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

评估神经振荡生物标志物在干预结果变化的啮齿动物模型中的潜力：走向个性化心理保健

• 批准号: 10718156
• 负责人: Wilder T Doucette
• 金额: $ 59.3万
• 依托单位: DARTMOUTH-HITCHCOCK CLINIC
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-07-01 至 2028-05-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10718156
• 关键词: Anterior; Attention deficit hyperactivity disorder; Behavior; Behavioral; Bilateral; Biological Markers; Biological Models; Borderline Personality Disorder; Brain; Brain region; Clinical; Communication; Corpus striatum structure; Data; Diagnosis; Funding; Future; Genetic; Goals; Heterogeneity; Human; Impairment; Individual; Intervention; Link; Machine Learning; Measures; Mediating; Mental Health Services; Mental disorders; Modeling; National Institute of Mental Health; Neurobiology; Nucleus Accumbens; Outcome; Pathway interactions; Patients; Performance; Pharmaceutical Preparations; Physiology; Pre-Clinical Model; Predisposition; Rat Strains; Rattus; Reporting; Research Personnel; Rewards; Risk; Ritalin; Rodent; Rodent Model; Schizophrenia; Suicide; System; Task Performances; Testing; Therapeutic; Time; Training; Treatment outcome; Variant; Violence; Work; biomarker identification; career; designer receptors exclusively activated by designer drugs; discounting; effective therapy; gene therapy; implementation intervention; individual variation; individualized medicine; innovation; machine learning model; neural; neuropsychiatry; pharmacologic; risk sharing; sex; substance use; theories; translational goal; translational research program

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.

项目总结/摘要 精神卫生保健的一个主要挑战包括目前心理治疗的结果不一致， 药理学和脑刺激干预。我们的理论是，在不同的个体中， 基础表现在系统层面，导致功能和具体诊断领域受损。 这种异质性导致相同的干预措施在不同的人身上产生不同的结果。到 为了克服这一挑战，我们假设系统水平的大脑活动（神经振荡）包含 预测脑功能领域中个体差异和鉴定生物标志物所必需的信息 指导干预措施的个性化实施。为了验证这些假设， 需要足够的变化和复杂性，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远交系大鼠品系（Sprague道利）中， (DDT)风险贴现任务（RDT）。当脑刺激（目标1）、药理学（目标2）或 在这些大鼠中实施了化学遗传学（目标3）干预，它们产生了异质性效应 这是一个很好的模型系统来评估我们的假设。 我们提出的概念验证研究将确定神经振荡作为生物标志物的潜在效用 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 预测个体和时间之间的任务绩效变化; 2）振荡可以预测个体 干预结果;以及3）干预引起的振荡变化可以预测相应的 DDT或RDT性能的变化。 进一步增强这一建议的翻译相关性，调节神经系统的神经系统， 与延迟和风险折扣相关的奖励价值在啮齿动物和人类之间具有同源性， 与重要的临床结果有关。例如，通过以下方式过度减少奖励价值 延迟与在多种精神病状况中的不良结果的显著风险有关（例如，多动症， 精神分裂症和边缘型人格障碍）。异常延迟和风险折扣也有联系 具体行为，包括自杀，暴力和危险物质的使用，加强了影响， 建议的研究。作为一名早期职业调查员，这项提案的资金将使我能够发起一项 创新的转化研究计划与NIMH的战略目标相一致，专注于开发系统- 水平的脑活动生物标志物，以指导患者的干预措施的个性化实施 精神疾病