Reduced reward anticipation in youth at high-risk for unipolar depression: a preliminary study.
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ABSTRACT:
SUBMITTER: Olino TM
PROVIDER: S-EPMC3960320 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Differentiating bipolar disorders (BD) from unipolar depression (UD) remains a major clinical challenge. The identification of neurobiological markers may help to differentiate these disorders, particularly during depressive episodes. This cross-sectional study, including 33 patients with UD, 33 patients with BD, and 34 healthy controls, is one of the first to directly compare UD and BD with respect to reward processing. A card-guessing paradigm was employed and brain activity associated with reward processing was investigated by means of fMRI. A 3 (group) × 2 (condition: reward>control, loss>control) ANOVA was conducted using the nucleus accumbens (NAcc) as ROI. Furthermore, a whole-brain approach was applied. A functional connectivity analysis was performed to characterize diagnosis-related alterations in the functional coupling between the NAcc and other brain areas. The ANOVA revealed higher activity for healthy controls (HCs) than for BD and UD in the NAcc during reward processing. Moreover, UD showed a higher functional connectivity between the NAcc and the VTA than HC. The patients groups could be differentiated in that BD showed a decreased activation, in the reward condition, of the NAcc, caudate nucleus, thalamus, putamen, insula, and prefrontal areas compared with UD. These results may help to refine the understanding of neural correlates of reward processing in both disorders, and to understand the neural underpinnings of anhedonia, a core symptom of depressive episodes.
| S-EPMC4569953 | biostudies-literature
Project description:Bipolar disorder is often misdiagnosed as major depressive disorder, which leads to inadequate treatment. Depressed individuals versus healthy control subjects, show increased expectation of negative outcomes. Due to increased impulsivity and risk for mania, however, depressed individuals with bipolar disorder may differ from those with major depressive disorder in neural mechanisms underlying anticipation processes. Graph theory methods for neuroimaging data analysis allow the identification of connectivity between multiple brain regions without prior model specification, and may help to identify neurobiological markers differentiating these disorders, thereby facilitating development of better therapeutic interventions. This study aimed to compare brain connectivity among regions involved in win/loss anticipation in depressed individuals with bipolar disorder (BDD) versus depressed individuals with major depressive disorder (MDD) versus healthy control subjects using graph theory methods. The study was conducted at the University of Pittsburgh Medical Center and included 31 BDD, 39 MDD, and 36 healthy control subjects. Participants were scanned while performing a number guessing reward task that included the periods of win and loss anticipation. We first identified the anticipatory network across all 106 participants by contrasting brain activation during all anticipation periods (win anticipation + loss anticipation) versus baseline, and win anticipation versus loss anticipation. Brain connectivity within the identified network was determined using the Independent Multiple sample Greedy Equivalence Search (IMaGES) and Linear non-Gaussian Orientation, Fixed Structure (LOFS) algorithms. Density of connections (the number of connections in the network), path length, and the global connectivity direction ('top-down' versus 'bottom-up') were compared across groups (BDD/MDD/healthy control subjects) and conditions (win/loss anticipation). These analyses showed that loss anticipation was characterized by denser top-down fronto-striatal and fronto-parietal connectivity in healthy control subjects, by bottom-up striatal-frontal connectivity in MDD, and by sparse connectivity lacking fronto-striatal connections in BDD. Win anticipation was characterized by dense connectivity of medial frontal with striatal and lateral frontal cortical regions in BDD, by sparser bottom-up striatum-medial frontal cortex connectivity in MDD, and by sparse connectivity in healthy control subjects. In summary, this is the first study to demonstrate that BDD and MDD with comparable levels of current depression differed from each other and healthy control subjects in density of connections, connectivity path length, and connectivity direction as a function of win or loss anticipation. These findings suggest that different neurobiological mechanisms may underlie aberrant anticipation processes in BDD and MDD, and that distinct therapeutic strategies may be required for these individuals to improve coping strategies during expectation of positive and negative outcomes.
| S-EPMC4995358 | biostudies-literature
Project description:Neuroimaging studies of mood disorders demonstrate abnormalities in brain regions implicated in reward processing. However, there is a paucity of research investigating how social rewards affect reward circuit activity in these disorders. Here, we evaluated the relationship of both diagnostic category and dimensional depression severity to reward system function in bipolar and unipolar depression. In total, 86 adults were included, including 24 patients with bipolar depression, 24 patients with unipolar depression, and 38 healthy comparison subjects. Participants completed a social reward task during 3T BOLD fMRI. On average, diagnostic groups did not differ in activation to social reward. However, greater depression severity significantly correlated with reduced bilateral ventral striatum activation to social reward in the bipolar depressed group, but not the unipolar depressed group. In addition, decreased left orbitofrontal cortical activation correlated with more severe symptoms in bipolar depression, but not unipolar depression. These differential dimensional effects resulted in a significant voxelwise group by depression severity interaction. Taken together, these results provide initial evidence that deficits in social reward processing are differentially related to depression severity in the two disorders.
| S-EPMC4992640 | biostudies-literature
Project description:Distinguishing bipolar disorder (BD) from major depressive disorder (MDD) is clinically challenging, especially during depressive episodes. While both groups are characterized by aberrant working memory and anticipatory processing, the role of these processes in discriminating BD from MDD remains unexplored. In this study, we examine how brain activation corresponding to anticipation of and performance on easy vs. difficult working memory tasks with emotional stimuli contributes to discrimination among BD, MDD, and healthy controls (HC). Depressed individuals with BD (n = 18), MDD (n = 23), and HC (n = 23) were scanned while performing a working memory task in which they had to first anticipate performance on 1-back (easy) or 2-back (difficult) tasks with happy, fearful, or neutral faces, and then, perform the task. Anticipation-related and task-related brain activation was measured in the whole brain using functional magnetic resonance imagining. We used an elastic-net regression for variable selection, and a random forest classifier for BD vs. MDD classification. The former selected the activation differences (1-back minus 2-back) in the lateral and medial prefrontal cortices (PFC) during task anticipation and performance on the working memory tasks with fearful and neutral faces as variables relevant for BD vs. MDD classification. BD vs. MDD were classified with 70.7% accuracy (p < 0.01) based on the neuroimaging measures alone, with 80.5% accuracy (p = 0.001) based on clinical measures alone, and with 85.4% accuracy (p < 0.001) based on clinical and neuroimaging measures together. These findings suggest that PFC activation during working memory task anticipation and performance may be an important biological marker distinguishing BD from MDD.
| S-EPMC7162920 | biostudies-literature
Project description: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.
| S-EPMC4613620 | biostudies-literature
Project description:Acute nicotine abstinence is associated with disruption of executive function and reward processes; however, the neurobiological basis of these effects has not been fully elucidated.The effects of nicotine abstinence on brain function during reward-based probabilistic decision making were preliminarily investigated by scanning adult smokers (n?=?13) following 24 h of smoking abstinence and in a smoking-satiated condition. During fMRI scanning, participants completed the wheel of fortune task (Ernst et al. in Neuropsychologia 42:1585-1597, 2004), a decision-making task with probabilistic monetary outcomes. Brain activation was modeled during selection of options, anticipation of outcomes, and outcome feedback.During choice selection, reaction times were slower, and there was greater neural activation in the postcentral gyrus, insula, and frontal and parietal cortices in the abstinent condition compared to the satiated condition. During reward anticipation, greater activation was observed in the frontal pole, insula, and paracingulate cortex in the abstinent condition compared to the satiated condition. Greater activation was also shown in the precentral gyrus and putamen in the satiated condition compared to the abstinent condition. During the outcome phase, rewards (compared to no rewards) resulted in significant activation in the paracingulate cortex in the satiated condition compared to the abstinent condition.The results of this preliminary study suggest that smoking withdrawal results in greater recruitment of insular, frontal, and parietal cortical areas during probabilistic decision making.
| S-EPMC4140396 | biostudies-literature
Project description:Background: Bipolar depression (BD) and unipolar depression (UD) are both characterized by depressive moods, which are difficult to distinguish in clinical practice. Human brain activity is time-varying and dynamic. Investigating dynamical pattern alterations of depressed brains can provide deep insights into the pathophysiological features of depression. This study aimed to explore similar and different abnormal dynamic patterns between BD and UD. Methods: Brain resting-state functional magnetic resonance imaging data were acquired from 36 patients with BD type I (BD-I), 38 patients with UD, and 42 healthy controls (HCs). Analysis of covariance was adopted to examine the differential pattern of the dynamical regional homogeneity (dReHo) temporal variability across 3 groups, with gender, age, and education level as covariates. Post-hoc analyses were employed to obtain the different dynamic characteristics between any 2 groups. We further applied the machine-learning methods to classify BD-I from UD by using the detected distinct dReHo pattern. Results: Compared with patients with UD, patients with BD-I demonstrated decreased dReHo variability in the right postcentral gyrus and right parahippocampal gyrus. By using the dReHo variability pattern of these two regions as features, we achieved the 91.89% accuracy and 0.92 area under curve in classifying BD-I from UD. Relative to HCs, patients with UD showed increased dReHo variability in the right postcentral gyrus, while there were no dReHo variability differences in patients with BD-I. Conclusions: The results of this study mainly report the differential dynamic pattern of the regional activity between BD-I and UD, particular in the mesolimbic system, and show its promising potential in assisting the diagnosis of these two depression groups.
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Project description:Since the first neurodevelopmental models that sought to explain the influx of risky behaviors during adolescence were proposed, there have been a number of revisions, variations and criticisms. Despite providing a strong multi-disciplinary heuristic to explain the development of risk behavior, extant models have not yet reliably isolated neural systems that underlie risk behaviors in adolescence. To address this gap, we screened 2017 adolescents from an ongoing longitudinal study that assessed 15-health risk behaviors, targeting 104 adolescents (Age Range: 17-to-21.4), characterized as high-or-average/low risk-taking. Participants completed the Monetary Incentive Delay (MID) fMRI task, examining reward anticipation to "big win" versus "neutral". We examined neural response variation associated with both baseline and longitudinal (multi-wave) risk classifications. Analyses included examination of a priori regions of interest (ROIs); and exploratory non-parametric, whole-brain analyses. Hypothesis-driven ROI analysis revealed no significant differences between high- and average/low-risk profiles using either baseline or multi-wave classification. Results of whole-brain analyses differed according to whether risk assessment was based on baseline or multi-wave data. Despite significant mean-level task activation, these results do not generalize prior neural substrates implicated in reward anticipation and adolescent risk-taking. Further, these data indicate that whole-brain differences may depend on how risk-behavior profiles are defined.
| S-EPMC7262007 | biostudies-literature
Project description:Aberrant sensitivity of incentive neurocircuitry to nondrug rewards has been suggested as either a risk factor for or consequence of drug addiction. Using functional magnetic resonance imaging, we tested whether alcohol-dependent patients (ADP: n = 29) showed altered recruitment of ventral striatal (VS) incentive neurocircuitry compared to controls (n = 23) by: (1) cues to respond for monetary rewards, (2) post-response anticipation of rewards, or (3) delivery of rewards. Using an instrumental task with two-stage presentation of reward-predictive information, subjects saw cues signaling opportunities to win $0, $1, or $10 for responding to a target. Following this response, subjects were notified whether their success would be indicated by a lexical notification (“Hit?”) or by delivery of a monetary reward (“Win?”). After a variable interval, subjects then viewed the trial outcome. We found no significant group differences in voxelwise activation by task contrasts, or in signal change extracted from VS. Both ADP and controls showed significant VS and other limbic recruitment by pre-response reward anticipation. In addition, controls also showed VS recruitment by post-response reward-anticipation, and ADP had appreciable subthreshold VS activation. Both groups also showed similar mesolimbic responses to reward deliveries. Across all subjects, a questionnaire measure of “hot” impulsivity correlated with VS recruitment by post-response anticipation of low rewards and with VS recruitment by delivery of low rewards. These findings indicate that incentive-motivational processing of nondrug rewards is substantially maintained in recovering alcoholics, and that reward-elicited VS recruitment correlates more with individual differences in trait impulsivity irrespective of addiction.
| S-EPMC3342463 | biostudies-literature
Project description:Alcohol use disorder is characterised by disrupted reward learning, underpinned by dysfunctional cortico-striatal reward pathways, although relatively little is known about the biology of reward processing in populations who engage in risky alcohol use. Cues that trigger reward anticipation can be categorized according to their learnt valence (i.e., positive vs. negative outcomes) and motivational salience (i.e., incentive vs. neutral cues). Separating EEG signals associated with these dimensions is challenging because of their inherent collinearity, but the recent application of machine learning methods to single EEG trials affords a solution. Here, the Alcohol Use Disorders Identification Test (AUDIT) was used to quantify risky alcohol use, with participants split into high alcohol (HA) (n = 22, mean AUDIT score: 13.82) and low alcohol (LA) (n = 22, mean AUDIT score: 5.77) groups. We applied machine learning multivariate single-trial classification to the electroencephalography (EEG) data collected during reward anticipation. The LA group demonstrated significant valence discrimination in the early stages of reward anticipation within the cue-P3 time window (400-550 ms), whereas the HA group was insensitive to valence within this time window. Notably, the LA, but not the HA group demonstrated a relationship between single-trial variability in the early valence component and reaction times for gain and loss trials. This study evidences disrupted hypoactive valence sensitivity in the HA group, revealing potential neurophysiological markers for risky drinking behaviours which place individuals at-risk of adverse health events.
| S-EPMC9286798 | biostudies-literature