Functional networks related to cocaine dependence and its treatment and relapse

与可卡因依赖及其治疗和复发相关的功能网络

• 批准号: 9262879
• 负责人: Marc N Potenza
• 金额: $ 25.13万
• 依托单位: YALE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-05-01 至 2019-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9262879
• 关键词: Abstinence; Aftercare; Attention; Biological Markers; Brain; Brain region; Cocaine; Cocaine Dependence; Conflict (Psychology); Confusion; Data; Data Set; Dorsal; Drug abuse; Drug usage; Functional Magnetic Resonance Imaging; Heterogeneity; Impairment; Incentives; Inpatients; Insula of Reil; Linear Models; Midbrain structure; Motivation; Nature; Neurons; Outcome; Outpatients; Participant; Pathological Gambling; Patients; Recovery; Relapse; Reporting; Research; Research Personnel; Rewards; Sampling; Signal Transduction; Source; Substance Use Disorder; Task Performances; Testing; Thalamic structure; Treatment outcome; Urine; Ventral Striatum; addiction; base; blood oxygen level dependent; cocaine use; cognitive control; diagnostic biomarker; effective therapy; follow-up; high dimensionality; imaging study; incentive salience; independent component analysis; insight; neural correlate; neuropathology; neuropsychiatric disorder; non-drug; novel strategies; predictive marker; prospective; public health relevance; secondary analysis; theories; therapy development

 DESCRIPTION (provided by applicant): This application responds to PAR-13-080 - Accelerating the Pace of Drug Abuse Research Using Existing Data. Functional magnetic resonance imaging (fMRI) and the traditional general-linear-model-based analysis (GLM-BA) have been used to assess neural correlates of cocaine dependence (CD) and other neuropsychiatric disorders. However, these studies have reported inconsistent findings including reduced and increased brain activity in patients relative to healthy controls (HCs), and have not been able to provide a clear picture on CD neuropathology and define reliable biomarkers for CD treatment. Investigators have suggested multiple factors such as addiction stages of patients contributing to conflicting findings. We recently applied spatial independent component analysis (sICA) to several fMRI datasets and found extensive overlaps of functional networks (FNs) with opposite timecourses of task-related activities. Based on these findings, we predict: 1) that blood-oxygenation-level-dependent (BOLD) signal mixtures reflecting concurrent co-localized activation and deactivation (CCAD) of different neurons in the same voxels contribute to the opposite findings, while CCAD is determined by balanced excitation and inhibition and functional heterogeneity in the brain; 2) that due to the nature of signal mixtures,a reduced brain deactivation might be expressed as an increased BOLD signal and misinterpreted as a greater brain activation by studies using GLM-BA, which cannot differentiate mixed signals from same voxels; and 3) that sICA will overcome the limitation of GLM-BA and reveal consistent fMRI findings in patients, because sICA can separate signal mixtures from the same voxels into different FNs, and thus mitigate the confusion of reduced deactivation vs. increased activation. For testing our predictions and better understanding CD neuropathology, this project will use sICA to perform secondary analyses on fMRI data acquired from 419 participants, including 179 HCs and 196 CD patients. They performed fMRI tasks for assessing cognitive control and/or monetary reward/loss- motivation. Most patients were treated for CD and followed for 3 ~ 12 months after treatment. We hypothesize that sICA will consistently reveal reduced task-related modulations of FNs related to cognitive control and/or reward/loss-motivation in CD patients relative to HCs, increased (i.e., "recovery") modulations of these FNs in patients after effective treatment for CD, and positive correlations between greater modulations of these FNs and better long-term outcomes after treatment. Findings supporting our hypotheses will not only provide a consistent insight into CD neuropathology and reconcile extant conflicting data, but also demonstrate that task- related modulations in FNs related to cognitive control and/or reward/loss-motivation in CD patients as revealed by sICA are excellent candidates for reliable diagnostic and predictive biomarkers for optimizing and developing CD treatments. Furthermore, these findings will have a sustained, powerful impact on fMRI theories and practices in a general and broad sense and will help move the entire field forward.

 描述（由申请人提供）：本申请响应 PAR-13-080 - 使用现有数据加速药物滥用研究的步伐。 ）已被用来评估可卡因依赖（CD）和其他神经精神疾病的神经相关性。然而，这些研究报告了不一致的结果，包括相对于健康对照组，患者的大脑活动减少和增加。 （HC），并且无法提供 CD 神经病理学的清晰图像并定义 CD 治疗的可靠生物标志物。研究人员提出了多种因素，例如患者的成瘾阶段，导致了相互矛盾的结果。我们最近应用了空间独立成分分析（sICA）。 ）对几个功能磁共振成像数据集进行了研究，发现功能网络（FN）与任务相关活动的相反时间进程存在广泛重叠。根据这些发现，我们预测：1）血液氧合水平依赖性（BOLD）信号混合物反映了并发的情况。同一体素中不同神经元的共定位激活和失活（CCAD）导致相反的发现，而 CCAD 是由大脑中的平衡兴奋和抑制以及功能异质性决定的；2）由于信号混合物的性质，a通过使用 GLM-BA 的研究，大脑失活的减少可能会表现为 BOLD 信号增加，并被误解为更大的大脑激活，而 GLM-BA 无法区分来自相同体素的混合信号；3) sICA 将克服以下限制： GLM-BA 并揭示了患者中一致的 fMRI 结果，因为 sICA 可以将来自相同体素的信号混合物分离到不同的 FN，从而减轻减少失活与增加激活的混淆。为了测试我们的预测并更好地理解 CD 神经病理学。将使用 sICA 对从 419 名参与者（包括 179 名 HC 和 196 名 CD 患者）获得的 fMRI 数据进行二次分析，他们执行 fMRI 任务来评估认知控制和/或金钱奖励/损失。大多数患者接受 CD 治疗，并在治疗后随访 3 ~ 12 个月，我们希望 sICA 能够持续揭示与 HC 患者相比，与认知控制和/或奖赏/丧失动机相关的 FN 的任务相关调节。 ，在有效治疗 CD 后，患者中这些 FN 的调节增加（即“恢复”），并且这些 FN 的更大调节与治疗后更好的长期结果之间呈正相关。支持我们的假设不仅可以提供对 CD 神经病理学的一致见解并协调现有的相互冲突的数据，而且还证明 sICA 揭示的与 CD 患者的认知控制和/或奖励/损失动机相关的 FN 中的任务相关调节是非常好的此外，这些发现将对功能磁共振成像理论和实践产生持续、强大的影响，并将有助于推动整个领域的发展。