Prediction Error and Affective Salience Abnormalities in Aging and Late-Life Depression

项目总结 本次K01指导研究科学家职业发展奖的目标是为候选人提供 从事独立研究工作所需的概念知识和技术技能 计算认知神经学家专注于衰老和晚年情绪障碍。这位候选人有一个 在认知范式设计和功能神经成像方法学方面有很强的背景，以及不断发展的 对抑郁症老年人认知和情感功能障碍的计算机建模的兴趣。这个 研究研究将使用计算方法来阐明奖励和显著的干扰机制 这一过程可能会产生可作为未来个性化治疗的数据驱动目标的研究结果。 拟议的培训由正式课程、结构化教程和实践方法指导组成。 旨在加强考生对研究计算模型的理解和发展 正价系统(PVS)异常在衰老和晚年抑郁症中的研究。她的指导团队 由经验丰富的研究人员组成，他们将在神经生物学和 研究奖赏和显著异常的计算方法。 这项研究是对候选人培训计划的补充，因为它侧重于可能出现的PVS功能障碍 导致正常衰老和晚年抑郁的奖赏处理异常。它是基于 预测与衰老相关的奖赏回路异常与神经生物学异常相互作用 抑郁可能会改变奖励预期和奖励反应，导致抑郁的老年人将 对负面刺激有更强的情感敏感度。因此，这项研究建议调查 年龄和抑郁症状对三岁情绪显著刺激预测错误编码的影响 分析层次：电路、行为和自我报告。参与者将是60-85岁的老年人， 重度抑郁症(N=34，分为两个严重程度)或无精神病史或存在精神病理(N =34)。 这项拟议的研究将使用基于任务的功能磁共振成像和计算建模来检查动态 年龄和老年抑郁症状的交互作用影响神经网络功能和 由此产生的奖励和显著加工行为。这项研究和后续的研究承诺识别 针对急需干预的个性化行为和神经生物学目标。这项工作是及时的，因为 认知补救、脑刺激和有针对性的行为干预的进展正在成为 越来越有能力影响选择性的神经生物学功能和相关行为。

PROJECT SUMMARY The goal of this K01 Mentored Research Scientist Career Development Award is to provide the candidate with the conceptual knowledge and technical skills needed to pursue an independent research career as a computational cognitive neuroscientist focused on aging and late-life mood disorders. The candidate has a strong background in cognitive paradigm design and functional neuroimaging methodology, and an evolving interest in computational modeling of cognitive and affective dysfunctions in depressed older adults. The research study will use computational approaches to clarify disrupted mechanisms of reward and salience processes and may lead to findings that can serve as data-driven targets for future personalized treatments. The proposed training consists of formal courses, structured tutorials, and hands-on methodological instruction intended to strengthen the candidate's understanding and development of computational models for the study of Positive Valence Systems (PVS) abnormalities in aging and late-life depression. Her mentoring team consists of accomplished investigators who will provide guidance and training in neurobiological and computational approaches for the study of reward and salience abnormalities. The research study complements the candidate's training plan, as it focuses on PVS dysfunctions that may contribute to reward processing abnormalities in normal aging and late-life depression. It is based on the prediction that aging-related abnormalities in reward circuits interacting with neurobiological abnormalities of depression may alter reward expectancy and reward responsiveness, leading depressed older adults to assign greater affective salience to negative stimuli. Accordingly, the study proposes to investigate the impact of the effects of aging and depressive symptoms on prediction error encoding of affectively salient stimuli at three levels of analysis: circuits, behavior, and self-report. The participants will be older adults aged 60-85 years with major depression (N = 34, stratified into two levels of severity) or no history or presence of psychopathology (N = 34). The proposed study will use task-based fMRI and computational modeling to examine how the dynamic interaction of age and late-life depressive symptomatology influences neural network functions and the resulting reward and salience processing behaviors. This study and the studies to follow promise to identify personalized behavioral and neurobiological targets for much-needed interventions. This work is timely, as advances in cognitive remediation, brain stimulation, and targeted behavioral interventions are becoming increasingly capable of influencing selective neurobiological functions and associated behaviors.