Testing competing models of the computational role of dopamine in hallucinations

测试多巴胺在幻觉中的计算作用的竞争模型

• 批准号: 10752192
• 负责人: Justin Buck
• 金额: $ 4.77万
• 依托单位: COLUMBIA UNIVERSITY HEALTH SCIENCES
• 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 2025-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10752192
• 关键词: Adherence; Arbitration; Auditory; Automobile Driving; Basal Ganglia; Behavior; Brain Diseases; Brain region; Clinical; Cognitive; Computer Models; Corpus striatum structure; Data; Detection; Development; Dissociation; Dopamine; Dorsal; Fostering; Functional Magnetic Resonance Imaging; General Population; Hallucinations; Hearing; Incentives; Learning; Link; Literature; Magnetic Resonance Imaging; Mathematics; Measures; Midbrain structure; Modeling; Neurocognitive; Neurosciences; Participant; Patients; Perception; Perceptual disturbance; Perceptual learning; Process; Proxy; Psychiatry; Quality of life; Reporting; Research Personnel; Rewards; Sampling; Schizophrenia; Severities; Signal Transduction; Specificity; Stimulus; Substantia nigra structure; Testing; Training; Update; Ventral Striatum; Ventral Tegmental Area; behavior prediction; cognitive process; comorbidity; design; dopaminergic neuron; effective therapy; expectation; experience; improved; indexing; individualized medicine; interest; neural; neural circuit; neural correlate; neurochemistry; neuroimaging; neuromelanin; novel; pharmacologic; phenomenological models; predictive modeling; role model; sensory stimulus; side effect; symptomatic improvement; theories; transmission process; treatment adherence; treatment strategy

Project Summary: Hallucinations are common in clinical and nonclinical groups, can be difficult to treat, and often predict worsening functionality. The poor efficacy and severe side effects of current treatments are in part a consequence of our immature understanding of the mechanisms that cause hallucinations. Excess striatal dopamine release has been causally implicated in the development and severity of hallucinations but the precise circuits and cognitive processes that link this neurochemical alteration to false perception remain unclear. Evidence from the basic neuroscience literature has inspired competing theories about how excess striatal dopamine drives hallucinations. Specifically, reward and perceptual hypotheses of hallucinations have emerged, but they have yet to be directly tested in a falsifiable framework. Identifying which of these hypothesized mechanisms drives hallucinations is critically important given that reward and perceptual learning are facilitated by distinct dopaminergic basal circuits each of which may provide a separate treatment target. We have developed a mathematical framework that formalizes these hypotheses with biologically grounded computational models and generated falsifiable predictions about how alterations in either perceptual or reward learning could drive hallucinations. Here, we will rigorously test the neural and behavioral predictions of these models using a novel fMRI-compatible auditory signal-detection task and a validated proxy measure for midbrain dopamine function. In Aim 1, we will evaluate participant perceptual and reward learning and the relationship with hallucination proneness. In Aim 2, we will identify the neural circuits that support reward and perceptual learning during the task. In Aim 3, we will use a validated proxy measure of dopamine function to dissociate the specific subcircuits driving alterations in learning. Overall, the proposed study aims to bridge the explanatory gap between our understanding of the neurochemistry and phenomenology of hallucinations. Critically, this could promote the identification of individualized treatment targets that are not only more effective but have more limited side effects. This proposal will also support my training in state-of-the-art computational modeling and neuroimaging approaches and promote my development as an independent researcher in the field of computational psychiatry.

项目概要： 幻觉在临床和非临床群体中很常见，可能难以治疗，并且通常预示着病情会恶化 功能。当前治疗效果不佳和严重副作用的部分原因是我们的 对引起幻觉的机制的不成熟理解。纹状体多巴胺释放过多 与幻觉的发展和严重程度有因果关系，但精确的回路和认知 将这种神经化学改变与错误知觉联系起来的过程仍不清楚。基本证据 神经科学文献激发了关于过量纹状体多巴胺如何驱动的相互竞争的理论 幻觉。具体来说，幻觉的奖励和知觉假设已经出现，但它们没有 尚未在可证伪的框架中直接进行测试。确定这些假设机制中的哪一个驱动 鉴于奖励和知觉学习是通过不同的机制来促进的，幻觉至关重要 多巴胺能基础回路中的每一个都可以提供单独的治疗目标。我们开发了一个 数学框架，用基于生物学的计算模型形式化这些假设， 生成了关于感知或奖励学习的改变如何驱动的可证​​伪的预测 幻觉。 在这里，我们将使用一种新型的功能磁共振成像兼容来严格测试这些模型的神经和行为预测 听觉信号检测任务和经验证的中脑多巴胺功能代理测量。在目标 1 中，我们将 评估参与者的感知和奖励学习以及与幻觉倾向的关系。在目标 2 中， 我们将识别任务期间支持奖励和感知学习的神经回路。在目标 3 中，我们将 使用经过验证的多巴胺功能代理测量来分离驱动改变的特定子电路 学习。总体而言，拟议的研究旨在弥合我们对 幻觉的神经化学和现象学。至关重要的是，这可以促进对 个体化治疗目标不仅更有效，而且副作用也更有限。这个提议 还将支持我在最先进的计算建模和神经影像方法方面的培训， 促进我作为计算精神病学领域的独立研究员的发展。