Computational psychiatry (Cambridge, Mass.)最新文献

{"title":"Investigating Sensorimotor Decision-Making in Depressed Individuals Using a Bayesian Approach.","authors":"Xin Song, Mathi Manavalan, Julia Griem, Tobias Nolte, Peter Fonagy, Iris Vilares","doi":"10.5334/cpsy.195","DOIUrl":"https://doi.org/10.5334/cpsy.195","url":null,"abstract":"<p><p>Depression is among the most prevalent and disabling mental health conditions worldwide. It is associated with low mood and motivation, cognitive inefficiencies, altered reward and punishment learning, and broader executive dysfunction that can disrupt daily functioning. Depression has also been linked to differences in sensory perception, sensitivity, and processing speed. However, how depression affects sensorimotor decision-making under uncertainty remains comparatively understudied. In this study, we examined how individuals with depression process and weigh prior information relative to current sensory evidence during sensorimotor decisions. Participants completed a visuomotor coin-catching task, and behavior was analyzed within a Bayesian Decision Theory framework. We tested whether reliance on current information differed between depressed and non-depressed individuals, and whether any differences depended on uncertainty in the prior or the sensory signal. Across behavioral and computational analyses, both groups combined prior knowledge and sensory input in a qualitatively Bayesian manner, placing greater weight on current information when it was less uncertain and/or when prior information was more uncertain. The groups did not differ significantly in overall relative reliance on current information. Despite these broad similarities, more subtle differences were apparent. Model-based analyses indicated that Bayesian models outperformed heuristic alternatives in both groups, but model fit was poorer in the depressed group. Both groups adjusted sensory weighting as prior uncertainty changed, but non-depressed participants showed about twice the shift observed in depressed individuals, although this difference was not statistically significant. Together, these findings suggest that depression does not eliminate Bayesian-like integration of priors and sensory evidence, but may potentially reduce sensitivity to changes in prior reliability. Future work should test whether individual differences in symptom profiles, task demands, and cognitive flexibility moderate these effects.</p>","PeriodicalId":72664,"journal":{"name":"Computational psychiatry (Cambridge, Mass.)","volume":"10 1","pages":"202-218"},"PeriodicalIF":0.0,"publicationDate":"2026-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13651772/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149167835","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"(Re)building Cooperation: Effects of a Cognitive Intervention on Cooperative Behaviour in Games.","authors":"Ismail Guennouni, Samuel Dupret, Quentin J M Huys, Maarten Speekenbrink","doi":"10.5334/cpsy.178","DOIUrl":"10.5334/cpsy.178","url":null,"abstract":"<p><p>Cooperation often breaks down when one party appears to withdraw trust, yet most research has focused on initial trust formation rather than how the aggrieved party can resist the impulse to retaliate. In a randomised controlled online trial (N = 318), we tested whether a brief cognitive intervention inspired by Dialectical Behaviour Therapy principles could promote resilient cooperation in the face of trust withdrawals. Participants played a Repeated Trust Game as trustees against adaptive computerised investors driven by hidden Markov models (HMMs) trained on human data, providing behavioural realism under full experimental control. Following the intervention, participants returned a significantly higher proportion of the amount received than an active control group across the post-manipulation game. The groups diverged most sharply at the pre-programmed low investment, where the control group retaliated by reducing returns while the intervention group maintained the same level of returns. This shift occurred without a change in self-reported emotional reactivity, dissociating the preserved emotional reaction from the retaliatory behaviour it drives. HMM analysis of participants' own return patterns revealed that participants in the intervention condition were less likely to become stuck in low-return behavioural states following the pre-programmed low investment, though a notable minority did not respond to the intervention. The intervention effect did not transfer to a Prisoner's Dilemma game, consistent with context-specific effects. These findings provide proof-of-concept evidence that targeted cognitive strategies can support cooperation after trust violations, and show that HMM-based agents are a useful tool for studying social behaviour under controlled conditions.</p>","PeriodicalId":72664,"journal":{"name":"Computational psychiatry (Cambridge, Mass.)","volume":"10 1","pages":"184-201"},"PeriodicalIF":0.0,"publicationDate":"2026-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13588210/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149009532","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Associations Between Steep Delay Discounting and Punishment Learning.","authors":"Jeremy Haynes, Peter Kvam, Thomas Olino","doi":"10.5334/cpsy.172","DOIUrl":"10.5334/cpsy.172","url":null,"abstract":"<p><p>Reward valuation and reward and punishment learning are important constructs for understanding and intervening on mental illness. These constructs are frequently measured with behavioral tasks such as intertemporal choice tasks, measuring delay discounting, and the Iowa Gambling Task (IGT), measuring reward and punishment learning. Delay discounting refers to how people value delayed outcomes, with steep discounting (i.e., delayed outcomes holding little value) considered a form of impulsive decision-making. Reward and punishment learning refers to how people adjust their decision behavior in response to rewards and punishments, with deficits indicating atypical reward and punishment processing related to clinical outcomes such as substance abuse. In this study, we tested the association between delay discounting and computational measures of reward and punishment learning in adults (<i>N</i> = 299) that completed an intertemporal choice task and the play-or-pass IGT. We fit a joint model to the task data to simultaneously estimate parameters from the hyperbolic discounting model (for the intertemporal choice task) and a reinforcement learning model (for the play-or-pass IGT). Our results indicate that steep delay discounting is associated with lower performance on the IGT, specifically through lower punishment learning. That is, people who do not value delayed outcomes also show less learning from punishment, resulting in worse performance in the IGT. Implications of these findings are discussed in the context of improving assessment of reward valuation and reward and punishment learning as constructs relevant to mental illness.</p>","PeriodicalId":72664,"journal":{"name":"Computational psychiatry (Cambridge, Mass.)","volume":"10 1","pages":"159-183"},"PeriodicalIF":0.0,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13544050/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148898367","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"OCD Compulsions as Aberrant Integration of Uncertainty from Local Goals to Global Goals.","authors":"Andra Geana, Christina L Boisseau, Steven Rasmussen, Michael J Frank","doi":"10.5334/cpsy.145","DOIUrl":"10.5334/cpsy.145","url":null,"abstract":"<p><p>Recent years have seen unprecedented increases in compulsive behaviors, even in previously undiagnosed populations. Yet, despite their rising prevalence and the fact that compulsions-notably associated with obsessive-compulsive disorder (OCD), but also a key feature of other disorders such a hoarding or body dysmorphic disorder-significantly hamper daily function, the specific mechanisms of their formation remain unknown. Previous research holds mixed findings on compulsivity-linked cognitive deficits, and, while many accounts assume that compulsions aim to reduce anxiety, most individuals with anxiety do not develop compulsions-suggesting that the anxiety-reduction account is incomplete. We propose here a broader, uncertainty-resolving account of compulsivity, that bypasses the commonly-used, single-goal structure of many cognitive tasks to leverage the real-world hierarchical structure of goals-with \"<i>local\", short-term subgoals</i> (e.g., \"how do I clean my hands?\") in the service of <i>long-term, \"global\" goals</i> (\"how do I stay healthy?\"). In that framework, we suggest that compulsivity may reflect a deficit in integrating uncertainty from local to global goals, which still spares the basic circuitry of reward and learning. We tested 20 OCD patients and 20 healthy volunteers in a predictive inference task with a hierarchical structure of local uncertainty reduction in the service of global uncertainty reduction. Both groups learned the reward structure of the local environment based on observed data; however, only the healthy volunteers showed evidence of integrating learned knowledge at the local level to reduce uncertainty about the higher level of the task hierarchy. This indicates a potential mechanism for compulsions that relies on the inability to adaptively integrate, prioritize, and \"toggle\" among different local goals in the service of global goals.</p>","PeriodicalId":72664,"journal":{"name":"Computational psychiatry (Cambridge, Mass.)","volume":"10 1","pages":"142-158"},"PeriodicalIF":0.0,"publicationDate":"2026-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13475530/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148765763","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Cortical Microstructural Variations Correlate With Individual Differences in Gamified Exploration-Exploitation Behaviours.","authors":"Ashley Tyrer, Niia Nikolova, Magda Dubois, Leah Banellis, Melina Vejlø, Tobias U Hauser, Micah Allen","doi":"10.5334/cpsy.164","DOIUrl":"10.5334/cpsy.164","url":null,"abstract":"<p><p>The exploration-exploitation trade-off is ubiquitous in our everyday lives, and individuals display considerable variability in their preferred decision-making strategies. Most previous work pertaining to neural signatures of exploration is restricted to functional pathways. However, the specific contributions of cortical microarchitectures to high-level cognitive processes such as decision-making are as yet unknown. Here, we investigated the neuroanatomical foundations of inter-individual variability in decision-making strategies. To this end, 122 healthy participants completed a gamified multi-armed bandit paradigm aimed at teasing apart distinct exploration-exploitation decision strategies. We also collected whole-brain quantitative MRI maps indexing microstructural features of cortical myelination and iron content. Through computational modelling, we disentangled individual-specific exploration strategies, including value-free random exploration. Whole-brain regression analyses identified significant associations between value-free exploration and increased cortical myelination in right frontal brain areas with reported links to impulsivity. By elucidating the brain microstructural correlates of distinct exploration-exploitation strategies, we aimed to further our understanding of why individuals differ in their decision-making capabilities, and how decision-making may become aberrant in mental health conditions.</p>","PeriodicalId":72664,"journal":{"name":"Computational psychiatry (Cambridge, Mass.)","volume":"10 1","pages":"121-141"},"PeriodicalIF":0.0,"publicationDate":"2026-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13450271/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148698474","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Excessive Switching in OCD and Paranoia Arises From Different Deficits in Belief-Updating.","authors":"Charlotte M Freeland, Praveen Suthaharan, Santiago Castiello de Obeso, Christopher Pittenger, Philip R Corlett","doi":"10.5334/cpsy.136","DOIUrl":"10.5334/cpsy.136","url":null,"abstract":"<p><p>Both obsessions and paranoia are characterized by cognitive inflexibility, particularly in uncertain environments. Differential diagnosis can be challenging and depends on clinical interviews and self-report symptom questionnaires. We predicted that obsessions and paranoia would be associated with distinct suboptimal choice behavioral patterns in our well-established probabilistic reversal learning (PRL) task. Probabilistic reversal learning involves updating beliefs about rewards when contingencies change. Obsessions and paranoia have been linked to excessive switching behaviors during reversal learning; other reports have found perseveration in both OCD and schizophrenia. Here, we analyze data collected from the general population to assess associations between obsessions, paranoia, and PRL task performance. Using a recently developed computational approach - Bayesian Gaussian graphical modeling combined with a Hierarchical Gaussian Filter - we distinguish the impacts of paranoia and obsessions on reversal learning, which we find to be distinct despite the significant correlation of these clinical states. We find that win-switch behavior arises in paranoia from deficits in updating beliefs about uncertainty (i.e., volatility) in the global task structure, whereas excessive switching in OCD arises from diminished belief updating about choice-outcome associations.</p>","PeriodicalId":72664,"journal":{"name":"Computational psychiatry (Cambridge, Mass.)","volume":"10 1","pages":"104-120"},"PeriodicalIF":0.0,"publicationDate":"2026-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13308528/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148347239","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Neural Bases of Affect-Based Impulsivity: A Decision Neuroscience Account.","authors":"Alison M Schreiber, Michael N Hallquist","doi":"10.5334/cpsy.159","DOIUrl":"10.5334/cpsy.159","url":null,"abstract":"<p><p>Affect-based impulsivity describes the tendency to behave impulsively while experiencing negative or positive affective states. In the context of psychiatric disorders, the consequences of affect-based impulsivity can be dire, including suicidal behavior and harmful substance use. Here, we provide a narrative review and articulate a decision neuroscience account of affect-based impulsivity. We focus specifically on how negative emotions alter the balance of Pavlovian and goal-directed decision systems. We consider how negative affect influences <i>whether</i> to act, <i>what</i> actions to consider, <i>which</i> action to select, and <i>how</i> vigorously to engage in a selected action. Further, we describe the neural and neuroendocrine bases of these computations. We propose that modulation of norepinephrine and glucocorticoids during negative affective states enhances the pursuit of rewards by reducing goal-directed computations and increasing appetitive Pavlovian computations.</p>","PeriodicalId":72664,"journal":{"name":"Computational psychiatry (Cambridge, Mass.)","volume":"10 1","pages":"85-103"},"PeriodicalIF":0.0,"publicationDate":"2026-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13109919/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147790733","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Anhedonic Traits Do Not Impair Performance in a 3-Arm Bandit Task.","authors":"Arjun Ramaswamy, Yumeya Yamamori, Umesh Vivekananda, Vladimir Litvak, Jonathan P Roiser","doi":"10.5334/cpsy.135","DOIUrl":"10.5334/cpsy.135","url":null,"abstract":"<p><p>Anhedonia, a transdiagnostic symptom marked by diminished reward sensitivity, is often linked to impairments in reinforcement learning (RL). Standard tasks (e.g., the 4-arm bandit) can place substantial demands on participants and may blur valuation with other processes. We therefore adapted a three-arm bandit (3AB) task from Seymour et al. (2012), incorporating design features intended to lessen task demands (fewer options; denser feedback) while enabling separate estimation of reward and punishment learning rates and sensitivities. In an online sample pre-screened for anhedonia (N = 206; 111 anhedonic, 95 non-anhedonic), hierarchical Bayesian modelling using a four-parameter specification showed no credible group differences in reward learning rate, punishment learning rate, reward sensitivity, or punishment sensitivity; Bayes factors favoured the null (BF₀₁ = 3.36-5.96). Model-agnostic win-stay/lose-shift strategies likewise showed no group differences (Welch's tests, all p > .05). Posterior predictive checks indicated above-chance choice prediction: the model's highest-probability action matched participants' actual choices on 59.6% of trials (chance = 33%). Parameter recovery was excellent for valuation parameters (r = 0.96-0.97) and acceptable for learning rates (r = 0.67-0.85). Simulations generated from fitted parameters preserved individual-difference structure, with high correlations between observed and simulated win-stay (r = 0.89 anhedonic; 0.86 non-anhedonic) and moderate correlations for lose-shift (r = 0.62; 0.67), alongside small systematic mean-level biases (simulated win-stay lower by 3.5-4.9 percentage points; simulated lose-shift higher by 12.8-13.2 points). Model comparison showed that lapse-augmented variants achieved marginally better predictive fit, but group comparisons under both lapse models yielded overlapping posteriors with 95% HDIs including zero for all learning, sensitivity, and lapse parameters, indicating that the null findings were robust to inclusion of lapse terms. Non-anhedonic participants also responded more slowly on average than anhedonic participants, which we treat as exploratory. Together, these results suggest that in this 3AB task, anhedonia is not reliably associated with differences in core RL parameters or simple choice strategies, while providing a detailed characterisation of model performance and limitations in an online setting.</p>","PeriodicalId":72664,"journal":{"name":"Computational psychiatry (Cambridge, Mass.)","volume":"10 1","pages":"58-84"},"PeriodicalIF":0.0,"publicationDate":"2026-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13089363/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147724760","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Role of Alexithymia in Social Learning and Feedback-Driven Social Inferences.","authors":"Mina Hosseinnezhad, Soroosh Golbabaei, Mohammad Reza Bigham, Khatereh Borhani","doi":"10.5334/cpsy.153","DOIUrl":"10.5334/cpsy.153","url":null,"abstract":"<p><p>Dynamic social interactions and feedback are crucial for understanding others' emotions, particularly when confronted with contradictory emotional cues. Alexithymia, a condition that co-occurs with many psychiatric disorders, is characterized by impairment in emotional processing. However, computational mechanisms by which it alters social inferences based on feedback cues remain unexplored. To examine this, 60 participants with low and high levels of alexithymia completed an emotional learning task involving contradictory social (verbal and visual) cues to infer targets' emotions. Computational analyses, including bin-based, reinforcement learning, and drift-diffusion modeling, revealed how alexithymia alters latent parameters that govern value updating and choice. Individuals with high alexithymia demonstrated lower accuracy in learning from social feedback, and learning rate for verbal cues was negatively associated with difficulties in identifying and describing feelings. Drift diffusion analysis revealed a perceptual bias toward the visual cue, with higher drift rates and bias in the visual-correct condition, and a general requirement for greater evidence accumulation to infer others' emotions. These findings suggest that individuals with high alexithymia exhibit impaired social learning and difficulty with decision-making in situations with conflicting social information, with computational modeling quantifying the latent processes involved and advancing mechanistic targets for computational psychiatry.</p>","PeriodicalId":72664,"journal":{"name":"Computational psychiatry (Cambridge, Mass.)","volume":"10 1","pages":"35-57"},"PeriodicalIF":0.0,"publicationDate":"2026-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13004067/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147500514","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Self-Reflection Protects Behavior from Volatile Beliefs Linked to Paranoia.","authors":"Praveen Suthaharan, Santiago Castiello, Yuen-Siang Ang, Phil Corlett","doi":"10.5334/cpsy.150","DOIUrl":"10.5334/cpsy.150","url":null,"abstract":"<p><p>Processing uncertainty may be pathognomonic (characteristic of a disease) for some psychiatric conditions. Some people expect the world to change, even when it doesn't. This tendency is central to paranoia, where individuals often anticipate threat or change without clear evidence. But what determines whether these beliefs translate into behavior? One possibility is that metacognitive structure - the coherence and depth with which one articulates their own thinking - acts as a buffer. An agent may endorse a belief but have sufficient accessory hypotheses to insulate it from action. To test this, we used metacognitive prompting in GPT-4 to score individual reflections on open-ended questions (e.g., <i>did you use any particular strategy?</i>) after completing a probabilistic reversal learning task. Individuals with higher paranoia demonstrate lower metacognitive structure (<i>t</i> = 5.98, <i>p</i> < 0.001), with metacognition attenuating the relationship between volatility belief and switching behavior (Δ = -15 pp, <i>p</i> < 0.001) even after controlling for reflection verbosity and general cognitive ability. These findings suggest that metacognition protects against uncertainty-driven instability, pointing to a key mechanism by which reflection protects against cognition under change. This work provides a novel framework to measure metacognition from behavioral task debrief questions.</p>","PeriodicalId":72664,"journal":{"name":"Computational psychiatry (Cambridge, Mass.)","volume":"10 1","pages":"18-34"},"PeriodicalIF":0.0,"publicationDate":"2026-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12922661/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147273235","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}