Linking brain network dynamics to imminent smoking lapse risk and behavior

将大脑网络动态与即将戒烟的风险和行为联系起来

• 批准号: 10708145
• 负责人: Stephen Jeffrey Wilson
• 金额: $ 46.14万
• 依托单位: PENNSYLVANIA STATE UNIVERSITY, THE
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-30 至 2027-07-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10708145
• 关键词: Abstinence; Acute; Adult; Affect; Behavior; Behavioral; Brain; Cause of Death; Cigarette; Cognition; Complex; Coupling; Disease; Effectiveness; Failure; Female; Foundations; Functional Magnetic Resonance Imaging; Goals; Hour; Knowledge; Lateral; Lead; Link; Measures; Medial; Mental Processes; Methodology; Methods; Modeling; Negative Reinforcements; Neurobiology; Nicotine; Outcome; Parietal Lobe; Patient Self-Report; Pattern; Prefrontal Cortex; Prevention strategy; Process; Protocols documentation; Psychological reinforcement; Relapse; Research; Risk; Scanning; Self-control as a personality trait; Smoke; Smoking; Smoking Behavior; Testing; Theoretical model; Thinking; Time; Work; base; cigarette smoking; cingulate cortex; clinically relevant; cognitive process; craving; design; executive function; improved; indexing; innovation; insight; male; negative affect; neural; novel; prevent; psychologic; response; segregation; sex; smoking cessation; smoking initiation; smoking relapse; trait

Project Summary Most attempts to quit smoking end in relapse, or a return to regular smoking. One of the biggest threats to cessation is a lapse (i.e., any cigarette use during a quit attempt). Thus, characterizing why lapses occur is essential to understanding and preventing smoking relapse. Functional magnetic resonance imaging (fMRI) is a promising method for characterizing the psychological processes that lead to smoking lapses because it provides a way to measures patterns of brain activity thought to reflect relevant mental processes as they change over time. However, methodological issues have hindered the ability to capitalize on this potential and prevented an understanding of how brain activity and corresponding psychological processes unfold in the critical moments that immediately precede a smoking lapse. The proposed project will address this knowledge gap using a novel fMRI paradigm adapted from a well-validated behavioral lapse task. This novel fMRI paradigm includes an in-scanner delay period that models the ability to resist smoking during acute nicotine abstinence and a post-scan ad-lib period that captures key aspects of the smoking behavior that follows. Adults who smoke will abstain from cigarettes for 12 hours before completing the fMRI lapse paradigm. The goals of the project are to characterize changes in brain activity that lead up to a lapse and to investigate how these changes are related to concurrent affect and subsequent cigarette use. The study will focus specifically on linking lapse-related outcomes to time-dependent interactions between two large-scale brain networks: the executive control network, which includes parts of the lateral prefrontal and parietal cortices, and the default mode network, which includes parts of the medial prefrontal and posterior cingulate cortices. The central hypothesis guiding the proposed research is that lapse-related behavior and affect will be predicted by the extent to which the default mode network and the executive control network are functionally segregated (i.e., the strength of the connectivity within the default mode and executive control networks, relative to connectivity between the networks). The aims of the project are: 1) To examine the association between time-dependent changes in brain network dynamics and subsequent risk of smoking lapse; 2) To examine the association between time-dependent changes in brain network dynamics and self-reported affect leading up to a smoking lapse; and 3) To examine the association between brain network dynamics directly before a lapse and reinforcement from the smoking that follows. An additional exploratory aim of the study is to evaluate potential moderators of the association between brain network dynamics and lapse-related outcomes. The proposed study capitalizes on an innovative experimental fMRI approach to study in real time the neural underpinnings of discrete smoking lapse episodes. Successful completion of the proposed research will advance theoretical knowledge regarding the neural and psychological antecedents of smoking lapses. Results will also have implications for improving the effectiveness of strategies designed to prevent smoking lapses.

项目概要 大多数戒烟尝试都会以复发或恢复正常吸烟而告终。最大的威胁之一 戒烟是一种失误（即在尝试戒烟期间使用任何香烟）。因此，描述失误发生的原因是 对于了解和预防吸烟复吸至关重要。功能磁共振成像 (fMRI) 是 一种描述导致吸烟失误的心理过程的有前途的方法，因为它 提供了一种测量大脑活动模式的方法，该模式被认为反映了相关的心理过程 随着时间的推移而改变。然而，方法论问题阻碍了利用这一潜力的能力， 阻碍了对大脑活动和相应心理过程如何展开的理解 戒烟前的关键时刻。拟议的项目将解决这些知识 使用改编自经过充分验证的行为失误任务的新型功能磁共振成像范式来弥补差距。这种新颖的功能磁共振成像 范例包括扫描仪内延迟期，该延迟期模拟急性尼古丁期间抵抗吸烟的能力 戒烟和扫描后的即兴发挥阶段，捕捉随后吸烟行为的关键方面。 吸烟的成年人在完成 fMRI 失效范式之前将戒烟 12 小时。这 该项目的目标是描述导致失误的大脑活动变化的特征，并研究如何 这些变化与同时发生的情绪和随后的吸烟有关。该研究将特别关注 将与失误相关的结果与两个大规模大脑网络之间的时间依赖性相互作用联系起来： 执行控制网络，包括部分外侧前额叶和顶叶皮质，以及默认的 模式网络，包括内侧前额叶皮质和后扣带皮层的部分。中央 指导拟议研究的假设是，与失误相关的行为和影响将由 默认模式网络和执行控制网络在功能上隔离的程度（即， 默认模式和执行控制网络内的连接强度（相对于连接性） 网络之间）。该项目的目标是： 1）检查时间依赖性之间的关联 大脑网络动态的变化以及随后戒烟的风险； 2）检查关联性 大脑网络动态的时间依赖性变化与导致吸烟的自我报告影响之间的关系 失效； 3）检查故障发生前的大脑网络动态之间的关联 随后吸烟的强化。该研究的另一个探索性目的是评估潜在的 大脑网络动态与失误相关结果之间关联的调节因素。拟议的 研究利用创新的实验功能磁共振成像方法来实时研究神经基础 离散的吸烟失误事件。成功完成拟议的研究将推进理论研究 有关吸烟失误的神经和心理因素的知识。结果也会有 对提高旨在预防吸烟失误的策略的有效性的影响。