Evaluating the potential of neural oscillation biomarkers in a rodent model of intervention outcome variation: Toward personalized mental health care

项目摘要/摘要 精神卫生保健的一个主要挑战包括当前心理治疗的结果不一致， 药理学和脑刺激干预。我们理论认为，在个体之间，不同种类的神经 基础表现在系统层面上，导致功能和特定诊断领域受损。 这种异质性导致相同的干预措施在不同的个体之间产生不同的结果。至 克服这一挑战，我们假设系统级的大脑活动(神经振荡)包含 预测大脑功能领域中的个体差异和识别生物标志物所需的信息 指导一项干预措施的个性化实施。为了验证这些假说，一个模型大脑系统 需要有足够的多样性和复杂性，以产生行为和干预的异质性 结果。先前的工作，包括我们自己的初步数据，证明了这种行为差异的存在 在执行延迟折扣任务的异种鼠品系(SpragueDawley)中，跨个体和性别 (DDT)和风险贴现任务(RDT)。当脑刺激(目标1)、药理学(目标2)或 已经在这些大鼠身上实施了化学发生(目标3)干预，它们产生了不同的影响 这使它成为评估我们假设的一个很好的模型系统。 我们提议的概念验证研究将确定神经振荡作为生物标志物的潜在用途。 反映了延迟和风险贴现的神经基础的个体差异，以及 这些人必须对干预措施作出反应。我们将使用机器学习来确定：1)振荡是否可以 预测任务绩效在不同个体和时间上的变化；2)振荡可以预测个体 干预结果；以及3)干预引起的振荡的变化预测相应的 DDT或RDT性能的变化。 进一步增强这一提议的翻译相关性，调节 与延迟和风险贴现相关的奖励价值在啮齿动物和人类之间具有同源性，并且 与重要的临床结果有关。例如，奖励价值的过度减少 延迟与多种精神疾病(例如，ADHD， 精神分裂症和边缘人格障碍)。不正常的延误和风险贴现也被联系在一起 针对特定行为，包括自杀、暴力和使用危险物质，增强了 建议进行的研究。作为一名职业生涯早期的调查员，为这项提议提供资金将使我能够发起一项 与专注于开发系统的NIMH战略目标保持一致的创新翻译研究计划- 脑活动生物标志物水平以指导患者个体化干预的实施 精神疾病。

PROJECT SUMMARY/ABSTRACT A major challenge in mental health care includes inconsistent outcomes of current psychotherapeutic, pharmacologic, and brain stimulation interventions. We theorize that across individuals, heterogeneous neural underpinnings manifest at a systems level, leading to impaired domains of function and specific diagnoses. This heterogeneity causes the same intervention to produce different outcomes across individuals. To overcome this challenge, we hypothesize that systems-level brain activity (neural oscillations) contains the information necessary to predict both individual variation in a domain of brain function and identify biomarkers to guide the individualized implementation of an intervention. To test these hypotheses, a model brain system is needed with sufficient variation and complexity to produce heterogeneity in behavior and intervention outcomes. Prior work, including our own preliminary data, demonstrates such behavioral variation exists across individuals and sexes in an outbred rat strain (Sprague Dawley) performing the delay discounting task (DDT) and risk discounting task (RDT). When brain stimulation (Aim 1), pharmacologic (Aim 2) or chemogenetic (Aim 3) interventions have been implemented in these rats, they produce heterogeneous effects on task performance across individuals making this an excellent model system to evaluate our hypotheses. Our proposed proof-of-concept study will determine the potential utility of neural oscillations as biomarkers reflecting individual variation in the neural underpinnings of delay and risk discounting and the predisposition of those individuals to respond to interventions. We will use machine learning to determine if: 1) oscillations can predict variation in task performance across individuals and time; 2) oscillations can predict individual intervention outcomes; and 3) changes in oscillations induced by interventions are predictive of corresponding changes in DDT or RDT performance. Further enhancing the translational relevance of this proposal, the neural systems that modulate the value of rewards associated with delay and risk discounting share homology between rodents and humans and have been linked to important clinical outcomes. For instance, the excessive reduction of reward value by delay relates to a significant risk for poor outcomes in multiple psychiatric conditions (e.g., ADHD, schizophrenia and borderline personality disorder). Abnormal delay and risk discounting have also been linked to specific behaviors, including suicide, violence and risky substance use, enhancing the impact of the proposed studies. As an early-career investigator, funding for this proposal would allow me to launch an innovative translational research program aligned with NIMH strategic goals focused on developing systems- level brain activity biomarkers to guide the individualized implementation of interventions for patients with mental illness.