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.

项目摘要 大多数戒烟的尝试都以故态复萌或恢复正常吸烟告终。最大的威胁之一是 戒烟是一种失误(即戒烟过程中的任何吸烟行为)。因此，描述为什么会发生失误的原因是 对了解和防止吸烟复发至关重要。功能磁共振成像(FMRI)是 一种有希望的方法来表征导致吸烟的心理过程，因为它 提供了一种测量大脑活动思维模式的方法，以反映相关的心理过程 随着时间的推移而改变。然而，方法问题阻碍了利用这一潜力的能力，并且 阻碍了对大脑活动和相应的心理过程如何在 紧接在吸烟失误之前的关键时刻。拟议的项目将解决这一知识 GAP使用了一种新的功能磁共振成像范式，该范式改编自一项经过充分验证的行为失误任务。这种新的功能磁共振成像 范例包括一个扫描仪延迟期，它模拟了在急性尼古丁期间抵抗吸烟的能力 禁欲和扫描后的即兴阶段，捕捉到随后吸烟行为的关键方面。 吸烟的成年人在完成功能磁共振成像失误范式之前将戒烟12小时。这个 该项目的目标是描述导致失误的大脑活动变化的特征，并调查 这些变化与同时影响和随后的香烟使用有关。这项研究将特别关注 关于将失误相关结果与两个大规模大脑网络之间依赖时间的相互作用联系起来： 执行控制网络，包括部分外侧前额叶和顶叶皮质，以及默认 模式网络，包括部分内侧前额叶和后扣带回皮质。中环 指导这项拟议研究的假设是，与失误相关的行为和情感将由 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相对于连接的强度 在网络之间)。该项目的目标是：1)检查时间依赖关系之间的关联 大脑网络动力学的变化和随后吸烟的风险；2)检查这种联系 大脑网络动力学的时间依赖性变化与导致吸烟的自我报告的情绪之间的关系 错误；以及3)检查错误之前的大脑网络动态与错误之间的关联 随之而来的吸烟带来的强化。这项研究的另一个探索性目的是评估潜力 脑网络动态与失误相关结果之间关系的调节者。建议数 这项研究利用了一种创新的实验功能磁共振方法来实时研究脑梗塞的神经基础 不连续的吸烟失误发作。拟议研究的成功完成将推动理论 关于吸烟的神经和心理先兆的知识。结果也将是 对改进旨在防止吸烟失误的策略的有效性的影响。