Michal M. Graczyk , Rudolf N. Cardinal , Tsen Vei Lim , Salvatore Nigro , Elijah Mak , Karen D. Ersche
{"title":"Deconstructing Delay Discounting in Human Cocaine Addiction Using Computational Modeling and Neuroimaging","authors":"Michal M. Graczyk , Rudolf N. Cardinal , Tsen Vei Lim , Salvatore Nigro , Elijah Mak , Karen D. Ersche","doi":"10.1016/j.bpsc.2024.12.010","DOIUrl":null,"url":null,"abstract":"<div><h3>Background</h3><div>A preference for sooner-smaller over later-larger rewards, known as delay discounting, is a candidate transdiagnostic marker of waiting impulsivity and a research domain criterion. While abnormal discounting rates have been associated with many psychiatric diagnoses and abnormal brain structure, the underlying neuropsychological processes remain largely unknown. Here, we deconstruct delay discounting into choice and rate processes by testing different computational models and investigate their associations with white matter tracts.</div></div><div><h3>Methods</h3><div>Patients with cocaine use disorder (CUD) (<em>n</em> = 107) and healthy participants (<em>n</em> = 81) completed the Monetary Choice Questionnaire. We computed their discounting rate using the well-known Kirby method, as well as logistic regression, single-subject Bayesian, and full hierarchical Bayesian models. In Bayesian models, we also included a choice sharpness parameter. Seventy patients with CUD and 69 healthy participants also underwent diffusion tensor imaging tractography to quantify streamlines that connect the executive control and valuation brain networks.</div></div><div><h3>Results</h3><div>Patients with CUD showed significantly higher discounting rates and lower choice sharpness, suggesting greater indifference in their choices. Importantly, the full Bayesian model had the greatest reliability for parameter recovery when compared to the Kirby and logistic regression methods. Using Bayesian estimates, we found that white matter streamlines that connect the executive control network with the nucleus accumbens predicted the discounting rate in healthy participants but not in patients with CUD.</div></div><div><h3>Conclusions</h3><div>We demonstrated that measuring delay discounting and choice sharpness directly with a novel computational model explained impulsive discounting choices in patients with CUD better than standard hyperbolic discounting. Our findings highlight a distinct neuropsychological phenotype of impulsive discounting, which may be generalizable to other patient groups.</div></div>","PeriodicalId":54231,"journal":{"name":"Biological Psychiatry-Cognitive Neuroscience and Neuroimaging","volume":"10 8","pages":"Pages 856-864"},"PeriodicalIF":4.8000,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Biological Psychiatry-Cognitive Neuroscience and Neuroimaging","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2451902224003859","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"NEUROSCIENCES","Score":null,"Total":0}
引用次数: 0
Abstract
Background
A preference for sooner-smaller over later-larger rewards, known as delay discounting, is a candidate transdiagnostic marker of waiting impulsivity and a research domain criterion. While abnormal discounting rates have been associated with many psychiatric diagnoses and abnormal brain structure, the underlying neuropsychological processes remain largely unknown. Here, we deconstruct delay discounting into choice and rate processes by testing different computational models and investigate their associations with white matter tracts.
Methods
Patients with cocaine use disorder (CUD) (n = 107) and healthy participants (n = 81) completed the Monetary Choice Questionnaire. We computed their discounting rate using the well-known Kirby method, as well as logistic regression, single-subject Bayesian, and full hierarchical Bayesian models. In Bayesian models, we also included a choice sharpness parameter. Seventy patients with CUD and 69 healthy participants also underwent diffusion tensor imaging tractography to quantify streamlines that connect the executive control and valuation brain networks.
Results
Patients with CUD showed significantly higher discounting rates and lower choice sharpness, suggesting greater indifference in their choices. Importantly, the full Bayesian model had the greatest reliability for parameter recovery when compared to the Kirby and logistic regression methods. Using Bayesian estimates, we found that white matter streamlines that connect the executive control network with the nucleus accumbens predicted the discounting rate in healthy participants but not in patients with CUD.
Conclusions
We demonstrated that measuring delay discounting and choice sharpness directly with a novel computational model explained impulsive discounting choices in patients with CUD better than standard hyperbolic discounting. Our findings highlight a distinct neuropsychological phenotype of impulsive discounting, which may be generalizable to other patient groups.
期刊介绍:
Biological Psychiatry: Cognitive Neuroscience and Neuroimaging is an official journal of the Society for Biological Psychiatry, whose purpose is to promote excellence in scientific research and education in fields that investigate the nature, causes, mechanisms, and treatments of disorders of thought, emotion, or behavior. In accord with this mission, this peer-reviewed, rapid-publication, international journal focuses on studies using the tools and constructs of cognitive neuroscience, including the full range of non-invasive neuroimaging and human extra- and intracranial physiological recording methodologies. It publishes both basic and clinical studies, including those that incorporate genetic data, pharmacological challenges, and computational modeling approaches. The journal publishes novel results of original research which represent an important new lead or significant impact on the field. Reviews and commentaries that focus on topics of current research and interest are also encouraged.