Decision-making abilities in Alzheimer's disease and related dementias: From clinical standards to decision neuroscience

项目摘要/摘要 阿尔茨海默病和相关痴呆症的特点是早期和显著的决策障碍- 这往往给患者及其家人带来灾难性的后果。虽然最近对决策的研究 神经科学和神经经济学在阐明这些疾病背后的神经机制方面大有可为。 损害(最终是为了实现更深层次的理解，从而产生改进策略 患者的决定)，在许多情况下，神经科学的发现如何应用于 病人在现实生活中表现出的决策错误。尖端研究之间的这种转换鸿沟 临床实践将在拟议的工作中通过将当前决策神经科学与 临床标准通常用于评估患者的决策能力。在一个广泛的- 痴呆症和其他认知障碍的公认标准、受损的决定可能是由于未能做到： (1)了解决策的相关特点，(2)了解决策与自身情况的关系，(3) 理性地操纵信息以做出决定，或者(4)始终如一地证明选择。这些标准 反映临床医生对患者损伤的专业知识，并体现关于如何 人们做出决定，以及在疾病中决策是如何受到影响的--这些假设现在可以 运用决策神经科学的工具进行了实证研究。建议的研究是围绕以下几个方面展开的 代表当前神经科学和公认的临床标准之间联系的三个具体目标： 1(赏识)：以价值观为基础调查不同痴呆综合征的元认知障碍 选择。2(推理)：阐明将相关信息应用于决策的机制，这些机制是 患有阿尔茨海默氏症。3(选择)：评估在不同情况下显示的偏好的不一致性 痴呆症。在这项工作中，我们将从阿尔茨海默氏症患者的特征良好的队列中提取数据 疾病、额颞部痴呆症患者和健康的老年对照组，所有这些都与临床和 神经成像数据。多个队列将允许症状或靶向脑之间的特定关联 结构和不正常的决定；否则，疾病或认知减退的一般影响通常不能 被排除在外。将使用计算机行为测试和决策来实现目标1和目标3 目标2将在决策任务期间使用基于任务的功能磁共振成像来实现。创新的 方法将增强外部有效性(通过将结果与临床专家关于决策的工作联系起来 患者在日常生活中表现出的损害)和僵硬(使用不同疾病的比较来确保 研究结果反映了特定的神经效应，而不是其他混淆)。因此，拟议的工作有望 通过将决策神经科学与广泛接受的临床标准联系起来，做出了重大贡献 促进我们对临床决策障碍的机制的理解，最终导致 改进了评估工具和未来干预措施的目标，以防止对患者造成严重伤害。

PROJECT SUMMARY/ABSTRACT Alzheimer’s disease and related dementias are marked by early and significant impairments in decision- making, often with disastrous consequences for patients and their families. While recent research in decision neuroscience and neuroeconomics holds great promise for elucidating neural mechanisms underlying these impairments (and ultimately, for achieving a deeper understanding that can yield strategies for improving patients’ decisions), in many cases it remains unclear how neuroscientific findings can be applied to the decision-making errors that patients exhibit in real life. This translational gap between cutting-edge research and clinical practice will be addressed in the proposed work by linking current decision neuroscience to clinical standards routinely applied in the assessment of patients’ decision-making abilities. On a widely- accepted standard, impaired decisions in dementia and other cognitive disorders can result from failures to: (1) understand relevant features of a decision, (2) appreciate how this relates to one’s own situation, (3) rationally manipulate information to arrive at a decision, or (4) consistently evidence a choice. These criteria reflect clinicians’ expertise with patients’ impairments and embody mechanistic assumptions about how people make decisions and how decision-making is compromised in disease—assumptions that can now be investigated empirically using tools of decision neuroscience. The proposed research is organized around three specific aims that represent links between current neuroscience and accepted clinical standards: 1 (Appreciation): Investigate metacognitive impairments in different dementia syndromes in value-based choice. 2 (Reasoning): Elucidate mechanisms for applying relevant information to decision-making, which are disrupted in Alzheimer’s disease. 3 (Choice): Assess inconsistency in revealed preferences in different dementia syndromes. In this work we will draw from well-characterized cohorts of patients with Alzheimer’s disease, patients with frontotemporal dementia, and healthy older controls, all with linked clinical and neuroimaging data. Multiple cohorts will allow for specific associations between syndromes or targeted brain structures and abnormal decisions; otherwise, generic effects of illness or diminished cognition often cannot be excluded. Aims 1 & 3 will be pursued using computer-based behavioral testing with decision-making tasks, while Aim 2 will be pursued using task-based fMRI during a decision-making task. The innovative approach will enhance external validity (by linking results to the work of clinical experts about the decisional impairments that patients exhibit in daily life) and rigor (using comparisons across diseases to assure that findings reflect specific neural effects rather than other confounds). The proposed work is therefore poised to make a significant contribution by linking decision neuroscience with widely-accepted clinical standards to advance our understanding of mechanisms of clinical decision-making impairments, ultimately resulting in improved assessment tools and in targets for future interventions to prevent serious harms to patients.