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Adaptive and Maladaptive Neural Network Responses to Inhibitory Challenges

自适应和适应不良神经网络对抑制性挑战的反应

基本信息

批准号：
10542339
负责人：
Naomi Samimi-Sadeh
金额：
$ 51.46万
依托单位：
UNIVERSITY OF DELAWARE
依托单位国家：
美国
项目类别：
财政年份：
2019
资助国家：
美国
起止时间：
2019-04-01 至 2024-12-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10542339
关键词：
Adult Affective Alcohols Amygdaloid structure Antisocial Personality Disorder Behavior Benchmarking Biological Assay Biological Markers Brain Classification Clinical Clinical Treatment Cognitive Communication Compensation Complex Cues Data Desire for food Diagnostic Dimensions Disease Emotional Emotions Failure Functional Magnetic Resonance Imaging Goals Health Hypersensitivity Image Impulsivity Individual Informal Social Control Investigation Knowledge Learning Life Life Expectancy Light Link MRI Scans Magnetic Resonance Imaging Maps Measures Mental disorders Methods Modeling National Institute of Mental Health Nature Neurobiology Neurosciences Outcome Participant Pathologic Play Process Protocols documentation Psychiatric Diagnosis Psychopathology Public Health Reaction Research Research Domain Criteria Resources Rewards Risk Risk Behaviors Risk Factors Role Sampling Self-control as a personality trait Short-Term Memory Structure Substance Use Disorder Suicide System Taxes Translating Violence clinical diagnostics clinical risk distraction graph theory high risk behavior improved negative mood neural neural circuit neural model neural network neuroimaging novel promote resilience recruit resilience response reward processing substance use support network trait impulsivity

项目摘要

ABSTRACT Impulse control predicts a myriad of serious public health problems that substantially reduce life expectancy, including suicide, violence, substance use, and other risky behaviors. Although it is known that inhibitory control deficits confer risk for these clinical problems, one critical barrier to progress in this field is that much less is known about how this core regulatory process interacts with other cognitive and affective systems. Given that impulse control failures that occur in everyday life reflect the interaction of multiple cognitive and affective systems, this knowledge is critical for mapping impulse control failures onto neural circuits and accurately modeling the impulsivity that occurs in psychopathology as disruptions in neural systems. The objective of this application is to determine how functional brain networks supporting inhibitory control respond to cognitively- and affectively-challenging contexts and to evaluate the relevance of these networks for explaining clinical problems with impulsivity. We propose a novel investigation aimed at better understanding how three contexts known to challenge impulse control (cognitive resource depletion, competing appetitive cues, and negative mood induction) impact the functional brain networks that support successful inhibitory control and, ultimately, self-regulation in mental illness. First, healthy adults will undergo a thorough clinical diagnostic assessment and complete a battery of functional magnetic resonance imaging (fMRI) tasks in the MRI scanner that assess inhibitory control in different challenging contexts. These data are expected to contribute a precise working model of how functional brain networks compensate to meet the unique inhibitory control demands present in different challenging contexts. They will also add context as a level of analysis to existing neural models of inhibition, bringing them closer to capturing the multidimensional nature of inhibitory control failures in everyday life. Next, given that replication failures are common in neuroimaging research, a subset of participants will undergo a second MRI scan after a three-month period to establish the reliability of the novel functional brain metrics of inhibitory control we propose to investigate. Finally, a central goal of the NIMH RDoC initiative is to link clinical problems to neural systems (Cuthbert & Insel, 2013). Consistent with this initiative, we propose to examine disruptions in inhibitory control networks as potential transdiagnostic risk factors for externalizing disorders (e.g., alcohol/ substance use disorders, antisocial personality disorder) and as biomarkers for identifying subtypes of inhibition. This approach has the potential to create a more neuroscience-based classification of clinical problems related to impulsivity. Together, this research is expected to ultimately aid in the treatment of clinical impulsivity by leading to a deeper understanding of the brain networks that support successful inhibitory control.

摘要冲动控制预示着无数严重的公共卫生问题，大大减少预期寿命，包括自杀、暴力、吸毒和其他危险行为。尽管已知抑制性的控制缺陷会给这些临床问题带来风险，这一领域进展的一个关键障碍是，关于这一核心调节过程如何与其他认知和情感系统相互作用，人们知之甚少。鉴于日常生活中发生的冲动控制失败反映了多种认知和情感系统，这方面的知识是至关重要的映射脉冲控制故障到神经电路，准确地模拟神经系统中断时精神病理学中出现的冲动。的本申请的目的是确定支持抑制控制的功能性脑网络如何响应认知和情感挑战的背景下，并评估这些网络的相关性，用冲动来解释临床问题我们提出了一个新的调查，旨在更好地了解三种已知的挑战冲动控制的环境（认知资源耗尽，竞争性食欲，暗示和消极情绪诱导）影响支持成功抑制的功能性大脑网络。控制和最终的自我调节。首先，健康的成年人将接受彻底的临床检查，诊断评估，并完成一系列功能性磁共振成像（fMRI）任务， MRI扫描仪，在不同的挑战性环境中评估抑制控制。预计这些数据将贡献了一个精确的工作模型，说明功能性大脑网络如何补偿，以满足独特的抑制作用。控制需求存在于不同的挑战性环境中。他们还将添加上下文作为分析级别，现有的抑制神经模型，使他们更接近捕捉抑制的多维性质，日常生活中的控制失误。接下来，鉴于复制失败在神经影像学研究中很常见，一部分参与者将在三个月后接受第二次MRI扫描，以确定新的功能性大脑指标的抑制控制，我们建议调查。最后， NIMH RDoC计划将临床问题与神经系统联系起来（Cuthbert & Insel，2013）。符合在这一倡议中，我们建议将抑制性控制网络中的中断作为潜在的transdiagnosis风险进行检查。使疾病外化的因素（例如，酒精/物质使用障碍，反社会人格障碍）和作为识别抑制亚型的生物标志物。这种方法有可能创造一个更基于神经科学的冲动性相关临床问题的分类。总之，这项研究是预期最终有助于治疗临床冲动，通过更深入地了解支持成功抑制控制的大脑网络。