Modulation of ventromedial orbitofrontal cortical glutamatergic activity affects the explore-exploit balance and influences value-based decision-making.

The balance between exploration and exploitation is essential for decision-making. The present study investigated the role of ventromedial orbitofrontal cortex (vmOFC) glutamate neurons in mediating value-based decision-making by first using optogenetics to manipulate vmOFC glutamate activity in rats during a probabilistic reversal learning (PRL) task. Rats that received vmOFC activation during informative feedback completed fewer reversals and exhibited reduced reward sensitivity relative to rats. Analysis with a Q-learning computational model revealed that increased vmOFC activity did not affect the learning rate but instead promoted maladaptive exploration. By contrast, vmOFC inhibition increased the number of completed reversals and increased exploitative behavior. In a separate group of animals, calcium activity of vmOFC glutamate neurons was recorded using fiber photometry. Complementing our results above, we found that suppression of vmOFC activity during the latter part of rewarded trials was associated with improved PRL performance, greater win-stay responding and selecting the correct choice on the next trial. These data demonstrate that excessive vmOFC activity during reward feedback disrupted value-based decision-making by increasing the maladaptive exploration of lower-valued options. Our findings support the premise that pharmacological interventions that normalize aberrant vmOFC glutamate activity during reward feedback processing may attenuate deficits in value-based decision-making.

Resting state connectivity predictors of symptom change during gaze-contingent music reward therapy of social anxiety disorder.

BACKGROUND: Social anxiety disorder (SAD) is common, first-line treatments are often only partially effective, and reliable predictors of treatment response are lacking. Here, we assessed resting state functional connectivity (rsFC) at pre-treatment and during early treatment as a potential predictor of response to a novel attention bias modification procedure, gaze-contingent music reward therapy (GC-MRT). METHODS: Thirty-two adults with SAD were treated with GC-MRT. rsFC was assessed with multi-voxel pattern analysis of fMRI at pre-treatment and after 2-3 weeks. For comparison, 20 healthy control (HC) participants without treatment were assessed twice for rsFC over the same time period. All SAD participants underwent clinical evaluation at pre-treatment, early-treatment (week 2-3), and post-treatment. RESULTS: SAD and depressive symptoms improved significantly from pre-treatment to post-treatment. After 2-3 weeks of treatment, decreased connectivity between the executive control network (ECN) and salience network (SN), and increased connectivity within the ECN predicted improvement in SAD and depressive symptoms at week 8. Increased connectivity between the ECN and default mode network (DMN) predicted greater improvement in SAD but not depressive symptoms at week 8. Connectivity within the DMN decreased significantly after 2-3 weeks of treatment in the SAD group, while no changes were found in HC over the same time interval. CONCLUSION: We identified early changes in rsFC during a course of GC-MRT for SAD that predicted symptom change. Connectivity changes within the ECN, ECN-DMN, and ECN-SN may be related to mechanisms underlying the clinical effects of GC-MRT and warrant further study in controlled trials.

A multi-pronged investigation of option generation using depression, PET and modafinil.

Option generation is a critical process in decision making, but previous studies have largely focused on choices between options given by a researcher. Consequently, how we self-generate options for behaviour remain poorly understood. Here, we investigated option generation in major depressive disorder and how dopamine might modulate this process, as well as the effects of modafinil (a putative cognitive enhancer) on option generation in healthy individuals. We first compared differences in self-generated options between healthy non-depressed adults [n = 44, age = 26.3 years (SD 5.9)] and patients with major depressive disorder [n = 54, age = 24.8 years (SD 7.4)]. In the second study, a subset of depressed individuals [n = 22, age = 25.6 years (SD 7.8)] underwent PET scans with 11C-raclopride to examine the relationships between dopamine D2/D3 receptor availability and individual differences in option generation. Finally, a randomized, double-blind, placebo-controlled, three-way crossover study of modafinil (100 mg and 200 mg), was conducted in an independent sample of healthy people [n = 19, age = 23.2 years (SD 4.8)] to compare option generation under different doses of this drug. The first study revealed that patients with major depressive disorder produced significantly fewer options [t(96) = 2.68, P = 0.009, Cohen's d = 0.54], albeit with greater uniqueness [t(96) = -2.54, P = 0.01, Cohen's d = 0.52], on the option generation task compared to healthy controls. In the second study, we found that 11C-raclopride binding potential in the putamen was negatively correlated with fluency (r = -0.69, P = 0.001) but positively associated with uniqueness (r = 0.59, P = 0.007). Hence, depressed individuals with higher densities of unoccupied putamen D2/D3 receptors in the putamen generated fewer but more unique options, whereas patients with lower D2/D3 receptor availability were likely to produce a larger number of similar options. Finally, healthy participants were less unique [F(2,36) = 3.32, P = 0.048, partial η2 = 0.16] and diverse [F(2,36) = 4.31, P = 0.021, partial η2 = 0.19] after taking 200 mg versus 100 mg and 0 mg of modafinil, while fluency increased linearly with dosage at a trend level [F(1,18) = 4.11, P = 0.058, partial η2 = 0.19]. Our results show, for the first time, that option generation is affected in clinical depression and that dopaminergic activity in the putamen of patients with major depressive disorder may play a key role in the self-generation of options. Modafinil was also found to influence option generation in healthy people by reducing the creativity of options produced.

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.

Altered coordination between frontal delta and parietal alpha networks underlies anhedonia and depressive rumination in major depressive disorder.

BACKGROUND: A hyperactive default mode network (DMN) has been observed in people with major depressive disorder (MDD), and weak DMN suppression has been linked to depressive symptoms. However, whether dysregulation of the DMN contributes to blunted positive emotional experience in people with MDD is unclear. METHODS: We recorded 128-channel electroencephalograms (EEGs) from 24 participants with MDD and 31 healthy controls in a resting state (RS) and an emotion-induction state (ES), in which participants engaged with emotionally positive pictures. We combined Granger causality analysis and data-driven decomposition to extract latent brain networks shared among states and groups, and we further evaluated their interactions across individuals. RESULTS: We extracted 2 subnetworks. Subnetwork 1 represented a delta (δ)-band (1~4 Hz) frontal network that was activated more in the ES than the RS (i.e., task-positive). Subnetwork 2 represented an alpha (α)-band (8~13 Hz) parietal network that was suppressed more in the ES than the RS (i.e., task-negative). These subnetworks were anticorrelated in both the healthy control and MDD groups, but with different sensitivities: for participants with MDD to achieve the same level of task-positive (subnetwork 1) activation as healthy controls, more suppression of task-negative (subnetwork 2) activation was necessary. Furthermore, the anticorrelation strength in participants with MDD correlated with the severity of 2 core MDD symptoms: anhedonia and rumination. LIMITATIONS: The sample size was small. CONCLUSION: Our findings revealed altered coordination between 2 functional networks in MDD and suggest that weak suppression of the task-negative α-band parietal network contributes to blunted positive emotional responses in adults with depression. The subnetworks identified here could be used for diagnosis or targeted for treatment in the future.

Stress-induced alterations in HPA-axis reactivity and mesolimbic reward activation in individuals with emotional eating.

BACKGROUND: Emotional eating has emerged as a contributing factor to overeating, potentially leading to obesity or disordered eating behaviors. However, the underlying biological mechanisms related to emotional eating remain unclear. The present study examined emotional, hormonal, and neural alterations elicited by an acute laboratory stressor in individuals with and without emotional eating. METHODS: Emotional (n = 13) and non-emotional eaters (n = 15) completed two main study visits, one week apart: one visit included a Stress version and the other a No-stress version of the Maastricht Acute Stress Task (MAST). Immediately pre- and post-MAST, blood was drawn for serum cortisol and participants rated their anxiety level. After the MAST, participants completed a Food Incentive Delay (FID) task during functional magnetic resonance imaging (fMRI), followed by an ad libitum snack period. RESULTS: Emotional eaters exhibited elevated anxiety (p = 0.037) and cortisol (p = 0.001) in response to the Stress MAST. There were no changes in anxiety or cortisol among non-emotional eaters in response to the Stress MAST or in either group in response to the No-stress MAST. In response to the Stress MAST, emotional eaters exhibited reduced activation during anticipation of food reward in mesolimbic reward regions (caudate: p = 0.014, nucleus accumbens: p = 0.022, putamen: p = 0.013), compared to non-emotional eaters. Groups did not differ in snack consumption. CONCLUSIONS: These data indicate disrupted neuroendocrine and neural responsivity to psychosocial stress amongst otherwise-healthy emotional eaters, who demonstrated hyperactive HPA-axis response coupled with hypoactivation in reward circuitry. Differential responsivity to stress may represent a risk factor in the development of maladaptive eating behaviors.

Functional connectomics of affective and psychotic pathology.

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.

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.

Fear Extinction Recall Modulates Human Frontomedial Theta and Amygdala Activity.

Human functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) studies, as well as animal studies, indicate that the amygdala and frontomedial brain regions are critically involved in conditioned fear and that frontomedial oscillations in the theta range (4-8 Hz) may support communication between these brain regions. However, few studies have used a multimodal approach to probe interactions among these key regions in humans. Here, our goal was to bridge the gap between prior human fMRI, EEG, and animal findings. Using simultaneous EEG-fMRI recordings 24 h after fear conditioning and extinction, conditioned stimuli presented (CS+E, CS-E) and not presented during extinction (CS+N, CS-N) were compared to identify effects specific to extinction versus fear recall. Differential (CS+ vs. CS-) electrodermal, frontomedial theta (EEG) and amygdala responses (fMRI) were reduced for extinguished versus nonextinguished stimuli. Importantly, effects on theta power covaried with effects on amygdala activation. Fear and extinction recall as indicated by theta explained 60% of the variance for the analogous effect in the right amygdala. Our findings show for the first time the interplay of amygdala and frontomedial theta activity during fear and extinction recall in humans and provide insight into neural circuits consistently linked with top-down amygdala modulation in rodents.

Personalized prediction of antidepressant v. placebo response: evidence from the EMBARC study.

BACKGROUND: Major depressive disorder (MDD) is a highly heterogeneous condition in terms of symptom presentation and, likely, underlying pathophysiology. Accordingly, it is possible that only certain individuals with MDD are well-suited to antidepressants. A potentially fruitful approach to parsing this heterogeneity is to focus on promising endophenotypes of depression, such as neuroticism, anhedonia, and cognitive control deficits. METHODS: Within an 8-week multisite trial of sertraline v. placebo for depressed adults (n = 216), we examined whether the combination of machine learning with a Personalized Advantage Index (PAI) can generate individualized treatment recommendations on the basis of endophenotype profiles coupled with clinical and demographic characteristics. RESULTS: Five pre-treatment variables moderated treatment response. Higher depression severity and neuroticism, older age, less impairment in cognitive control, and being employed were each associated with better outcomes to sertraline than placebo. Across 1000 iterations of a 10-fold cross-validation, the PAI model predicted that 31% of the sample would exhibit a clinically meaningful advantage [post-treatment Hamilton Rating Scale for Depression (HRSD) difference ⩾3] with sertraline relative to placebo. Although there were no overall outcome differences between treatment groups (d = 0.15), those identified as optimally suited to sertraline at pre-treatment had better week 8 HRSD scores if randomized to sertraline (10.7) than placebo (14.7) (d = 0.58). CONCLUSIONS: A subset of MDD patients optimally suited to sertraline can be identified on the basis of pre-treatment characteristics. This model must be tested prospectively before it can be used to inform treatment selection. However, findings demonstrate the potential to improve individual outcomes through algorithm-guided treatment recommendations.

A Novel Strategy to Identify Placebo Responders: Prediction Index of Clinical and Biological Markers in the EMBARC Trial.

BACKGROUND: One in three clinical trial patients with major depressive disorder report symptomatic improvement with placebo. Strategies to mitigate the effect of placebo responses have focused on modifying study design with variable success. Identifying and excluding or controlling for individuals with a high likelihood of responding to placebo may improve clinical trial efficiency and avoid unnecessary medication trials. METHODS: Participants included those assigned to the placebo arm (n = 141) of the Establishing Moderators and Biosignatures for Antidepressant Response in Clinical Care (EMBARC) trial. The elastic net was used to evaluate 283 baseline clinical, behavioral, imaging, and electrophysiological variables to identify the most robust yet parsimonious features that predicted depression severity at the end of the double-blind 8-week trial. Variables retained in at least 50% of the 100 imputed data sets were used in a Bayesian multiple linear regression model to simultaneously predict the probabilities of response and remission. RESULTS: Lower baseline depression severity, younger age, absence of melancholic features or history of physical abuse, less anxious arousal, less anhedonia, less neuroticism, and higher average theta current density in the rostral anterior cingulate predicted a higher likelihood of improvement with placebo. The Bayesian model predicted remission and response with an actionable degree of accuracy (both AUC > 0.73). An interactive calculator was developed predicting the likelihood of placebo response at the individual level. CONCLUSION: Easy-to-measure clinical, behavioral, and electrophysiological assessments can be used to identify placebo responders with a high degree of accuracy. Development of this calculator based on these findings can be used to identify potential placebo responders.

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.

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.

Postnatal Phencyclidine-Induced Deficits in Decision Making Are Ameliorated by Optogenetic Inhibition of Ventromedial Orbitofrontal Cortical Glutamate Neurons.

Background: The orbitofrontal cortex (OFC) is essential for decision making, and functional disruptions within the OFC are evident in schizophrenia. Postnatal phencyclidine (PCP) administration in rats is a neurodevelopmental manipulation that induces schizophrenia-relevant cognitive impairments. We aimed to determine whether manipulating OFC glutamate cell activity could ameliorate postnatal PCP-induced deficits in decision making. Methods: Male and female Wistar rats (n = 110) were administered saline or PCP on postnatal days 7, 9, and 11. In adulthood, we expressed YFP (yellow fluorescent protein) (control), ChR2 (channelrhodopsin-2) (activation), or eNpHR 3.0 (enhanced halorhodopsin) (inhibition) in glutamate neurons within the ventromedial OFC (vmOFC). Rats were tested on the probabilistic reversal learning task once daily for 20 days while we manipulated the activity of vmOFC glutamate cells. Behavioral performance was analyzed using a Q-learning computational model of reinforcement learning. Results: Compared with saline-treated rats expressing YFP, PCP-treated rats expressing YFP completed fewer reversals, made fewer win-stay responses, and had lower learning rates. We induced similar performance impairments in saline-treated rats by activating vmOFC glutamate cells (ChR2). Strikingly, PCP-induced performance deficits were ameliorated when the activity of vmOFC glutamate cells was inhibited (halorhodopsin). Conclusions: Postnatal PCP-induced deficits in decision making are associated with hyperactivity of vmOFC glutamate cells. Thus, normalizing vmOFC activity may represent a potential therapeutic target for decision-making deficits in patients with schizophrenia.

Cognitive Signatures of Depressive and Anhedonic Symptoms and Affective States Using Computational Modeling and Neurocognitive Testing.

BACKGROUND: Deeper phenotyping may improve our understanding of depression. Because depression is heterogeneous, extracting cognitive signatures associated with severity of depressive symptoms, anhedonia, and affective states is a promising approach. METHODS: Sequential sampling models decomposed behavior from an adaptive approach-avoidance conflict task into computational parameters quantifying latent cognitive signatures. Fifty unselected participants completed clinical scales and the approach-avoidance conflict task by either approaching or avoiding trials offering monetary rewards and electric shocks. RESULTS: Decision dynamics were best captured by a sequential sampling model with linear collapsing boundaries varying by net offer values, and with drift rates varying by trial-specific reward and aversion, reflecting net evidence accumulation toward approach or avoidance. Unlike conventional behavioral measures, these computational parameters revealed distinct associations with self-reported symptoms. Specifically, passive avoidance tendencies, indexed by starting point biases, were associated with greater severity of depressive symptoms (R = 0.34, p = .019) and anhedonia (R = 0.49, p = .001). Depressive symptoms were also associated with slower encoding and response execution, indexed by nondecision time (R = 0.37, p = .011). Higher reward sensitivity for offers with negative net values, indexed by drift rates, was linked to more sadness (R = 0.29, p = .042) and lower positive affect (R = -0.33, p = .022). Conversely, higher aversion sensitivity was associated with more tension (R = 0.33, p = .025). Finally, less cautious response patterns, indexed by boundary separation, were linked to more negative affect (R = -0.40, p = .005). CONCLUSIONS: We demonstrated the utility of multidimensional computational phenotyping, which could be applied to clinical samples to improve characterization and treatment selection.

Using Drift Diffusion and RL Models to Disentangle Effects of Depression On Decision-Making vs. Learning in the Probabilistic Reward Task.

The Probabilistic Reward Task (PRT) is widely used to investigate the impact of Major Depressive Disorder (MDD) on reinforcement learning (RL), and recent studies have used it to provide insight into decision-making mechanisms affected by MDD. The current project used PRT data from unmedicated, treatment-seeking adults with MDD to extend these efforts by: (1) providing a more detailed analysis of standard PRT metrics-response bias and discriminability-to better understand how the task is performed; (2) analyzing the data with two computational models and providing psychometric analyses of both; and (3) determining whether response bias, discriminability, or model parameters predicted responses to treatment with placebo or the atypical antidepressant bupropion. Analysis of standard metrics replicated recent work by demonstrating a dependency between response bias and response time (RT), and by showing that reward totals in the PRT are governed by discriminability. Behavior was well-captured by the Hierarchical Drift Diffusion Model (HDDM), which models decision-making processes; the HDDM showed excellent internal consistency and acceptable retest reliability. A separate "belief" model reproduced the evolution of response bias over time better than the HDDM, but its psychometric properties were weaker. Finally, the predictive utility of the PRT was limited by small samples; nevertheless, depressed adults who responded to bupropion showed larger pre-treatment starting point biases in the HDDM than non-responders, indicating greater sensitivity to the PRT's asymmetric reinforcement contingencies. Together, these findings enhance our understanding of reward and decision-making mechanisms that are implicated in MDD and probed by the PRT.

Enhanced decision-making in nicotine dependent individuals who abstain: A computational analysis using Hierarchical Drift Diffusion Modeling.

BACKGROUND: Variability in decision-making capacity and reward responsiveness may underlie differences in the ability to abstain from smoking. Computational modeling of choice behavior, as with the Hierarchical Drift Diffusion Model (HDDM), can help dissociate reward responsiveness from underlying components of decision-making. Here we used the HDDM to identify which decision-making or reward-related parameters, extracted from data acquired in a reward processing task, contributed to the ability of people who smoke that are not seeking treatment to abstain from cigarettes during a laboratory task. METHODS: 80 adults who smoke cigarettes completed the Probabilistic Reward Task (PRT) - a signal detection task with a differential reinforcement schedule - following smoking as usual, and the Relapse Analogue Task (RAT) - a task in which participants could earn money for delaying smoking up to 50min - after a period of overnight abstinence. Two cohorts were defined by the RAT; those who waited either 0-min (n=36) or the full 50-min (n=44) before smoking. RESULTS: PRT signal detection metrics indicated all subjects learned the task contingencies, with no differences in response bias or discriminability between the two groups. However, HDDM analyses indicated faster drift rates in 50-min vs. 0-min waiters. CONCLUSIONS: Relative to those who did not abstain, computational modeling indicated that people who abstained from smoking for 50min showed faster evidence accumulation during reward-based decision-making. These results highlight the importance of decision-making mechanisms to smoking abstinence, and suggest that focusing on the evidence accumulation process may yield new targets for treatment.

Reinforcement learning deficits exhibited by postnatal PCP-treated rats enable deep neural network classification.

The ability to appropriately update the value of a given action is a critical component of flexible decision making. Several psychiatric disorders, including schizophrenia, are associated with impairments in flexible decision making that can be evaluated using the probabilistic reversal learning (PRL) task. The PRL task has been reverse-translated for use in rodents. Disrupting glutamate neurotransmission during early postnatal neurodevelopment in rodents has induced behavioral, cognitive, and neuropathophysiological abnormalities relevant to schizophrenia. Here, we tested the hypothesis that using the NMDA receptor antagonist phencyclidine (PCP) to disrupt postnatal glutamatergic transmission in rats would lead to impaired decision making in the PRL. Consistent with this hypothesis, compared to controls the postnatal PCP-treated rats completed fewer reversals and exhibited disruptions in reward and punishment sensitivity (i.e., win-stay and lose-shift responding, respectively). Moreover, computational analysis of behavior revealed that postnatal PCP-treatment resulted in a pronounced impairment in the learning rate throughout PRL testing. Finally, a deep neural network (DNN) trained on the rodent behavior could accurately predict the treatment group of subjects. These data demonstrate that disrupting early postnatal glutamatergic neurotransmission impairs flexible decision making and provides evidence that DNNs can be trained on behavioral datasets to accurately predict the treatment group of new subjects, highlighting the potential for DNNs to aid in the diagnosis of schizophrenia.

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).

Striatal dopamine in anhedonia: A simultaneous [11C]raclopride positron emission tomography and functional magnetic resonance imaging investigation.

BACKGROUND: Anhedonia is hypothesized to be associated with blunted mesocorticolimbic dopamine (DA) functioning in samples with major depressive disorder. The purpose of this study was to examine linkages between striatal DA, reward circuitry functioning, anhedonia, and, in an exploratory fashion, self-reported stress, in a transdiagnostic anhedonic sample. METHODS: Participants with (n = 25) and without (n = 12) clinically impairing anhedonia completed a reward-processing task during simultaneous positron emission tomography and magnetic resonance (PET-MR) imaging with [11C]raclopride, a DA D2/D3 receptor antagonist that selectively binds to striatal DA receptors. RESULTS: Relative to controls, the anhedonia group exhibited decreased task-related DA release in the left putamen, caudate, and nucleus accumbens and right putamen and pallidum. There were no group differences in task-related brain activation (fMRI) during reward processing after correcting for multiple comparisons. General functional connectivity (GFC) findings revealed blunted fMRI connectivity between PET-derived striatal seeds and target regions in the anhedonia group. Associations were identified between anhedonia severity and the magnitude of task-related DA release to rewards in the left putamen, but not mesocorticolimbic GFC. CONCLUSIONS: Results provide evidence for reduced striatal DA functioning during reward processing and blunted mesocorticolimbic network functional connectivity in a transdiagnostic sample with clinically significant anhedonia.