Defining neurobiological links between substance use and mental illness

定义物质使用和精神疾病之间的神经生物学联系

• 批准号: 10928587
• 负责人: Amy Janes
• 金额: $ 251.24万
• 依托单位: NATIONAL INSTITUTE ON DRUG ABUSE
• 依托单位国家: 美国
• 资助国家: 美国
• 起止时间: 至
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10928587
• 关键词: Abstinence; Adult; Alcohol dependence; Biological; Blood; Blood flow; Brain; Brain Mapping; Brain region; Choice Behavior; Chronic; Cigarette; Clinical; Cognition; Collaborations; Communication; Computer Analysis; Computer Models; Data; Data Collection; Decision Making; Detection; Development; Diffusion; Disease; Disease remission; Dissociation; Drug Addiction; Economics; Elements; Excision; Functional Magnetic Resonance Imaging; Goals; Health; Human; Impaired cognition; Individual; Laboratories; Learning; Link; Literature; Major Depressive Disorder; Manuscripts; Measures; Mental Health; Mental disorders; Methods; Modeling; National Institute of Drug Abuse; Neurobiology; Neurosciences; Nicotine; Nicotine Dependence; Nicotinic Agonists; Nicotinic Antagonists; Outcome; Participant; Pattern; Persons; Pharmaceutical Preparations; Phase; Population; Process; Property; Public Health; Publishing; Recommendation; Reinforcement Schedule; Relapse; Rest; Rewards; Risk; Signal Transduction; Smoke; Smoking; Substance Use Disorder; Substance of Abuse; Testing; Time; Tobacco smoking behavior; Variant; Work; analog; cigarette smoke; cognitive control; cohort; comorbidity; connectome; decision-making capacity; denoising; depressive symptoms; design; hemodynamics; improved; innovation; meetings; neuroadaptation; neurotransmission; nicotine use; non-smoker; novel; preventable death; recruit; response; reward anticipation; reward processing; sex; smoking abstinence; substance use

Dr. Janes continued to grow her newly established lab and began data collection at NID-IRP. She focused on staff recruitment and published 2 manuscripts, which are described below. 1. Wanger T, Janes AC, Frederick BF 2023. Spatial variation of changes in test-retest reliability of functional connectivity after global signal regression: the effect of considering hemodynamic delay. Human Brain Mapping Global signal regression (GSR) is a controversial analysis method, since its removal of signal has been observed to reduce the reliability of functional connectivity estimates. Here, we used test-retest reliability to characterize potential differences in spatial patterns between conventional, static GSR (sGSR) and a novel dynamic form of GSR (dGSR). In contrast with sGSR, dGSR models the global signal at a time delay to correct for blood arrival time. Thus, dGSR accounts for greater variation in global signal, removes blood-flow-related nuisance signal, and leaves higher quality neuronal signal remaining. We used intraclass correlation coefficients (ICCs) to estimate the reliability of functional connectivity in 462 healthy controls from the Human Connectome Project. We tested across two factors: denoising method used (control, sGSR, and dGSR), and interacquisition interval (between days, or within session while varying phase encoding direction). Reliability was estimated regionally to identify topographic patterns for each condition. sGSR and dGSR provided global reductions in reliability compared with the non-GSR control. Test-retest reliability was highest in the frontoparietal and default mode regions, and lowest in sensorimotor cortex for all conditions. dGSR provides more effective denoising in regions where both strategies greatly reduce reliability. Both GSR methods substantially reduced test-retest reliability, which was most evident in brain regions that had low reliability prior to denoising. These findings suggest that reliability of interregional correlation is likely inflated by the global signal, which is thought to primarily reflect dynamic blood flow. 2. Biernacki K, Molokotos E, Han C, Dillon D, Leventhal AM, Janes AC (In Press). Enhanced decision-making in nicotine dependent individuals who abstain: A computational analysis using Hierarchical Drive Diffusion Modeling. Drug and Alcohol Dependence. Background: Variability in decision-making capacity and reward responsiveness may underlie differences in the ability to abstain from smoking. Computational modeling of choice behavior, as with the Hierarchical Drift Diffusion Model (HDDM), can help dissociate reward responsiveness from underlying components of decision-making. Here we used the HDDM to identify which decision-making or reward-related parameters, extracted from data acquired in a reward processing task, contributed to the ability of people who smoke that are not seeking treatment to abstain from cigarettes during a laboratory task. Methods: 80 adults who smoke cigarettes completed the Probabilistic Reward Task (PRT) - a signal detection task with a differential reinforcement schedule - following smoking as usual, and the Relapse Analogue Task (RAT) - a task in which participants could earn money for delaying smoking up to 50min - after a period of overnight abstinence. Two cohorts were defined by the RAT; those who waited either 0-min (n=36) or the full 50-min (n=44) before smoking. Results: PRT signal detection metrics indicated all subjects learned the task contingencies, with no differences in response bias or discriminability between the two groups. However, HDDM analyses indicated faster drift rates in 50-min vs. 0-min waiters. Conclusions: Relative to those who did not abstain, computational modeling indicated that people who abstained from smoking for 50min showed faster evidence accumulation during reward-based decision-making. These results highlight the importance of decision-making mechanisms to smoking abstinence, and suggest that focusing on the evidence accumulation process may yield new targets for treatment.

Janes博士继续发展她新建立的实验室，并开始在NID-IRP收集数据。她专注于员工招聘，发表了2篇手稿，如下所述。 1. 第2023章：我是你的女人整体信号回归后功能连接重测信度变化的空间变异：考虑血流动力学延迟的影响。人脑成像 全局信号回归（GSR）是一种有争议的分析方法，因为它的信号删除已被观察到，以降低功能连接估计的可靠性。在这里，我们使用重测信度来表征传统的静态GSR（sGSR）和一种新的动态形式的GSR（dGSR）之间的空间模式的潜在差异。与sGSR相比，dGSR以时间延迟对全局信号进行建模，以校正血液到达时间。因此，dGSR解释了全局信号的更大变化，去除了血流相关的干扰信号，并留下了更高质量的神经元信号。我们使用组内相关系数（ICC）来估计来自人类连接组计划的462名健康对照的功能连接的可靠性。我们测试了两个因素：所使用的去噪方法（对照、sGSR和dGSR）和采集间隔（天之间，或在会话内，同时改变相位编码方向）。可靠性进行了区域估计，以确定每种条件下的地形模式。与非GSR对照相比，sGSR和dGSR提供了可靠性的整体降低。重测信度最高的额顶叶和默认模式区域，最低的感觉运动皮层的所有条件。dGSR在两种策略都大大降低可靠性的区域中提供更有效的去噪。这两种GSR方法都大大降低了重测可靠性，这在去噪前可靠性低的大脑区域中最为明显。这些发现表明，区域间相关性的可靠性可能会被全球信号夸大，这被认为主要反映了动态血流。 2. Biernacki K，Molokotos E，Han C，Dillon D，Leventhal AM，Janes AC.戒烟的尼古丁依赖个体的决策增强：使用分层驱动扩散模型的计算分析。药物和酒精依赖。 背景：决策能力和奖励反应的差异可能是戒烟能力差异的基础。选择行为的计算模型，如分层漂移扩散模型（HDDM），可以帮助将奖励反应与决策的基本组成部分分离开来。在这里，我们使用HDDM来确定哪些决策或奖励相关的参数，从奖励处理任务中获得的数据中提取，有助于吸烟的人在实验室任务中不寻求治疗戒烟的能力。 研究方法：80名吸烟的成年人完成了概率奖励任务（PRT）-一种具有差异强化时间表的信号检测任务-在像往常一样吸烟后，以及复发性焦虑任务（RAT）-一种参与者可以通过延迟吸烟长达50分钟来赚钱的任务-经过一段时间的通宵戒烟。两个队列由大鼠定义;那些在吸烟前等待0分钟（n=36）或整个50分钟（n=44）的人。 结果如下：PRT信号检测指标表明，所有受试者都学会了任务的偶然性，两组之间的反应偏差或辨别力没有差异。然而，HDDM分析表明，50分钟与0分钟等待者的漂移率更快。 结论：相对于那些没有戒烟的人，计算模型表明，戒烟50分钟的人在基于奖励的决策过程中表现出更快的证据积累。这些结果强调了决策机制对戒烟的重要性，并表明关注证据积累过程可能会产生新的治疗目标。