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Background: Loneliness and social isolation have detrimental consequences for mental health and act as vulnerability factors for the development of depressive symptoms, such as anhedonia. The mitigation strategies used to contain COVID-19, such as social distancing and lockdowns, allowed us to investigate putative associations between daily objective and perceived social isolation and anhedonic-like behavior. Methods: Reward-related functioning was objectively assessed using the Probabilistic Reward Task. A total of 114 unselected healthy individuals (71% female) underwent both a laboratory and an ecological momentary assessment. Computational modeling was applied to performance on the Probabilistic Reward Task to disentangle reward sensitivity and learning rate. Results: Findings revealed that objective, but not subjective, daily social interactions were associated with motivational behavior. Specifically, higher social isolation (less time spent with others) was associated with higher responsivity to rewarding stimuli and a reduced influence of a given reward on successive behavioral choices. Conclusions: Overall, the current results broaden our knowledge of the potential pathways that link (COVID-19-related) social isolation to altered motivational functioning.

Loneliness and social isolation negatively impact mental health and contribute to depressive symptoms like anhedonia. With COVID-19 restrictions such as social distancing, we examined how daily social isolation, measured ecologically, is related to anhedonic behavior. We tested 114 healthy adults using a task that measured their responses to rewards. Greater isolation was linked to an increased response to rewards but also to a reduced ability to learn from them, which lessened the influence of rewards on future behavior. These findings highlight potential mechanisms that link social isolation to changes in motivation, ultimately leading to depressive symptoms.

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Misinformation has risen in recent years, negatively affecting domains ranging from politics to health. To curb the spread of misinformation it is useful to consider why, how, and when people decide to share information. Here we suggest that information-sharing decisions are value-based choices, in which sharers strive to maximize rewards and minimize losses to themselves and/or others. These outcomes can be tangible, in the form of monetary rewards or losses, or intangible, in the form of social feedback. On social media platforms these rewards and losses are not clearly tied to the accuracy of information shared. Thus, sharers have little incentive to avoid disseminating misinformation. Based on this framework, we propose ways to nudge sharers to prioritize accuracy during information-sharing.

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BACKGROUND: The nucleus accumbens (NAc) mediates reward learning and motivation. Despite an abundance of neuropeptides, peptidergic neurotransmission from the NAc has not been integrated into current models of reward learning. The existence of a sparse population of neurons containing corticotropin releasing factor (CRF) has been previously documented. Here we provide a comprehensive analysis of their identity and functional role in shaping reward learning. METHODS: To do this, we took a multidisciplinary approach that included florescent in situ hybridization (Nmice ≥ 3), tract tracing (Nmice = 5), ex vivo electrophysiology (Ncells ≥ 30), in vivo calcium imaging with fiber photometry (Nmice ≥ 4) and use of viral strategies in transgenic lines to selectively delete CRF peptide from NAc neurons (Nmice ≥ 4). Behaviors used were instrumental learning, sucrose preference and spontaneous exploration in an open field. RESULTS: Here we show that the vast majority of NAc CRF-containing (NAcCRF) neurons are spiny projection neurons (SPNs) comprised of dopamine D1-, D2- or D1/D2-containing SPNs that primarily project and connect to the ventral pallidum and to a lesser extent the ventral midbrain. As a population, they display mature and immature SPN firing properties. We demonstrate that NAcCRF neurons track reward outcomes during operant reward learning and that CRF release from these neurons acts to constrain initial acquisition of action-outcome learning, and at the same time facilitates flexibility in the face of changing contingencies. CONCLUSION: We conclude that CRF release from this sparse population of SPNs is critical for reward learning under normal conditions.

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Stressors can initiate a cascade of central and peripheral changes that modulate mesocorticolimbic dopaminergic circuits and, ultimately, behavioral response to rewards. Driven by the absence of conclusive evidence on this topic and the Research Domain Criteria framework, random-effects meta-analyses were adopted to quantify the effects of acute stressors on reward responsiveness, valuation, and learning in rodent and human subjects. In rodents, acute stress reduced reward responsiveness (g = -1.43) and valuation (g = -0.32), while amplifying reward learning (g = 1.17). In humans, acute stress had marginal effects on valuation (g = 0.25), without affecting responsiveness and learning. Moderation analyses suggest that acute stress neither has unitary effects on reward processing in rodents nor in humans and that the duration of the stressor and specificity of reward experience (i.e., food vs drugs) may produce qualitatively and quantitatively different behavioral endpoints. Subgroup analyses failed to reduce heterogeneity, which, together with the presence of publication bias, pose caution on the conclusions that can be drawn and point to the need of guidelines for the conduction of future studies in the field.

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Adverse childhood experiences (ACEs) are a major risk factor for the development of multiple psychopathological conditions, but the mechanisms underlying this link are poorly understood. Associative learning encompasses key mechanisms through which individuals learn to link important environmental inputs to emotional and behavioral responses. ACEs may impact the normative maturation of associative learning processes, resulting in their enduring maladaptive expression manifesting in psychopathology. In this review, we lay out a systematic and methodological overview and integration of the available evidence of the proposed association between ACEs and threat and reward learning processes. We summarize results from a systematic literature search (following PRISMA guidelines) which yielded a total of 81 articles (threat: n=38, reward: n=43). Across the threat and reward learning fields, behaviorally, we observed a converging pattern of aberrant learning in individuals with a history of ACEs, independent of other sample characteristics, specific ACE types, and outcome measures. Specifically, blunted threat learning was reflected in reduced discrimination between threat and safety cues, primarily driven by diminished responding to conditioned threat cues. Furthermore, attenuated reward learning manifested in reduced accuracy and learning rate in tasks involving acquisition of reward contingencies. Importantly, this pattern emerged despite substantial heterogeneity in ACE assessment and operationalization across both fields. We conclude that blunted threat and reward learning may represent a mechanistic route by which ACEs may become physiologically and neurobiologically embedded and ultimately confer greater risk for psychopathology. In closing, we discuss potentially fruitful future directions for the research field, including methodological and ACE assessment considerations.

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The Affective Bias Test (ABT) quantifies acute changes in affective state based on the affective biases they generate in an associative reward learning task. The Reward Learning Assay (RLA) provides a control assay for the ABT and reward-induced biases generated in this model are sensitive to changes in core affective state. Both tasks involve training animals to associate a specific digging substrate with a food reward. Animals learn to discriminate between two digging substrates placed in ceramic bowls, one rewarded and one unrewarded. In the ABT, the animal learns two independent substrate-reward associations with a fixed reward value following either an affective state or drug manipulation, or under control conditions. Affective biases generated are quantified in a choice test where the animals exhibit a bias (make more choices) for one of the substrates which is specifically related to affective state at the time of learning. The ABT is used to investigate biases generated during learning as well as modulation of biases associated with past experiences. The RLA follows a similar protocol, but the animal remains in the same affective state throughout and a reward-induced bias is generated by pairing one substrate with a higher value reward. The RLA provides a control to determine if drug treatments affect memory retrieval more generally. Studies in depression models and following environmental enrichment suggest that reward-induced biases are sensitive to core changes in affective state. Each task offers different insights into affective processing mechanisms and may help improve the translational validity of animal studies and benefit pre-clinical drug development. © 2024 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Bowl digging and discrimination training Basic Protocol 2: The reward learning assay Basic Protocol 3: The affective bias test - new learning Basic Protocol 4: The affective bias test - modulation of affective biases associated with past experiences.

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In classical cerebellar learning, Purkinje cells (PkCs) associate climbing fiber (CF) error signals with predictive granule cells (GrCs) that were active just prior (∼150 ms). The cerebellum also contributes to behaviors characterized by longer timescales. To investigate how GrC-CF-PkC circuits might learn seconds-long predictions, we imaged simultaneous GrC-CF activity over days of forelimb operant conditioning for delayed water reward. As mice learned reward timing, numerous GrCs developed anticipatory activity ramping at different rates until reward delivery, followed by widespread time-locked CF spiking. Relearning longer delays further lengthened GrC activations. We computed CF-dependent GrC→PkC plasticity rules, demonstrating that reward-evoked CF spikes sufficed to grade many GrC synapses by anticipatory timing. We predicted and confirmed that PkCs could thereby continuously ramp across seconds-long intervals from movement to reward. Learning thus leads to new GrC temporal bases linking predictors to remote CF reward signals-a strategy well suited for learning to track the long intervals common in cognitive domains.

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BACKGROUND: Decades of research have firmly established that cognitive health and cognitive treatment services are a key need for people living with psychosis. However, many current clinical programs do not address this need, despite the essential role that an individual's cognitive and social cognitive capacities play in determining their real-world functioning. Preliminary practice-based research in the Early Psychosis Intervention Network early psychosis intervention network shows that it is possible to develop and implement tools that delineate an individuals' cognitive health profile and that help engage the client and the clinician in shared decision-making and treatment planning that includes cognitive treatments. These findings signify a promising shift toward personalized cognitive health. STUDY DESIGN: Extending upon this early progress, we review the concept of interindividual variability in cognitive domains/processes in psychosis as the basis for offering personalized treatment plans. We present evidence from studies that have used traditional neuropsychological measures as well as findings from emerging computational studies that leverage trial-by-trial behavior data to illuminate the different latent strategies that individuals employ. STUDY RESULT: We posit that these computational techniques, when combined with traditional cognitive assessments, can enrich our understanding of individual differences in treatment needs, which in turn can guide evermore personalized interventions. CONCLUSION: As we find clinically relevant ways to decompose maladaptive behaviors into separate latent cognitive elements captured by model parameters, the ultimate goal is to develop and implement approaches that empower clients and their clinical providers to leverage individual's existing learning capacities to improve their cognitive health and well-being.

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Learning, an important activity for both human and animals, has long been a focal point of research. During the learning process, subjects assimilate not only their own information but also information from others, a phenomenon known as social learning. While numerous studies have explored the impact of social feedback as a reward/punishment during learning, few studies have investigated whether social feedback facilitates or inhibits the learning of environmental rewards/punishments. This study aims to test the effects of social feedback on economic feedback and its cognitive processes by using the Iowa Gambling Task (IGT). One hundred ninety-two participants were recruited and categorized into one non-social feedback group and four social feedback groups. Participants in the social feedback groups were informed that after the outcome of each choice, they would also receive feedback from an online peer. This peer was a fictitious entity, with variations in identity (novice or expert) and feedback type (random or effective). The Outcome-Representation Learning model (ORL model) was used to quantify the cognitive components of learning. Behavioral results showed that both the identity of the peer and the type of feedback provided significantly influenced the deck selection, with effective social feedback increasing the ratio of chosen good decks. Results in the ORL model showed that the four social feedback groups exhibited lower learning rates for gain and loss compared to the nonsocial feedback group, which suggested, in the social feedback groups, the impact of the recent outcome on the update of value decreased. Parameters such as forgetfulness, win frequency, and deck perseverance in the expert-effective feedback group were significantly higher than those in the non-social feedback and expert-random feedback groups. These findings suggest that individuals proactively evaluate feedback providers and selectively adopt effective feedback to enhance learning.

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Major depressive disorder (MDD) is one of the leading causes of disability-adjusted life years. Emerging evidence indicates the presence of reward processing abnormalities in MDD. An important scientific question is whether the abnormalities are due to reduced sensitivity to received rewards or reduced learning ability. Motivated by the probabilistic reward task (PRT) experiment in the EMBARC study, we propose a semiparametric inverse reinforcement learning (RL) approach to characterize the reward-based decision-making of MDD patients. The model assumes that a subject's decision-making process is updated based on a reward prediction error weighted by the subject-specific learning rate. To account for the fact that one favors a decision leading to a potentially high reward, but this decision process is not necessarily linear, we model reward sensitivity with a non-decreasing and nonlinear function. For inference, we estimate the latter via approximation by I-splines and then maximize the joint conditional log-likelihood. We show that the resulting estimators are consistent and asymptotically normal. Through extensive simulation studies, we demonstrate that under different reward-generating distributions, the semiparametric inverse RL outperforms the parametric inverse RL. We apply the proposed method to EMBARC and find that MDD and control groups have similar learning rates but different reward sensitivity functions. There is strong statistical evidence that reward sensitivity functions have nonlinear forms. Using additional brain imaging data in the same study, we find that both reward sensitivity and learning rate are associated with brain activities in the negative affect circuitry under an emotional conflict task.

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RATIONALE: Cognitive flexibility, the ability to adapt behaviour in response to a changing environment, is disrupted in several neuropsychiatric disorders, including obsessive-compulsive disorder and major depressive disorder. Evidence suggests that flexibility, which can be operationalised using reversal learning tasks, is modulated by serotonergic transmission. However, how exactly flexible behaviour and associated reinforcement learning (RL) processes are modulated by 5-HT action on specific receptors is unknown. OBJECTIVES: We investigated the effects of 5-HT2A receptor (5-HT2AR) and 5-HT2C receptor (5-HT2CR) antagonism on flexibility and underlying RL mechanisms. METHODS: Thirty-six male Lister hooded rats were trained on a touchscreen visual discrimination and reversal task. We evaluated the effects of systemic treatments with the 5-HT2AR and 5-HT2CR antagonists M100907 and SB-242084, respectively, on reversal learning and performance on probe trials where correct and incorrect stimuli were presented with a third, probabilistically rewarded, stimulus. Computational models were fitted to task choice data to extract RL parameters, including a novel model designed specifically for this task. RESULTS: 5-HT2AR antagonism impaired reversal learning only after an initial perseverative phase, during a period of random choice and then new learning. 5-HT2CR antagonism, on the other hand, impaired learning from positive feedback. RL models further differentiated these effects. 5-HT2AR antagonism decreased punishment learning rate (i.e. negative feedback) at high and low doses. The low dose also decreased reinforcement sensitivity (beta) and increased stimulus and side stickiness (i.e., the tendency to repeat a choice regardless of outcome). 5-HT2CR antagonism also decreased beta, but reduced side stickiness. CONCLUSIONS: These data indicate that 5-HT2A and 5-HT2CRs both modulate different aspects of flexibility, with 5-HT2ARs modulating learning from negative feedback as measured using RL parameters and 5-HT2CRs for learning from positive feedback assessed through conventional measures.

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The forkhead box protein P2 (Foxp2), initially identified for its role in speech and language development, plays an important role in neural development. Previous studies investigated the function of the Foxp2 gene by deleting or mutating Foxp2 from developmental stages. Little is known about its physiological function in adult brains. Although Foxp2 has been well studied in the dorsal striatum, its function in the nucleus accumbens (NAc) of the ventral striatum remains elusive. Here, we examine the physiological function of Foxp2 in NAc of mouse brains. We conditionally knocked out Foxp2 by microinjections of AAV-EGFP-Cre viruses into the medial shell of NAc of Foxp2 floxed (cKO) mice. Immunostaining showed increased c-Fos positive cells in cKO NAc at basal levels, suggesting an abnormality in Foxp2-deficient NAc cells. Unbiased behavioral profiling of Foxp2 cKO mice showed abnormalities in limbic-associated function. Foxp2 cKO mice exhibited abnormal social novelty without preference for interaction with strangers and familiar mice. In appetitive reward learning, Foxp2 cKO mice failed to learn the time expectancy of food delivery. In fear learning, Foxp2 cKO mice exhibited abnormal increases in freezing levels in response to tone paired with foot shock during fear conditioning. The extinction of the fear response was also altered in Foxp2 cKO mice. In contrast, conditional knockout of Foxp2 in NAc did not affect locomotion, motor coordination, thermal pain sensation, anxiety- and depression-like behaviors. Collectively, our study suggests that Foxp2 has a multifaceted physiological role in NAc in the regulation of limbic function in the adult brain.

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Attention filters sensory inputs to enhance task-relevant information. It is guided by an "attentional template" that represents the stimulus features that are currently relevant. To understand how the brain learns and uses templates, we trained monkeys to perform a visual search task that required them to repeatedly learn new attentional templates. Neural recordings found that templates were represented across the prefrontal and parietal cortex in a structured manner, such that perceptually neighboring templates had similar neural representations. When the task changed, a new attentional template was learned by incrementally shifting the template toward rewarded features. Finally, we found that attentional templates transformed stimulus features into a common value representation that allowed the same decision-making mechanisms to deploy attention, regardless of the identity of the template. Altogether, our results provide insight into the neural mechanisms by which the brain learns to control attention and how attention can be flexibly deployed across tasks.

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BACKGROUND: Neurocognitive factors including aberrant reward learning, blunted GABA (gamma-aminobutyric acid), and potentiated stress sensitivity have been linked to anhedonia, a hallmark depressive symptom, possibly in a sex-dependent manner. However, previous research has not investigated the putative associations among these factors or the extent to which they represent trait- or state-based vulnerabilities for depression. METHODS: Young adults with current major depressive disorder (MDD) (n = 44), remitted MDD (n = 42), and healthy control participants (HCs) (n = 44), stratified by sex assigned at birth, underwent magnetic resonance spectroscopy to assess macromolecular contaminated GABA (GABA+) and then a reward learning task before and after acute stress. We assessed changes in reward learning after stress and associations with GABA+. RESULTS: Results revealed blunted baseline reward learning in participants with remitted MDD versus participants with current MDD and HCs but, surprisingly, no differences between participants with current MDD and HCs. Reward learning was reduced following acute stress regardless of depressive history. GABA+ in the rostral anterior cingulate cortex, but not the dorsolateral prefrontal cortex, was associated with reduced baseline reward learning only in female participants. GABA+ did not predict stress-related changes in reward learning. CONCLUSIONS: To our knowledge, this is the first study to investigate associations among GABA, reward learning, and stress reactivity in current versus past depression. Hypothesized depression-related differences in reward learning did not emerge, precluding claims about state versus trait vulnerabilities. However, our finding that blunted GABA was associated with greater reward learning in female participants provides novel insights into sex-selective associations between the frontal GABAergic inhibitory system and reward processing.

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Investigations of information-seeking often highlight people's tendency to forgo financial reward in return for advance information about future outcomes. Most of these experiments use tasks in which reward contingencies are described to participants. The use of such descriptions leaves open the question of whether the opportunity to obtain such noninstrumental information influences people's ability to learn and represent the underlying reward structure of an experimental environment. In two experiments, participants completed a two-armed bandit task with monetary incentives where reward contingencies were learned via trial-by-trial experience. We find, akin to description-based tasks, that participants are willing to forgo financial reward to receive information about a delayed, unchangeable outcome. Crucially, however, there is little evidence this willingness to pay for information is driven by an inaccurate representation of the reward structure: participants' representations approximated the underlying reward structure regardless of the presence of advance noninstrumental information. The results extend previous conclusions regarding the intrinsic value of information to an experience-based domain and highlight challenges of probing participants' memories for experienced rewards.

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BACKGROUND: Cognitive impairment is common with schizophrenia spectrum disorders. Cognitive remediation (CR) is effective in improving global cognition, but not all individuals benefit from this type of intervention. A better understanding of the potential mechanism of action of CR is needed. One proposed mechanism is reward learning (RL), the cognitive processes responsible for adapting behavior following positive or negative feedback. It is proposed that the structure of CR enhances RL and motivation to engage in increasingly challenging tasks, and this is a potential mechanism by which CR improves cognitive functioning in schizophrenia. OBJECTIVE: Our primary objective is to examine reward processing in individuals with schizophrenia before and after completing CR and to compare this with a group of matched clinical controls. We will assess whether RL mediates the relationship between CR and improved cognitive function and reduced negative symptoms. Potential differences in social RL and nonsocial RL in individuals with schizophrenia will also be investigated and compared with a healthy matched control group. METHODS: We propose a clinical, nonrandomized, pre-post pilot study comparing the impact of CR on RL and neurocognitive outcomes. The study will use a combination of objective and subjective measures to assess neurocognitive, psychiatric symptoms, and neurophysiological domains. A total of 40 individuals with schizophrenia spectrum disorders (aged 18-35 years) will receive 12 weeks of CR therapy (n=20) or treatment as usual (n=20). Reward processing will be evaluated using a reinforcement learning task with 2 conditions (social reward vs nonsocial reward) at baseline and the 12-week follow-up. Functional magnetic resonance imaging responses will be measured during this task. To validate the reinforcement learning task, RL will also be assessed in 20 healthy controls, matched for age, sex, and premorbid functioning. Mixed-factorial ANOVAs will be conducted to evaluate treatment group differences. For the functional magnetic resonance imaging analysis, computational modeling will allow the estimation of learning parameters at each point in time, during each task condition, for each participant. We will use a variational Bayesian framework to measure how learning occurred during the experimental task and the subprocesses that underlie this learning. Second-level group analyses will examine how learning in patients differs from that observed in control participants and how CR alters learning efficiency and the underlying neural activity. RESULTS: As of September 2023, this study has enrolled 15 participants in the CR group, 1 participant in the treatment-as-usual group, and 11 participants in the healthy control group. Recruitment is expected to be completed by September 2024. Data analysis is expected to be completed and published in early 2025. CONCLUSIONS: The results of this study will contribute to the knowledge of CR and RL processes in severe mental illness and the understanding of the systems that impact negative symptoms and cognitive impairments within this population. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/52505.

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BACKGROUND: The Probabilistic Reward Task (PRT) is a signal detection task that assesses reward learning. In laboratory versions of the task, individuals with current or past major depressive disorder (MDD) were characterized by reduced response bias towards a more frequently rewarded stimuli, compared to controls. Our main goal was to develop and validate a novel online version of the PRT, and, in exploratory analyses, evaluate whether lifetime history of depression was associated with blunted reward learning. METHODS: 429 participants recruited via CloudResearch completed questionnaires assessing psychiatric history and an online PRT featuring visually appealing stimuli. 108 participants reported either current or past diagnosis of MDD (lifetime MDD group), and were compared to 321 without lifetime MDD. RESULTS: Participants showed overall increase in response bias, validating the online PRT. Females with lifetime MDD (N = 43), compared to females without prior history of MDD (N = 173), exhibited blunted response bias towards the more frequently rewarded stimulus (i.e., reduced reward learning). LIMITATIONS: Participants did not undergo a structured clinical interview, thus we cannot confirm whether they met full diagnostic criteria for depression. CONCLUSIONS: The online PRT yielded similar psychometric properties as laboratory versions of the task. In exploratory analyses, females with lifetime MDD showed a lower propensity to modulate behavior as a function of rewards, which might contribute to heightened vulnerability for developing MDD in females. Future studies should consider social, cultural, and neurobiological factors contributing to sex differences in reward responsiveness and how factors may relate to disease prognosis and treatment outcomes.

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BACKGROUND: Existing research indicates that individuals with Major Depressive Disorder (MDD) exhibit a bias toward salient negative stimuli. However, the impact of such biased stimuli on concurrent cognitive and affective processes in individuals with depression remains inadequately understood. This study aimed to investigate the effects of salient environmental stimuli, specifically emotional faces, on reward-associated processes in MDD. METHODS: Thirty-three patients with recurrent MDD and thirty-two healthy controls (HC) matched for age, sex, and education were included in the study. We used a reward-related associative learning (RRAL) task primed with emotional (happy, sad, neutral) faces to investigate the effect of salient stimuli on reward-related learning and decision-making in functional magnetic resonance imaging (fMRI). Participants were instructed to ignore emotional faces during the task. The fMRI data were analyzed using a full-factorial general linear model (GLM) in Statistical Parametric Mapping (SPM12). RESULTS: In depressed patients, cues primed with sad faces were associated with reduced amygdala activation. However, both HC and MDD group exhibited reduced ventral striatal activity while learning reward-related cues and receiving rewards. LIMITATIONS: The patients'medication usage was not standardized. CONCLUSIONS: This study underscores the functional alteration of the amygdala in response to cognitive tasks presented with negative emotionally salient stimuli in the environment of MDD patients. The observed alterations in amygdala activity suggest potential interconnected effects with other regions of the prefrontal cortex. Understanding the intricate neural connections and their disruptions in depression is crucial for unraveling the complex pathophysiology of the disorder.

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BACKGROUND: Aberrant reward functioning is implicated in depression. While attention precedes behavior and guides higher-order cognitive processes, reward learning from an attentional perspective - the effects of prior reward-learning on subsequent attention allocation - has been mainly overlooked. METHODS: The present study explored the effects of reward-based attentional learning in depression using two separate, yet complimentary, studies. In study 1, participants with high (HD) and low (LD) levels of depression symptoms were trained to divert their gaze toward one type of stimuli over another using a novel gaze-contingent music reward paradigm - music played when fixating the desired stimulus type and stopped when gazing the alternate one. Attention allocation was assessed before, during, and following training. In study 2, using negative reinforcement, the same attention allocation pattern was trained while substituting the appetitive music reward for gazing the desired stimulus type with the removal of an aversive sound (i.e. white noise). RESULTS: In study 1 both groups showed the intended shift in attention allocation during training (online reward learning), while generalization of learning at post-training was only evident among LD participants. Conversely, in study 2 both groups showed post-training generalization. Results were maintained when introducing anxiety as a covariate, and when using a more powerful sensitivity analysis. Finally, HD participants showed higher learning speed than LD participants during initial online learning, but only when using negative, not positive, reinforcement. CONCLUSIONS: Deficient generalization of learning characterizes the attentional system of HD individuals, but only when using reward-based positive reinforcement, not negative reinforcement.

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Reversal learning measures the ability to form flexible associations between choice outcomes with stimuli and actions that precede them. This type of learning is thought to rely on several cortical and subcortical areas, including the highly interconnected orbitofrontal cortex (OFC) and basolateral amygdala (BLA), and is often impaired in various neuropsychiatric and substance use disorders. However, the unique contributions of these regions to stimulus- and action-based reversal learning have not been systematically compared using a chemogenetic approach particularly before and after the first reversal that introduces new uncertainty. Here, we examined the roles of ventrolateral OFC (vlOFC) and BLA during reversal learning. Male and female rats were prepared with inhibitory designer receptors exclusively activated by designer drugs targeting projection neurons in these regions and tested on a series of deterministic and probabilistic reversals during which they learned about stimulus identity or side (left or right) associated with different reward probabilities. Using a counterbalanced within-subject design, we inhibited these regions prior to reversal sessions. We assessed initial and pre-/post-reversal changes in performance to measure learning and adjustments to reversals, respectively. We found that inhibition of the ventrolateral orbitofrontal cortex (vlOFC), but not BLA, eliminated adjustments to stimulus-based reversals. Inhibition of BLA, but not vlOFC, selectively impaired action-based probabilistic reversal learning, leaving deterministic reversal learning intact. vlOFC exhibited a sex-dependent role in early adjustment to action-based reversals, but not in overall learning. These results reveal dissociable roles for BLA and vlOFC in flexible learning and highlight a more crucial role for BLA in learning meaningful changes in the reward environment.

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