Computational psychiatry (Cambridge, Mass.)最新文献_第4页

The Computational and Neural Substrates of Ambiguity Avoidance in Anxiety. 焦虑症中模糊性规避的计算和神经基础》（The Computational and Neural Substrates of Ambiguity Avoidance in Anxiety.

Computational psychiatry (Cambridge, Mass.) Pub Date : 2022-01-01 Epub Date: 2022-02-03 DOI: 10.5334/cpsy.67

Emma L Lawrance, Christopher R Gagne, Jill X O'Reilly, Janine Bijsterbosch, Sonia J Bishop

{"title":"The Computational and Neural Substrates of Ambiguity Avoidance in Anxiety.","authors":"Emma L Lawrance, Christopher R Gagne, Jill X O'Reilly, Janine Bijsterbosch, Sonia J Bishop","doi":"10.5334/cpsy.67","DOIUrl":"10.5334/cpsy.67","url":null,"abstract":"Theoretical accounts have linked anxiety to intolerance of ambiguity. However, this relationship has not been well operationalized empirically. Here, we used computational and neuro-imaging methods to characterize anxiety-related differences in aversive decision-making under ambiguity and associated patterns of cortical activity. Adult human participants chose between two urns on each trial. The ratio of tokens ('O's and 'X's) in each urn determined probability of electrical stimulation receipt. A number above each urn indicated the magnitude of stimulation that would be received if a shock was delivered. On ambiguous trials, one of the two urns had tokens occluded. By varying the number of tokens occluded, we manipulated the extent of missing information. At higher levels of missing information, there is greater second order uncertainty, i.e., more uncertainty as to the probability of pulling a given type of token from the urn. Adult human participants demonstrated avoidance of ambiguous options which increased with level of missing information. Extent of 'information-level dependent' ambiguity aversion was significantly positively correlated with trait anxiety. Activity in both the dorsal anterior cingulate cortex and inferior frontal sulcus during the decision-making period increased as a function of missing information. Greater engagement of these regions, on high missing information trials, was observed when participants went on to select the ambiguous option; this was especially apparent in high trait anxious individuals. These findings are consistent with individuals vulnerable to anxiety requiring greater activation of frontal regions supporting rational decision-making to overcome a predisposition to engage in ambiguity avoidance at high levels of missing information.","PeriodicalId":72664,"journal":{"name":"Computational psychiatry (Cambridge, Mass.)","volume":" ","pages":"8-33"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9223033/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40403396","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}

引用次数: 0

Reduced Context Updating but Intact Visual Priors in Autism. 自闭症患者情境更新减少但视觉先验完好无损

Computational psychiatry (Cambridge, Mass.) Pub Date : 2021-12-29 eCollection Date: 2021-01-01 DOI: 10.5334/cpsy.69

R Randeniya, I Vilares, J B Mattingley, M I Garrido

{"title":"Reduced Context Updating but Intact Visual Priors in Autism.","authors":"R Randeniya, I Vilares, J B Mattingley, M I Garrido","doi":"10.5334/cpsy.69","DOIUrl":"10.5334/cpsy.69","url":null,"abstract":"A general consensus persists that sensory-perceptual differences in autism, such as hypersensitivities to light or sound, result from an overreliance on new (rather than prior) sensory observations. However, conflicting Bayesian accounts of autism remain unresolved as to whether such alterations are caused by more precise sensory observations (precise likelihood model) or by forming a less precise model of the sensory context (hypo-priors model). We used a decision-under-uncertainty paradigm that manipulated uncertainty in both likelihoods and priors. Contrary to model predictions we found no differences in reliance on likelihood in autistic group (AS) compared to neurotypicals (NT) and found no differences in subjective prior variance between groups. However, we found reduced context adjustment in the AS group compared to NT. Further, the AS group showed heightened variability in their relative weighting of sensory information (vs. prior) on a trial-by-trial basis. When participants were aligned on a continuum of autistic traits, we found no associations with likelihood reliance or prior variance but found an increase in likelihood precision with autistic traits. These findings together provide empirical evidence for intact priors, precise likelihood, reduced context updating and heightened variability during sensory learning in autism.","PeriodicalId":72664,"journal":{"name":"Computational psychiatry (Cambridge, Mass.)","volume":"5 1","pages":"140-158"},"PeriodicalIF":0.0,"publicationDate":"2021-12-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11104295/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141077383","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}

引用次数: 0

Economic Decisions with Ambiguous Outcome Magnitudes Vary with Low and High Stakes but Not Trait Anxiety or Depression. 结果幅度不明确的经济决策会随着低风险和高风险而变化，但不会影响特质焦虑或抑郁。

Computational psychiatry (Cambridge, Mass.) Pub Date : 2021-10-21 eCollection Date: 2021-01-01 DOI: 10.5334/cpsy.79

Tomislav D Zbozinek, Caroline J Charpentier, Song Qi, Dean Mobbs

{"title":"Economic Decisions with Ambiguous Outcome Magnitudes Vary with Low and High Stakes but Not Trait Anxiety or Depression.","authors":"Tomislav D Zbozinek, Caroline J Charpentier, Song Qi, Dean Mobbs","doi":"10.5334/cpsy.79","DOIUrl":"10.5334/cpsy.79","url":null,"abstract":"Most of life's decisions involve risk and uncertainty regarding whether reward or loss will follow. Decision makers often face uncertainty not only about the likelihood of outcomes (what are the chances that I will get a raise if I ask my supervisor? What are the chances that my supervisor will be upset with me for asking?) but also the magnitude of outcomes (if I do get a raise, how large will it be? If my supervisor gets upset, how bad will the consequences be for me?). Only a few studies have investigated economic decision making with ambiguous likelihoods, and even fewer have investigated ambiguous outcome magnitudes. In the present report, we investigated the effects of ambiguous outcome magnitude, risk, and gains/losses in an economic decision-making task with low stakes (Study 1; $3.60-$5.70; N = 367) and high stakes (Study 2; $6-$48; N = 210) using a within-subjects design. We conducted computational modeling to determine individuals' preferences/aversions for ambiguous outcome magnitudes, risk, and gains/losses. We additionally investigated the association between trait anxiety and trait depression and decision-making parameters. Our results show that increasing stakes increased ambiguous gain aversion and unambiguous risk aversion but increased ambiguous sure loss preference; participants also became more averse to ambiguous sure gains relative to unambiguous risky gains. There were no significant effects of trait anxiety or trait depression on economic decision making. Our results suggest that as stakes increase, people tend to avoid uncertainty in the gain domain (especially ambiguous gains) but prefer ambiguous vs unambiguous sure losses.","PeriodicalId":72664,"journal":{"name":"Computational psychiatry (Cambridge, Mass.)","volume":"5 1","pages":"119-139"},"PeriodicalIF":0.0,"publicationDate":"2021-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11104296/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141077381","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}

引用次数: 0

Slower Learning Rates from Negative Outcomes in Substance Use Disorder over a 1-Year Period and their Potential Predictive Utility 1年内药物使用障碍负面结果的学习率降低及其潜在的预测效用

Computational psychiatry (Cambridge, Mass.) Pub Date : 2021-10-19 DOI: 10.1101/2021.10.18.21265152

Ryan Smith, S. Taylor, J. Stewart, S. Guinjoan, M. Ironside, N. Kirlic, H. Ekhtiari, Evan J. White, Haixia Zheng, R. Kuplicki, M. Paulus

{"title":"Slower Learning Rates from Negative Outcomes in Substance Use Disorder over a 1-Year Period and their Potential Predictive Utility","authors":"Ryan Smith, S. Taylor, J. Stewart, S. Guinjoan, M. Ironside, N. Kirlic, H. Ekhtiari, Evan J. White, Haixia Zheng, R. Kuplicki, M. Paulus","doi":"10.1101/2021.10.18.21265152","DOIUrl":"https://doi.org/10.1101/2021.10.18.21265152","url":null,"abstract":"Computational modelling is a promising approach to parse dysfunctional cognitive processes in substance use disorders (SUDs), but it is unclear how much these processes change during the recovery period. We assessed 1-year follow-up data on a sample of treatment-seeking individuals with one or more SUDs (alcohol, cannabis, sedatives, stimulants, hallucinogens, and/or opioids; N = 83) that were previously assessed at baseline within a prior computational modelling study. Relative to healthy controls (HCs; N = 48), these participants were found at baseline to show altered learning rates and less precise action selection while completing an explore-exploit decision-making task. Here we replicate these analyses when these individuals returned and re-performed the task 1 year later to assess the stability of these baseline differences. We also examine whether baseline modelling measures can predict symptoms at follow-up. Bayesian analyses indicate that: (a) group differences in learning rates were stable over time (posterior probability = 1); (b) intra-class correlations (ICCs) between model parameters at baseline and follow-up were significant and ranged from small to moderate (.25 < ICCs < .54); and (c) learning rates and/or information-seeking values at baseline were associated with substance use severity at 1-year follow-up in stimulant and opioid users (.36 < rs < .43, .002 < ps < .02). These findings suggest that learning dysfunctions are moderately stable during recovery and could correspond to trait-like vulnerability factors. In addition, computational measures at baseline had some predictive value for changes in substance use severity over time and could be clinically informative.","PeriodicalId":72664,"journal":{"name":"Computational psychiatry (Cambridge, Mass.)","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45695457","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 15

Multi-Round Trust Game Quantifies Inter-Individual Differences in Social Exchange from Adolescence to Adulthood. 多轮信任博弈量化青少年至成年社会交换的个体间差异。

Computational psychiatry (Cambridge, Mass.) Pub Date : 2021-10-14 DOI: 10.5334/cpsy.65

Andreas Hula, Michael Moutoussis, Geert-Jan Will, Danae Kokorikou, Andrea M Reiter, Gabriel Ziegler, E D Bullmore, Peter B Jones, Ian Goodyer, Peter Fonagy, P Read Montague, Raymond J Dolan

{"title":"Multi-Round Trust Game Quantifies Inter-Individual Differences in Social Exchange from Adolescence to Adulthood.","authors":"Andreas Hula, Michael Moutoussis, Geert-Jan Will, Danae Kokorikou, Andrea M Reiter, Gabriel Ziegler, E D Bullmore, Peter B Jones, Ian Goodyer, Peter Fonagy, P Read Montague, Raymond J Dolan","doi":"10.5334/cpsy.65","DOIUrl":"10.5334/cpsy.65","url":null,"abstract":"Investing in strangers in a socio-economic exchange is risky, as we may be uncertain whether they will reciprocate. Nevertheless, the potential rewards for cooperating can be great. Here, we used a cross sectional sample (n = 784) to study how the challenges of cooperation versus defection are negotiated across an important period of the lifespan: from adolescence to young adulthood (ages 14 to 25). We quantified social behaviour using a multi round investor-trustee task, phenotyping individuals using a validated model whose parameters characterise patterns of real exchange and constitute latent social characteristics. We found highly significant differences in investment behaviour according to age, sex, socio-economic status and IQ. Consistent with the literature, we showed an overall trend towards higher trust from adolescence to young adulthood but, in a novel finding, we characterized key cognitive mechanisms explaining this, especially regarding socio-economic risk aversion. Males showed lower risk-aversion, associated with greater investments. We also found that inequality aversion was higher in females and, in a novel relation, that socio-economic deprivation was associated with more risk averse play.","PeriodicalId":72664,"journal":{"name":"Computational psychiatry (Cambridge, Mass.)","volume":"5 1","pages":"102-118"},"PeriodicalIF":0.0,"publicationDate":"2021-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7612797/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89720923","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}

引用次数: 0

Enhancing the Psychometric Properties of the Iowa Gambling Task Using Full Generative Modeling. 利用全生成模型增强爱荷华赌博任务的心理测量特性。

Computational psychiatry (Cambridge, Mass.) Pub Date : 2021-10-11 DOI: 10.31234/osf.io/yxbjz

Holly Sullivan-Toole, Nathaniel Haines, K. Dale, T. Olino

{"title":"Enhancing the Psychometric Properties of the Iowa Gambling Task Using Full Generative Modeling.","authors":"Holly Sullivan-Toole, Nathaniel Haines, K. Dale, T. Olino","doi":"10.31234/osf.io/yxbjz","DOIUrl":"https://doi.org/10.31234/osf.io/yxbjz","url":null,"abstract":"Poor psychometrics, particularly low test-retest reliability, pose a major challenge for using behavioral tasks in individual differences research. Here, we demonstrate that full generative modeling of the Iowa Gambling Task (IGT) substantially improves test-retest reliability and may also enhance the IGT's validity for use in characterizing internalizing pathology, compared to the traditional analytic approach. IGT data (n=50) was collected across two sessions, one month apart. Our full generative model incorporated (1) the Outcome Representation Learning (ORL) computational model at the person-level and (2) a group-level model that explicitly modeled test-retest reliability, along with other group-level effects. Compared to the traditional 'summary score' (proportion good decks selected), the ORL model provides a theoretically rich set of performance metrics (Reward Learning Rate (A+), Punishment Learning Rate (A-), Win Frequency Sensitivity (βf), Perseveration Tendency (βp), Memory Decay (K)), capturing distinct psychological processes. While test-retest reliability for the traditional summary score was only moderate (r=.37, BCa 95% CI [.04, .63]), test-retest reliabilities for ORL performance metrics produced by the full generative model were substantially improved, with test-retest correlations ranging between r=.64-.82 for the five ORL parameters. Further, while summary scores showed no substantial associations with internalizing symptoms, ORL parameters were significantly associated with internalizing symptoms. Specifically, Punishment Learning Rate was associated with higher self-reported depression and Perseveration Tendency was associated with lower self-reported anhedonia. Generative modeling offers promise for advancing individual differences research using the IGT, and behavioral tasks more generally, through enhancing task psychometrics.","PeriodicalId":72664,"journal":{"name":"Computational psychiatry (Cambridge, Mass.)","volume":"6 1 1","pages":"189-212"},"PeriodicalIF":0.0,"publicationDate":"2021-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46251145","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4

A Competition of Critics in Human Decision-Making. 人类决策中的批评家之争。

Computational psychiatry (Cambridge, Mass.) Pub Date : 2021-08-12 eCollection Date: 2021-01-01 DOI: 10.5334/cpsy.64

Enkhzaya Enkhtaivan, Joel Nishimura, Cheng Ly, Amy L Cochran

{"title":"A Competition of Critics in Human Decision-Making.","authors":"Enkhzaya Enkhtaivan, Joel Nishimura, Cheng Ly, Amy L Cochran","doi":"10.5334/cpsy.64","DOIUrl":"10.5334/cpsy.64","url":null,"abstract":"Recent experiments and theories of human decision-making suggest positive and negative errors are processed and encoded differently by serotonin and dopamine, with serotonin possibly serving to oppose dopamine and protect against risky decisions. We introduce a temporal difference (TD) model of human decision-making to account for these features. Our model involves two critics, an optimistic learning system and a pessimistic learning system, whose predictions are integrated in time to control how potential decisions compete to be selected. Our model predicts that human decision-making can be decomposed along two dimensions: the degree to which the individual is sensitive to (1) risk and (2) uncertainty. In addition, we demonstrate that the model can learn about the mean and standard deviation of rewards, and provide information about reaction time despite not modeling these variables directly. Lastly, we simulate a recent experiment to show how updates of the two learning systems could relate to dopamine and serotonin transients, thereby providing a mathematical formalism to serotonin's hypothesized role as an opponent to dopamine. This new model should be useful for future experiments on human decision-making.","PeriodicalId":72664,"journal":{"name":"Computational psychiatry (Cambridge, Mass.)","volume":"5 1","pages":"81-101"},"PeriodicalIF":0.0,"publicationDate":"2021-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11104313/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141077543","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}

引用次数: 0

A Computational Model of Non-optimal Suspiciousness in the Minnesota Trust Game 明尼苏达信任博弈中非最优可疑性的计算模型

Computational psychiatry (Cambridge, Mass.) Pub Date : 2021-06-30 DOI: 10.31234/osf.io/kwe8p

R. Kazinka, I. Vilares, A. MacDonald

{"title":"A Computational Model of Non-optimal Suspiciousness in the Minnesota Trust Game","authors":"R. Kazinka, I. Vilares, A. MacDonald","doi":"10.31234/osf.io/kwe8p","DOIUrl":"https://doi.org/10.31234/osf.io/kwe8p","url":null,"abstract":"This study modeled spite sensitivity (the worry that others are willing to incur a loss to hurt you), which is thought to undergird suspiciousness and persecutory ideation. Two samples performed a parametric, non-iterative trust game known as the Minnesota Trust Game (MTG). The MTG is designed to distinguish suspicious decision-making from otherwise rational mistrust by incentivizing the player to trust in certain situations. Individuals who do not trust even under these circumstances are particularly suspicious of their potential partner’s intentions. In Sample 1, 243 undergraduates who completed the MTG showed less trust as the amount of money they could lose increased. However, for choices where partners had a financial disincentive to betray the player, variation in the willingness to trust the partner was associated with suspicious beliefs. To further examine spite sensitivity, we modified the Fehr-Schmidt (1999) inequity aversion model, which compares unequal outcomes in social decision-making tasks, to include the possibility for spite sensitivity. In this case, an anticipated partner’s dislike of advantageous inequity (i.e., guilt) parameter could take on negative values, with negative guilt indicating spite. We hypothesized that the anticipated guilt parameter would be strongly related to suspicious beliefs. Our modification of the Fehr-Schmidt model improved estimation of MTG behavior. We isolated the estimation of partner’s spite-guilt, which was highly correlated with choices most associated with persecutory ideation. We replicated our findings in a second sample, where the estimated spite-guilt parameter correlated with self-reported suspiciousness. The “Suspiciousness” condition, unique to the MTG, can be modeled to isolate spite sensitivity, suggesting that spite sensitivity is separate from inequity aversion or risk aversion, and may provide a means to quantify persecution. The MTG offers promise for future studies to quantify persecutory beliefs in clinical populations.","PeriodicalId":72664,"journal":{"name":"Computational psychiatry (Cambridge, Mass.)","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48724317","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Antisocial Learning: Using Learning Window Width to Model Callous-Unemotional Traits? 反社会学习:用学习窗口宽度来模拟冷酷无情的性格特征?

Computational psychiatry (Cambridge, Mass.) Pub Date : 2021-05-31 eCollection Date: 2021-01-01 DOI: 10.5334/cpsy.68

Caroline Moul, Oliver J Robinson, Evan J Livesey

引用次数: 0

The Reward-Complexity Trade-off in Schizophrenia. 精神分裂症的奖赏-复杂性权衡。

Computational psychiatry (Cambridge, Mass.) Pub Date : 2021-05-25 eCollection Date: 2021-01-01 DOI: 10.5334/cpsy.71

Samuel J Gershman, Lucy Lai

引用次数: 0