A neurocognitive and computational study of inhibitory control in substance use

描述(申请人提供)：兴奋剂滥用和依赖是美国年轻人面临的严重问题。大约20%的年轻人报告在18-20岁之间使用过非法药物，大约七分之一的受试者开始使用兴奋剂，最终导致依赖。有强有力的证据表明，药物使用和依赖与抑制控制缺陷有关。然而，这种去抑制性精神病理学背后的基本认知和神经过程却知之甚少。该项目的长期目标是描述临时兴奋剂使用者抑制性失调的神经起源和行为后果，这将对开发新的工具来识别高危个体、预防性干预以及行为和药物补救具有价值。具体目的是(1)调查刺激剂使用者和正常对照组之间的认知差异，特别是评估刺激剂使用者错误加工和/或时间知觉改变有助于抑制控制受损的假说；(2)确定不同大脑区域在停止行为中的不同贡献，以及刺激剂使用者和匹配对照组之间的神经生理学差异；(3)揭示预测临时刺激剂使用者最终是否会产生依赖使用的早期行为和神经生理标记物。为了实现目标1，一个新颖的抑制控制的量化模型，区分了各种认知过程的贡献，如感觉辨别、时间知觉、奖赏/错误加工、学习和适应，将被用来分析刺激剂使用者和执行停止信号范式的匹配控制。为了实现目标2，与目标1的量化模型的不同认知过程相对应的受试者和试验特定的参数回归变量将被用来识别各种认知过程的神经底物(使用功能磁共振数据)，并表征刺激剂使用者和匹配物对照组之间的任何神经生理差异。为了实现目标3，为期三年的跟踪调查将与最初的功能磁共振成像/行为实验中收集的行为和神经生理指标相关联，以确定预测从临时使用转向依赖的早期行为和神经生理标记物。行为和功能磁共振数据已经在另一项拨款下收集；由另一项拨款资助的后续调查将很快完成。 公共卫生相关性：兴奋剂滥用和依赖是年轻人中的重大问题，因此必须确定兴奋剂使用的致病因素，以及问题使用中认知缺陷的性质，以便制定更强大的诊断、预防和补救程序。在这个项目中，将开发一个复杂的、新颖的、量化的抑制控制模型，产生一套丰富的认知和行为测量方法，可以表征兴奋剂使用者和对照人群在药物使用和成瘾的不同阶段的细微差异。该模型将应用于随意兴奋剂使用者和匹配的对照组受试者的大量行为和功能MRI数据，目的是识别最能预测个人最终是否上瘾的行为和神经特征。

DESCRIPTION (provided by applicant): Stimulant abuse and dependence are significant problems facing young adults in the United States. Around 20% of young adults report the use of illicit drugs between the ages of 18-20 years, and approximately one in seven subjects initiating stimulant use progress eventually to dependence. There is strong evidence that drug use and dependence are associated with deficits in inhibitory control. However, the basic cognitive and neural processes underlying such disinhibitory psychopathology are poorly understood. The long-term goal of this project is to delineate the neural provenance and behavioral consequence of inhibitory dysregulation in casual stimulant users, which would be valuable for developing novel tools for the identification of at-risk individuals, for preventative intervention, and for behavioral and pharmacological remediation. The specific aims are (1) to investigate the cognitive differences between stimulant users and normal controls, specifically evaluating the hypotheses that altered error processing and/or temporal perception in stimulant users contribute to impaired inhibitory control, (2) to identify the differential contributions of various brain regions in stopping behavior, as well as neurophysiological differences between stimulant users and matched controls, and (3) to uncover early behavioral and neurophysiological markers that predict whether a casual stimulant user will eventually develop dependent use or not. To achieve Aim 1, a novel, quantitative model for inhibitory control, differentiating the contributions of various cognitive processes such as sensory discrimination, temporal perception, reward/error processing, learning and adaptation, will be used to analyze stimulant users and matched controls performing the stop signal paradigm. To achieve Aim 2, subject- and trial-specific parametric regressors, corresponding to distinct cognitive processes of the quantitative model of Aim 1, will be used to identify the neural substrate (using fMRI data) of the various cognitive processes, and to characterize any neurophysiological differences between stimulant users and matches controls. To achieve Aim 3, three-year follow-up surveys, indicating which casual users eventually develop dependence, will be correlated with behavioral and neurophysiological measures collected in the original fMRI/behavioral experiments, to identify early behavioral and neurophysiological markers that predict transition from casual use to dependence. The behavioral and fMRI data have already been collected under a different grant; the follow-up survey, funded by another grant, will soon be completed. PUBLIC HEALTH RELEVANCE: Stimulant abuse and dependence are significant problems among young adults, making it imperative to identify the causative factors for stimulant use, as well as the nature of cognitive deficits in problem use, in order to develop more powerful diagnostic, preventative, and remedial procedures. In this project, a sophisticated, novel, quantitative model of inhibitory control will be developed, yielding a rich set of cognitive and behavioral measures that can characterizes subtle differences between stimulant users and control populations at different stages of drug use and addiction. The model will be applied to a large set of behavioral and functional MRI data of casual stimulant users and matched control subjects, with the goal of identifying behavioral and neural features that best predict whether an individual eventually develops addiction or not.