticipation is one of the most common findings in neuroimaging studies of reward processing in MDD. Meta-analyses show that compared to healthy controls, individuals with MDD exhibit blunted activation in the ventral striatum during anticipation of reward (Keren et al., 2018). Similar findings have been observed in asymptomatic individuals who are at increased familial risk for MDD (Olino et al., 2014), suggesting that blunted anticipation-related striatal activation may be a trait-like vulnerability marker for MDD. In adolescents, blunted anticipation-related ventral striatum activation has also been found to predict increases in depressive symptom severity over 2 years (Morgan, Olino, McMakin, Ryan, & Forbes, 2013), as well as new depression onset and concurrent anhedonia longitudinally (Stringaris et al., 2015), suggesting that this marker is associated with depressive illness course. Finally, changes in anticipation-related ventral striatal activation during SSRI treatment has been found to be associated with changes in depressive symptom severity (Takamura et al., 2017), suggesting that normalizing aberrant anticipation-related activation in the ventral striatum may be important for the clinical effectiveness of antidepressant treatments.

5.4.1.2. Disrupted Corticostriatal Activation to Reward Outcome (Consumption) in MDD

Reduced activation in ventral (nucleus accumbens) and dorsal (caudate, putamen) striatum, ACC, and OFC, as well as potentiated activation in various PFC regions (medial PFC, ventromedial PFC, and dorsolateral PFC) has emerged in tasks probing consummatory anhedonia (Borsini et al., 2020; O’Callaghan & Stringaris, 2019; Zhang et al., 2016), with PFC over-recruitment thought to reflect over-compensation for reduced striatal activation (Forbes et al., 2009; O’Callaghan & Stringaris, 2019; Pan et al., 2017). Blunted reward consumption-related ventral striatal activation has also been dimensionally linked to anhedonia severity (Epstein et al., 2006). Functional connectivity between reward hubs (nucleus accumbens, VTA, OFC) and the ventromedial PFC while listening to pleasant music correlated negatively with anhedonia (Young et al., 2016). Finally, although striatal responses to rewards normalize after depression remission (Geugies et al., 2019), other abnormalities persist, including blunted OFC activation to reward receipt (Dichter, Kozink, McClernon, & Smoski, 2012) and reduced maintenance of ventral striatal responses to positive cues (Admon & Pizzagalli, 2015).

5.4.1.3. Disrupted Reward Prediction Errors in MDD

Studies using computational modeling to quantify expected value and RPEs in MDD have generally reported reduced RPE in the ventral and dorsal striatum (Gradin et al., 2011; Kumar et al., 2018; Kumar et al., 2008), ACC (Rupprechter et al., 2020; Ubl et al., 2015) and medial OFC (Rothkirch, Tonn, Köhler, & Sterzer, 2017), although null findings have emerged (Rutledge et al., 2017). In a study using an instrumental reinforcement learning task, MDD was characterized by reduced medial OFC and ventral striatal RPE, which correlated with anhedonia severity (Rothkirch et al., 2017). Of note, larger ventral striatum RPE has also been found to predict reductions in anhedonia 6 months later (Eckstrand et al., 2019). In addition, although individuals in remission from MDD show normative ventral striatum RPE, VTA RPE remained upregulated, indicating that some reward-related abnormalities persist after remission (Geugies et al., 2019). Collectively, these findings suggest that blunted valuation of expected rewards and reward learning might represent MDD-related vulnerabilities.

5.4.2. Neurobiology of Reward Processing in BD

Theoretical models of BD posit that mania and depression are underpinned by excessive activation and deactivation of brain reward responsiveness, respectively (Bart, Titone, Ng, Nusslock, & Alloy, 2021). Such models have considerable face validity in terms of explaining the hyper-hedonic symptoms of mania (e.g., spending sprees, excessive sociability) and anhedonic symptoms of BD depression. However, findings from neuroimaging studies are far from conclusive, and few have examined neural correlates of anhedonia in the context of BD.

5.4.2.1. Heightened Reward-Related Activation in the Lateral OFC Characterizes BD

One of the most consistent findings in fMRI studies in BD is increased left lateral OFC (particularly left ventrolateral PFC) activation during reward anticipation. This has been observed across all mood states, including depression (Chase et al., 2013), mania (Bermpohl et al., 2010) as well as during inter-episode periods of euthymia (Nusslock et al., 2012), and in both BD type I (Bermpohl et al., 2010; Chase et al., 2013; Nusslock et al., 2012) and BD type II (Caseras, Lawrence, Murphy, Wise, & Phillips, 2013). Similar patterns of activation have also been observed in unaffected first-degree relatives (Cattarinussi, Di Giorgio, Wolf, Balestrieri, & Sambataro, 2019), suggesting that abnormal reward-related left lateral OFC activation may be a trait-like vulnerability marker for BD. Some studies have found that this aberrant activation extends to consummatory processes, with heightened consumption-related lateral OFC activation being found in individuals with subthreshold hypomanic symptoms (O’Sullivan, Szczepanowski, El-Deredy, Mason, & Bentall, 2011), euthymic BD (Linke et al., 2012; Mason, O’Sullivan, Montaldi, Bentall, & El-Deredy, 2014), and in unaffected first-degree relatives (Linke et al., 2012). The left ventrolateral PFC has been implicated in evaluating cues denoting the probability of immediate future reward (Coffman et al., 2021), hence, aberrant left ventrolateral PFC function might underpin sensation seeking and impulsivity in BD.

5.4.2.2. Mixed Pattern of Striatal Activation in Response to Reward in BD

Unlike studies in unipolar MDD, studies in individuals with BD depression do not consistently demonstrate blunted striatal responses to rewards. For example, some studies have shown decreased striatal responses during reward consumption in individuals with BD depression relative to both healthy controls and individuals with MDD (Redlich et al., 2015). Other studies have found no differences in striatal activation (Chase et al., 2013; Satterthwaite et al., 2015) or even increased striatal activation to reward when under stress (Berghorst et al., 2016) in depressed individuals with BD relative to controls. Studies of reward learning in BD have also yielded mixed findings. Studies using behavioral probabilistic reward learning tasks have reported evidence of poorer reward learning in euthymic or mildly depressed individuals with BD relative to controls (Pizzagalli, Goetz, Ostacher, Iosifescu, & Perlis, 2008). However, studies using this same task have produced mixed findings depending on whether the BD sample was treatment-seeking (e.g., Whitton et al., 2021) or had psychotic features (Lewandowski et al., 2016). One of the few studies to examine striatal RPE signals during a reinforcement learning task also found no differences between healthy controls or individuals with BD (Whitton et al., 2021). The variability in these findings compared to those in MDD may be attributable to greater use of medicated samples in BD research and different patterns of comorbidity. For example, studies examining striatal responses to reward in BD have used samples where nearly all individuals were taking psychotropic medication, whereas meta-analyses of neural reward responsiveness in individuals with MDD indicate that more than 80% of participants were unmedicated (Keren et al., 2018). However, an alternate possibility is that the hedonic deficits observed in BD depression may be fundamentally different from those in unipolar MDD. If true, this would prompt a revision of theoretical models of BD depression and the role reward hyposensitivity may play in this aspect of the illness. For example, rather than showing blunted responses to reward, individuals with BD depression may show increased sensitivity to reward loss, or a greater sensitivity to differences between expected and actual outcomes regardless of the valence of the outcome. Given that these processes are thought to be underpinned by partially distinct neural pathways, further clarity on these issues could highlight novel treatment targets for BD depression.

5.4.3. Differences in Reward-Related Brain Activation between MDD and BD

Given the overlap in clinical presentation between MDD and BD during the depressive phase of the illness and the fact that recollection of prior (hypo)manic episodes in individuals with BD is not always clear, neural markers capable of distinguishing between these two conditions may aid in improving diagnostic precision. Toward this end, Chase and colleagues (2013) found that depressed individuals with BD showed increased anticipation-related activation in the left ventrolateral PFC compared to those with MDD, despite comparable disease severity. A recent study that included BD individuals in a variety of mood states also found evidence for decreased reward anticipation-related ventral striatal activation in individuals with BD relative to those with MDD (Schwarz et al., 2020). Similar findings were observed by Redlich and colleagues (2015) in terms of consumption-related activation, where those with BD depression showed decreased reward consumption-related activation in the striatum, thalamus, insula and PFC relative to individuals with MDD. These studies highlight quantitative differences in neural reward processing in MDD and BD depression, suggesting that hedonic disturbances in these conditions may partly diverge in terms of their underlying causes.

5.5. Summary

Findings from epidemiological, phenomenological and neuroimaging studies summarized in this chapter emphasize the clinical significance of anhedonia in mood disorders, and the critical role that anhedonia treatments will play in reducing the global burden of these disorders. Although vulnerability markers and treatment targets for anhedonia are emerging in the context of unipolar MDD, our understanding of anhedonia’s causes in BD remain limited, contributing to the clinical challenges inherent in treating BD depression. Finally, despite overlapping in their clinical features, studies highlight potential divergence in anhedonia pathophysiology in MDD and BD. Future research is needed to better understand these points of divergence, as they hold significant clinical utility for improving the early diagnosis and treatment of mood disorders.

Acknowledgements and Disclosures

Dr. Pizzagalli was partially supported by R37 MH068376 and P50 MH119467. Over the past 3 years, Dr. Pizzagalli has received consulting fees from Albright Stonebridge Group, BlackThorn Therapeutics, Boehringer Ingelheim, Compass Pathway, Concert Pharmaceuticals, Engrail Therapeutics, Neurocrine Biosciences, Neuroscience Software, Otsuka Pharmaceuticals, and Takeda Pharmaceuticals; one honorarium from Alkermes, and research funding from NIMH, Dana Foundation, Brain and Behavior Research Foundation, and Millennium Pharmaceuticals. In addition, he has received stock options from BlackThorn Therapeutics and Compass Pathway. Dr. Whitton has no financial disclosures, and there are no conflicts of interest with the work conducted in this study. All views expressed are solely those of the authors.

References

  1. Admon R, & Pizzagalli DA (2015). Corticostriatal pathways contribute to the natural time course of positive mood. Nature communications, 6(1), 1–11. [DOI] [PMC free article] [PubMed] [Google Scholar]
  2. An J, Li L, Wang L, Su Y-A, Wang Y, Li K, . . . Si, T. (2019). Striatal functional connectivity alterations after two-week antidepressant treatment associated to enduring clinical improvement in major depressive disorder. Frontiers in psychiatry, 10, 884. [DOI] [PMC free article] [PubMed] [Google Scholar]
  3. Ang Y-S, Kaiser R, Deckersbach T, Almeida J, Phillips ML, Chase HW, . . . McGrath P (2020). Pretreatment reward sensitivity and frontostriatal resting-state functional connectivity are associated with response to bupropion after sertraline nonresponse. Biological Psychiatry, 88(8), 657–667. [DOI] [PMC free article] [PubMed] [Google Scholar]
  4. Association AP (1980). Diagnostic and statistical manual of mental disorders (3rd ed.). Washington, DC: Author. [Google Scholar]
  5. Association AP (1994). Diagnostic and statistical manual of mental disorders (4th ed.). Washington, DC: Author. [Google Scholar]
  6. Association AP (2013). Diagnostic and statistical manual of mental disorders (5th ed.). Washington, DC: Author. [Google Scholar]
  7. Ballard ED, Wills K, Lally N, Richards EM, Luckenbaugh DA, Walls T, . . . Park L (2017). Anhedonia as a clinical correlate of suicidal thoughts in clinical ketamine trials. Journal of affective disorders, 218, 195–200. [DOI] [PMC free article] [PubMed] [Google Scholar]
  8. Bart CP, Titone MK, Ng TH, Nusslock R, & Alloy LB (2021). Neural reward circuit dysfunction as a risk factor for bipolar spectrum disorders and substance use disorders: A review and integration. Clinical Psychology Review, 102035. [DOI] [PMC free article] [PubMed] [Google Scholar]
  9. Berghorst LH, Kumar P, Greve DN, Deckersbach T, Ongur D, Dutra SJ, & Pizzagalli DA (2016). Stress and reward processing in bipolar disorder: a functional magnetic resonance imaging study. Bipolar disorders, 18(7), 602–611. [DOI] [PMC free article] [PubMed] [Google Scholar]
  10. Bermpohl F, Kahnt T, Dalanay U, Hägele C, Sajonz B, Wegner T, . . . Wrase J (2010). Altered representation of expected value in the orbitofrontal cortex in mania. Human brain mapping, 31(7), 958–969. [DOI] [PMC free article] [PubMed] [Google Scholar]
  11. Borsini A, Wallis ASJ, Zunszain P, Pariante CM, & Kempton MJ (2020). Characterizing anhedonia: a systematic review of neuroimaging across the subtypes of reward processing deficits in depression. Cognitive, Affective, & Behavioral Neuroscience, 20, 816–841. [DOI] [PMC free article] [PubMed] [Google Scholar]
  12. Cao B, Park C, Subramaniapillai M, Lee Y, Iacobucci M, Mansur RB, . . . McIntyre RS (2019). The efficacy of vortioxetine on anhedonia in patients with major depressive disorder. Frontiers in psychiatry, 10, 17. [DOI] [PMC free article] [PubMed] [Google Scholar]
  13. Caseras X, Lawrence NS, Murphy K, Wise RG, & Phillips ML (2013). Ventral striatum activity in response to reward: differences between bipolar I and II disorders. American Journal of Psychiatry, 170(5), 533–541. [DOI] [PMC free article] [PubMed] [Google Scholar]
  14. Cattarinussi G, Di Giorgio A, Wolf RC, Balestrieri M, & Sambataro F (2019). Neural signatures of the risk for bipolar disorder: A meta-analysis of structural and functional neuroimaging studies. Bipolar disorders, 21(3), 215–227. [DOI] [PubMed] [Google Scholar]
  15. Chase HW, Nusslock R, Almeida JR, Forbes EE, LaBarbara EJ, & Phillips ML (2013). Dissociable patterns of abnormal frontal cortical activation during anticipation of an uncertain reward or loss in bipolar versus major depression. Bipolar disorders, 15(8), 839–854. [DOI] [PMC free article] [PubMed] [Google Scholar]
  16. Chevance A, Ravaud P, Tomlinson A, Le Berre C, Teufer B, Touboul S, . . . Tran V (2020). Identifying outcomes for depression that matter to patients, informal caregivers, and health-care professionals: qualitative content analysis of a large international online survey. Lancet Psychiatry, 7(8). [DOI] [PubMed] [Google Scholar]
  17. Coffman BA, Torrence N, Murphy T, Bebko G, Graur S, Chase HW, . . . Phillips ML (2021). Trait Sensation Seeking is Associated with Heightened Beta-Band Oscillatory Dynamics over Left Ventrolateral Prefrontal Cortex during Reward Expectancy. Journal of Affective Disorders. [DOI] [PubMed] [Google Scholar]
  18. Craske MG, Meuret AE, Ritz T, Treanor M, & Dour HJ (2016). Treatment for anhedonia: A neuroscience driven approach. Depression and anxiety, 33(10), 927–938. [DOI] [PubMed] [Google Scholar]
  19. Der-Avakian A, & Markou A (2012). The neurobiology of anhedonia and other reward-related deficits. Trends in neurosciences, 35(1), 68–77. [DOI] [PMC free article] [PubMed] [Google Scholar]
  20. Di Nicola M, De Risio L, Battaglia C, Camardese G, Tedeschi D, Mazza M, . . . Di Giannantonio M (2013). Reduced hedonic capacity in euthymic bipolar subjects: a trait-like feature? Journal of Affective Disorders, 147(1–3), 446–450. doi: 10.1016/j.jad.2012.10.004 [DOI] [PubMed] [Google Scholar]
  21. Dichter GS, Kozink RV, McClernon FJ, & Smoski MJ (2012). Remitted major depression is characterized by reward network hyperactivation during reward anticipation and hypoactivation during reward outcomes. Journal of affective disorders, 136(3), 1126–1134. [DOI] [PMC free article] [PubMed] [Google Scholar]
  22. Diler RS, Goldstein TR, Hafeman D, Merranko J, Liao F, Goldstein BI, . . . Yen S (2017). Distinguishing bipolar depression from unipolar depression in youth: preliminary findings. Journal of child and adolescent psychopharmacology, 27(4), 310–319. [DOI] [PMC free article] [PubMed] [Google Scholar]
  23. Dimick MK, Hird MA, Fiksenbaum LM, Mitchell RH, & Goldstein BI (2021). Severe anhedonia among adolescents with bipolar disorder is common and associated with increased psychiatric symptom burden. Journal of psychiatric research, 134, 200–207. [DOI] [PubMed] [Google Scholar]
  24. Downar J, Geraci J, Salomons TV, Dunlop K, Wheeler S, McAndrews MP, . . . Kennedy SH (2014). Anhedonia and reward-circuit connectivity distinguish nonresponders from responders to dorsomedial prefrontal repetitive transcranial magnetic stimulation in major depression. Biological psychiatry, 76(3), 176–185. [DOI] [PubMed] [Google Scholar]
  25. Ducasse D, Dubois J, Jaussent I, Azorin JM, Etain B, Gard S, . . . Aubin V (2021). Association between anhedonia and suicidal events in patients with mood disorders: A 3-year prospective study. Depression and anxiety, 38(1), 17–27. [DOI] [PubMed] [Google Scholar]
  26. Ducasse D, Loas G, Dassa D, Gramaglia C, Zeppegno P, Guillaume S, . . . Courtet P (2018). Anhedonia is associated with suicidal ideation independently of depression: A meta-analysis. Depression and anxiety, 35(5), 382–392. [DOI] [PubMed] [Google Scholar]
  27. Dunlop K, Rizvi SJ, Kennedy SH, Hassel S, Strother SC, Harris JK, . . . Mansouri F (2020). Clinical, behavioral, and neural measures of reward processing correlate with escitalopram response in depression: a Canadian Biomarker Integration Network in Depression (CAN-BIND-1) Report. Neuropsychopharmacology, 45(8), 1390–1397. [DOI] [PMC free article] [PubMed] [Google Scholar]
  28. Eckstrand KL, Forbes EE, Bertocci MA, Chase HW, Greenberg T, Lockovich J, . . . Bebko G (2019). Anhedonia Reduction and the Association Between Left Ventral Striatal Reward Response and 6-Month Improvement in Life Satisfaction Among Young Adults. JAMA psychiatry. [DOI] [PMC free article] [PubMed] [Google Scholar]
  29. Epstein J, Pan H, Kocsis JH, Yang Y, Butler T, Chusid J, . . . Stern E (2006). Lack of ventral striatal response to positive stimuli in depressed versus normal subjects. American Journal of Psychiatry, 163(10), 1784–1790. [DOI] [PubMed] [Google Scholar]
  30. Fawcett J, Scheftner WA, Fogg L, Clark DC, Young MA, Hedeker D, & Gibbons R (1990). Time-related predictors of suicide in major affective disorder. The American journal of psychiatry. [DOI] [PubMed] [Google Scholar]
  31. Forbes EE, Hariri AR, Martin SL, Silk JS, Moyles DL, Fisher PM, . . . Axelson DA (2009). Altered striatal activation predicting real-world positive affect in adolescent major depressive disorder. American Journal of Psychiatry, 166(1), 64–73. [DOI] [PMC free article] [PubMed] [Google Scholar]
  32. Fried EI, Coomans F, & Lorenzo-Luaces L (2020). The 341 737 ways of qualifying for the melancholic specifier. The Lancet Psychiatry, 7(6), 479–480. [DOI] [PubMed] [Google Scholar]
  33. Gabbay V, Johnson AR, Alonso CM, Evans LK, Babb JS, & Klein RG (2015). Anhedonia, but not irritability, is associated with illness severity outcomes in adolescent major depression. Journal of child and adolescent psychopharmacology, 25(3), 194–200. [DOI] [PMC free article] [PubMed] [Google Scholar]
  34. Geugies H, Mocking RJ, Figueroa CA, Groot PF, Marsman J-BC, Servaas MN, . . . Ruhe HG (2019). Impaired reward-related learning signals in remitted unmedicated patients with recurrent depression. Brain, 142(8), 2510–2522. [DOI] [PMC free article] [PubMed] [Google Scholar]
  35. Gradin VB, Kumar P, Waiter G, Ahearn T, Stickle C, Milders M, . . . Steele JD (2011). Expected value and prediction error abnormalities in depression and schizophrenia. Brain, 134(6), 1751–1764. [DOI] [PubMed] [Google Scholar]
  36. Haber SN, & Knutson B (2010). The reward circuit: linking primate anatomy and human imaging. Neuropsychopharmacology, 35(1), 4–26. [DOI] [PMC free article] [PubMed] [Google Scholar]
  37. Höflich A, Michenthaler P, Kasper S, & Lanzenberger R (2019). Circuit mechanisms of reward, anhedonia, and depression. International Journal of Neuropsychopharmacology, 22(2), 105–118. [DOI] [PMC free article] [PubMed] [Google Scholar]
  38. Hui T, Kandola A, Shen L, Lewis G, Osborn D, Geddes J, & Hayes J (2019). A systematic review and meta-analysis of clinical predictors of lithium response in bipolar disorder. Acta Psychiatrica Scandinavica, 140(2), 94–115. [DOI] [PMC free article] [PubMed] [Google Scholar]
  39. Husain M, & Roiser JP (2018). Neuroscience of apathy and anhedonia: a transdiagnostic approach. Nature Reviews Neuroscience, 19(8), 470–484. [DOI] [PubMed] [Google Scholar]
  40. James W (1902). The varieties of religious experience: A study in human nature. New York, NY: Longmans, Green & Co. [Google Scholar]
  41. Karanti A, Kardell M, Joas E, Runeson B, Pålsson E, & Landén M (2020). Characteristics of bipolar I and II disorder: a study of 8766 individuals. Bipolar disorders, 22(4), 392–400. [DOI] [PubMed] [Google Scholar]
  42. Keren H, O’Callaghan G, Vidal-Ribas P, Buzzell GA, Brotman MA, Leibenluft E, . . . Wolke S (2018). Reward processing in depression: a conceptual and meta-analytic review across fMRI and EEG studies. American Journal of Psychiatry, 175(11), 1111–1120. [DOI] [PMC free article] [PubMed] [Google Scholar]
  43. Klein DF (1974). Endogenomorphic depression: a conceptual and terminological revision. Archives of general psychiatry, 31(4), 447–454. [DOI] [PubMed] [Google Scholar]
  44. Kleindienst N, Engel R, & Greil W (2005). Which clinical factors predict response to prophylactic lithium? A systematic review for bipolar disorders. Bipolar Disorders, 7(5), 404–417. doi: 10.1111/j.1399-5618.2005.00244.x [DOI] [PubMed] [Google Scholar]
  45. Kumar P, Goer F, Murray L, Dillon DG, Beltzer ML, Cohen AL, . . . Pizzagalli DA (2018). Impaired reward prediction error encoding and striatal-midbrain connectivity in depression. Neuropsychopharmacology, 43(7), 1581. [DOI] [PMC free article] [PubMed] [Google Scholar]
  46. Kumar P, Waiter G, Ahearn T, Milders M, Reid I, & Steele J (2008). Abnormal temporal difference reward-learning signals in major depression. Brain, 131(8), 2084–2093. [DOI] [PubMed] [Google Scholar]
  47. Lewandowski KE, Whitton AE, Pizzagalli DA, Norris LA, Ongur D, & Hall M-H (2016). Reward learning, neurocognition, social cognition, and symptomatology in psychosis. Frontiers in Psychiatry, 7, a100. doi: 10.3389/fpsyt.2016.00100 [DOI] [PMC free article] [PubMed] [Google Scholar]
  48. Lewis AJ (1934). Melancholia: a clinical survey of depressive states. Journal of Mental Science, 80(329), 277–378. [Google Scholar]
  49. Lewis WB (1889). A text-book of mental diseases: with special reference to the pathological aspects of insanity: Griffin. [Google Scholar]
  50. Lin Y, Maihofer AX, Stapp E, Ritchey M, Alliey-Rodriguez N, Anand A, . . . Bhattacharjee A (2021). Clinical predictors of non-response to lithium treatment in the Pharmacogenomics of Bipolar Disorder (PGBD) study. Bipolar Disorders. [DOI] [PubMed] [Google Scholar]
  51. Linke J, King AV, Rietschel M, Strohmaier J, Hennerici M, Gass A, . . . Wessa M (2012). Increased medial orbitofrontal and amygdala activation: evidence for a systems-level endophenotype of bipolar I disorder. American Journal of Psychiatry, 169(3), 316–325. [DOI] [PubMed] [Google Scholar]
  52. Mason L, O’Sullivan N, Montaldi D, Bentall RP, & El-Deredy W (2014). Decision-making and trait impulsivity in bipolar disorder are associated with reduced prefrontal regulation of striatal reward valuation. Brain, 137(8), 2346–2355. [DOI] [PMC free article] [PubMed] [Google Scholar]
  53. Mazza M, Squillacioti MR, Pecora RD, Janiri L, & Bria P (2009). Effect of aripiprazole on self-reported anhedonia in bipolar depressed patients. Psychiatry research, 165(1–2), 193–196. [DOI] [PubMed] [Google Scholar]
  54. McMakin DL, Olino TM, Porta G, Dietz LJ, Emslie G, Clarke G, . . . Birmaher B (2012). Anhedonia predicts poorer recovery among youth with selective serotonin reuptake inhibitor treatment–resistant depression. Journal of the American Academy of Child & Adolescent Psychiatry, 51(4), 404–411. [DOI] [PMC free article] [PubMed] [Google Scholar]
  55. Mitchell PB (2001). The clinical features of bipolar depression: a comparison with matched major depressive disorder patients. The Journal of clinical psychiatry, 62(3), 212–216. [PubMed] [Google Scholar]
  56. Morgan JK, Olino TM, McMakin DL, Ryan ND, & Forbes EE (2013). Neural response to reward as a predictor of increases in depressive symptoms in adolescence. Neurobiology of disease, 52, 66–74. [DOI] [PMC free article] [PubMed] [Google Scholar]
  57. Mula M, Pini S, Calugi S, Preve M, Masini M, Giovannini I, . . . Cassano GB (2010). Distinguishing affective depersonalization from anhedonia in major depression and bipolar disorder. Comprehensive Psychiatry, 51(2), 187–192. [DOI] [PubMed] [Google Scholar]
  58. Nusslock R, Almeida JR, Forbes EE, Versace A, Frank E, LaBarbara EJ, . . . Phillips ML (2012). Waiting to win: elevated striatal and orbitofrontal cortical activity during reward anticipation in euthymic bipolar disorder adults. Bipolar disorders, 14(3), 249–260. [DOI] [PMC free article] [PubMed] [Google Scholar]
  59. O’Sullivan N, Szczepanowski R, El-Deredy W, Mason L, & Bentall RP (2011). fMRI evidence of a relationship between hypomania and both increased goal-sensitivity and positive outcome-expectancy bias. Neuropsychologia, 49(10), 2825–2835. [DOI] [PubMed] [Google Scholar]
  60. O’Callaghan G, & Stringaris A (2019). Reward processing in adolescent depression across neuroimaging modalities. Zeitschrift für Kinder-und Jugendpsychiatrie und Psychotherapie. [DOI] [PMC free article] [PubMed] [Google Scholar]
  61. Olino TM, McMakin DL, Morgan JK, Silk JS, Birmaher B, Axelson DA, . . . Forbes EE (2014). Reduced reward anticipation in youth at high-risk for unipolar depression: a preliminary study. Developmental cognitive neuroscience, 8, 55–64. [DOI] [PMC free article] [PubMed] [Google Scholar]
  62. Pan PM, Sato JR, Salum GA, Rohde LA, Gadelha A, Zugman A, . . . Miguel EC (2017). Ventral striatum functional connectivity as a predictor of adolescent depressive disorder in a longitudinal community-based sample. American Journal of Psychiatry, 174(11), 1112–1119. [DOI] [PMC free article] [PubMed] [Google Scholar]
  63. Perlis RH, Brown E, Baker RW, & Nierenberg AA (2006). Clinical features of bipolar depression versus major depressive disorder in large multicenter trials. American Journal of Psychiatry, 163(2), 225–231. [DOI] [PubMed] [Google Scholar]
  64. Perlis RH, Miyahara S, Marangell LB, Wisniewski SR, Ostacher M, DelBello MP, . . . Investigators S-B (2004). Long-term implications of early onset in bipolar disorder: data from the first 1000 participants in the systematic treatment enhancement program for bipolar disorder (STEP-BD). Biological psychiatry, 55(9), 875–881. [DOI] [PubMed] [Google Scholar]
  65. Pizzagalli DA, Goetz E, Ostacher M, Iosifescu DV, & Perlis RH (2008). Euthymic patients with bipolar disorder show decreased reward learning in a probabilistic reward task. Biological psychiatry, 64(2), 162–168. [DOI] [PMC free article] [PubMed] [Google Scholar]
  66. Redlich R, Dohm K, Grotegerd D, Opel N, Zwitserlood P, Heindel W, . . . Dannlowski U (2015). Reward processing in unipolar and bipolar depression: a functional MRI study. Neuropsychopharmacology, 40(11), 2623. [DOI] [PMC free article] [PubMed] [Google Scholar]
  67. Ribot T-A (1896). La psychologie des sentiments [The Psychology of Feelings]. Paris: Felix Alcan. [Google Scholar]
  68. Rothkirch M, Tonn J, Köhler S, & Sterzer P (2017). Neural mechanisms of reinforcement learning in unmedicated patients with major depressive disorder. Brain, 140(4), 1147–1157. [DOI] [PubMed] [Google Scholar]
  69. Rupprechter S, Romaniuk L, Series P, Hirose Y, Hawkins E, Sandu A-L, . . . Harris MA (2020). Blunted medial prefrontal cortico-limbic reward-related effective connectivity and depression. Brain, 143(6), 1946–1956. [DOI] [PMC free article] [PubMed] [Google Scholar]
  70. Russo SJ, & Nestler EJ (2013). The brain reward circuitry in mood disorders. Nature Reviews Neuroscience, 14(9), 609–625. [DOI] [PMC free article] [PubMed] [Google Scholar]
  71. Rutledge RB, Moutoussis M, Smittenaar P, Zeidman P, Taylor T, Hrynkiewicz L, . . . Ousdal OT (2017). Association of neural and emotional impacts of reward prediction errors with major depression. JAMA psychiatry, 74(8), 790–797. [DOI] [PMC free article] [PubMed] [Google Scholar]
  72. Sagud M, Tudor L, Šimunić L, Jezernik D, Madžarac Z, Jakšić N, . . . Stefanović I (2020). Physical and social anhedonia are associated with suicidality in major depression, but not in schizophrenia. Suicide and Life-Threatening Behavior. [DOI] [PubMed] [Google Scholar]
  73. Satterthwaite TD, Kable JW, Vandekar L, Katchmar N, Bassett DS, Baldassano CF, . . . Gur RC (2015). Common and dissociable dysfunction of the reward system in bipolar and unipolar depression. Neuropsychopharmacology, 40(9), 2258. [DOI] [PMC free article] [PubMed] [Google Scholar]
  74. Schwarz K, Moessnang C, Schweiger JI, Baumeister S, Plichta MM, Brandeis D, . . . Walter H (2020). Transdiagnostic prediction of affective, cognitive, and social function through brain reward anticipation in schizophrenia, bipolar disorder, major depression, and autism spectrum diagnoses. Schizophrenia bulletin, 46(3), 592–602. [DOI] [PMC free article] [PubMed] [Google Scholar]
  75. Souery D, Zaninotto L, Calati R, Linotte S, Mendlewicz J, Sentissi O, & Serretti A (2012). Depression across mood disorders: review and analysis in a clinical sample. Comprehensive psychiatry, 53(1), 24–38. [DOI] [PubMed] [Google Scholar]
  76. Spijker J, Bijl R, De Graaf R, & Nolen W (2001). Determinants of poor 1-year outcome of DSM-III-R major depression in the general population: results of the Netherlands Mental Health Survey and Incidence Study (NEMESIS). Acta Psychiatr Scand, 103(2), 122–130. doi: 10.1034/j.1600-0447.2001.103002122.x [DOI] [PubMed] [Google Scholar]
  77. Stringaris A, Vidal-Ribas Belil P, Artiges E, Lemaitre H, Gollier-Briant F, Wolke S, . . . Struve M (2015). The brain’s response to reward anticipation and depression in adolescence: dimensionality, specificity, and longitudinal predictions in a community-based sample. American Journal of Psychiatry, 172(12), 1215–1223. [DOI] [PMC free article] [PubMed] [Google Scholar]
  78. Takamura M, Okamoto Y, Okada G, Toki S, Yamamoto T, Ichikawa N, . . . Fujii Y (2017). Patients with major depressive disorder exhibit reduced reward size coding in the striatum. Progress in neuro-psychopharmacology and biological psychiatry, 79, 317–323. [DOI] [PubMed] [Google Scholar]
  79. Ubl B, Kuehner C, Kirsch P, Ruttorf M, Diener C, & Flor H (2015). Altered neural reward and loss processing and prediction error signalling in depression. Social cognitive and affective neuroscience, 10(8), 1102–1112. [DOI] [PMC free article] [PubMed] [Google Scholar]
  80. Uher R, Perlis R, Henigsberg N, Zobel A, Rietschel M, Mors O, . . . Bajs M (2012). Depression symptom dimensions as predictors of antidepressant treatment outcome: replicable evidence for interest-activity symptoms. Psychological Medicine, 42(5), 967–980. [DOI] [PMC free article] [PubMed] [Google Scholar]
  81. Vrieze E, Pizzagalli DA, Demyttenaere K, Hompes T, Sienaert P, de Boer P, . . . Claes S (2013). Reduced reward learning predicts outcome in major depressive disorder. Biological Psychiatry, 73(7), 639–645. [DOI] [PMC free article] [PubMed] [Google Scholar]
  82. Walsh E, Carl H, Eisenlohr-Moul T, Minkel J, Crowther A, Moore T, . . . Smoski MJ (2017). Attenuation of frontostriatal connectivity during reward processing predicts response to psychotherapy in major depressive disorder. Neuropsychopharmacology, 42(4), 831. [DOI] [PMC free article] [PubMed] [Google Scholar]
  83. Watson R, Harvey K, McCabe C, & Reynolds S (2020). Understanding anhedonia: A qualitative study exploring loss of interest and pleasure in adolescent depression. European child & adolescent psychiatry, 29(4), 489–499. [DOI] [PMC free article] [PubMed] [Google Scholar]
  84. Webb CA, Auerbach RP, Bondy E, Stanton CH, Appleman L, & Pizzagalli DA (2021). Reward-related neural predictors and mechanisms of symptom change in cognitive behavioral therapy for depressed adolescent girls. Biological Psychiatry: Cognitive Neuroscience and Neuroimaging, 6(1), 39–49. [DOI] [PMC free article] [PubMed] [Google Scholar]
  85. Whitton AE, Kumar P, Treadway MT, Rutherford AV, Ironside ML, Foti D, . . . Pizzagalli DA (2021). Mapping Disease Course Across the Mood Disorder Spectrum Through a Research Domain Criteria Framework. Biological Psychiatry: Cognitive Neuroscience and Neuroimaging. [DOI] [PMC free article] [PubMed] [Google Scholar]
  86. Whitton AE, Reinen JM, Slifstein M, Ang Y-S, McGrath PJ, Iosifescu DV, . . . Schneier FR (2020). Baseline reward processing and ventrostriatal dopamine function are associated with pramipexole response in depression. Brain, 143(2), 701–710. doi: 10.1093/brain/awaa002 [DOI] [PMC free article] [PubMed] [Google Scholar]
  87. Young C, Chen T, Nusslock R, Keller J, Schatzberg A, & Menon V (2016). Anhedonia and general distress show dissociable ventromedial prefrontal cortex connectivity in major depressive disorder. Translational psychiatry, 6(5), e810–e810. [DOI] [PMC free article] [PubMed] [Google Scholar]
  88. Zhang B, Lin P, Shi H, Öngür D, Auerbach RP, Wang X, . . . Wang X (2016). Mapping anhedonia-specific dysfunction in a transdiagnostic approach: an ALE meta-analysis. Brain imaging and behavior, 10(3), 920–939. [DOI] [PMC free article] [PubMed] [Google Scholar]
  89. Zou YM, Ni K, Wang YY, Yu EQ, Lui SS, Zhou FC, . . . Cheung EF (2020). Effort–cost computation in a transdiagnostic psychiatric sample: Differences among patients with schizophrenia, bipolar disorder, and major depressive disorder. Psych Journal, 9(2), 210–222. doi: 10.1002/pchj.316 [DOI] [PubMed] [Google Scholar]

RESOURCES