Neural Substrates and Mechanisms Underlying Rumination in Depression

抑郁症沉思背后的神经基础和机制

• 批准号: 8197374
• 负责人: Neil Patrick Jones
• 金额: $ 14.16万
• 依托单位: UNIVERSITY OF PITTSBURGH AT PITTSBURGH
• 依托单位国家: 美国
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-12-01 至 2015-11-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8197374
• 关键词: Address; Affective; Amygdaloid structure; Anhedonia; Automobile Driving; Behavioral; Behavioral Research; Biological Neural Networks; Brain; Brain region; Chronic; Clinical; Cognition; Cognitive; Communication; Computer Simulation; Consultations; Country; Coupling; Cues; Depressed mood; Detection; Development; Development Plans; Disease; Diving; Educational Intervention; Educational workshop; Emotional; Etiology; Failure; Fostering; Functional Magnetic Resonance Imaging; Generations; Goals; Health; Housing; Human; Image; Individual; Intervention Studies; Knowledge; Lead; Mainstreaming; Maintenance; Maps; Measures; Medial; Memory; Mental Depression; Modeling; Neurobiology; Neurosciences Research; Participant; Patient Self-Report; Patients; Pattern; Persons; Prefrontal Cortex; Problem Solving; Process; Protocols documentation; Psychiatry; Psychopathology; Recovery; Relative (related person); Research; Research Training; Severities; Simulate; Social Functioning; Social Problems; Solutions; Staging; Supervision; Techniques; Thinking; Training; Training Programs; Universities; affective neuroscience; base; behavior measurement; blood oxygenation level dependent response; career; career development; clinical care; depressive symptoms; design; follow-up; improved; medical schools; neural circuit; neuroimaging; neuromechanism; novel; prevent; relating to nervous system

DESCRIPTION (provided by applicant): This K01 proposal is designed provide the training needed to facilitate a career that (1) develops computational models that aid in our understanding of depression; (2) identifies neural circuits that contribute to depression vulnerability and severity; and (3) identifies, creates, or refines treatments that target specific neural mechanisms of depression. To realize his goals the candidate has proposed a program of training to foster expertise in applying neuroimaging and computational modeling techniques to research focused on identifying and targeting neural deficits driving rumination in depression. Rumination is a potential mechanism underlying the etiology and maintenance of depression that is not well understood or adequately targeted in existing treatments. A significant portion of depressive rumination entails a causal search for the reasons one is depressed, that typically leads a depressed individual to examine his/her most pressing problems and concerns in an attempt to understand and solve them. However, this process does not lead to the generation of solutions. Hence, the candidate has conceptualized aspects of rumination as a depressed person's failed attempts to engage in problem-solving. Neuroimaging has produced promising results in identifying mechanisms, but has focused on a restricted set of features of depression generally not involving neural mechanisms of problem-solving. In order to carry out this needed research, the candidate has formulated a detailed career development plan. This plan focuses on (1) expanding his current training in neuroimaging assessment; (2) training him in the paradigms of cognitive affective neuroscience and intervention research; and (3) enhancing his knowledge of using computational modeling to understand brain functioning in psychopathology. This training will be achieved through didactic coursework, neuroimaging workshops, tutorials in computational modeling, and training in clinical intervention research. Training will also be facilitated through ongoing supervision and consultation with experts in relevant fields. This training will be used to conduct research that specifically aims to (1) identify, validate, and understand neural circuits associated with rumination; (2) identify neural deficits that inhibit problem-solving and drive rumination; and (3) examine the potential for problem-solving training to remediate neural deficits driving rumination in depression. The proposed training and research will be conducted in the Department of Psychiatry, at the University of Pittsburgh School of Medicine. The Department of Psychiatry houses several world-renowned clinical affective neuroscientists and is affiliated with one of the premier centers for understanding the neural basis of cognition in the country. The proposed research will take place in three stages to achieve its specific aims. In stage I, depressed and healthy control participants will be induced to ruminate while undergoing functional magnetic resonance imaging (fMRI). Group differences in activation and communication between brain regions facilitating problem-solving will then be examined. Subsequently, identified neural activity will be validated by associating it with relevant behavioral constructs, for example, measures of rumination. These results will facilitate the mapping of brain regions underlying rumination and point to mechanisms driving ruminative processing. In stage II, a computational model will be created to clarify the mechanisms underlying poor problem-solving and thus rumination in depression. This model will then be used to make predictions of neural deficits in depression during problem-solving. These predictions will be evaluated by observing brain activity in depressed and healthy subjects during the completion of a problem-solving task using fMRI. Identified neural mechanisms underlying deficits in problem-solving hypothesized to drive rumination will be validated by examining the degree to which this pattern of deficits is associated with the same pattern of deficits during ruminative processing. These results will facilitate the identification of mechanisms diving rumination in depression. In stage III, a subset of depressed participants will be asked to engage in a cognitive problem-solving training protocol designed to target the identified neural deficits. Change in brain activity from the baseline assessment will be evaluated using a follow-up fMRI assessment of rumination and problem-solving. If successful these results will suggest a means of directly targeting neural mechanisms driving rumination in depression that could be fully developed as an adjunctive treatment in future research. In summary, this proposal seeks to broaden the current focus of research into the neuropathophysiology of depression beyond its current scope of examining markers and mechanisms underlying anhedonia and chronic depressed mood. The current proposal will elucidate the neural circuits underlying rumination in depression by imaging tasks which specifically activate these circuits and showing their relevance to functioning and mechanistic change. Surprisingly very little is known regarding the neural substrates of rumination. The current conceptualization of rumination in depression as a disrupted functional process has allowed for the identification of novel neural mechanisms that do not appear to be targeted in current treatments. Successfully identifying and addressing these deficits may prove in future research to provide certain depressed individuals with lasting recovery.

描述（由申请人提供）：此K 01提案旨在提供促进职业所需的培训，（1）开发有助于我们理解抑郁症的计算模型;（2）识别导致抑郁症脆弱性和严重性的神经回路;（3）识别，创建或改进针对抑郁症特定神经机制的治疗。为了实现他的目标，候选人提出了一项培训计划，以培养将神经成像和计算建模技术应用于研究的专业知识，这些研究的重点是识别和瞄准抑郁症中驱动反刍的神经缺陷。沉思是抑郁症的病因和维持的潜在机制，在现有的治疗中还没有得到很好的理解或充分的靶向。抑郁性反刍的一个重要部分需要寻找一个人抑郁的原因，这通常会导致抑郁症患者检查他/她最紧迫的问题和担忧，试图理解和解决它们。然而，这一过程并没有导致解决方案的产生。因此，这位候选人将沉思的各个方面概念化为抑郁症患者解决问题的失败尝试。神经影像学在识别机制方面取得了可喜的成果，但集中在一组有限的抑郁症特征上，通常不涉及解决问题的神经机制。为了进行这项必要的研究，候选人制定了详细的职业发展计划。该计划的重点是（1）扩大他目前在神经影像学评估方面的培训;（2）在认知情感神经科学和干预研究的范式方面培训他;（3）提高他使用计算建模的知识，以了解精神病理学中的大脑功能。这种培训将通过教学课程，神经影像学研讨会，计算建模教程和临床干预研究培训来实现。还将通过持续监督和与相关领域专家的协商，为培训提供便利。该培训将用于进行研究，具体目的是（1）识别，验证和理解与反刍相关的神经回路;（2）识别抑制解决问题和驱动反刍的神经缺陷;（3）检查解决问题培训的潜力，以修复抑郁症中驱动反刍的神经缺陷。拟议的培训和研究将在匹兹堡大学医学院精神病学系进行。精神病学系拥有几位世界知名的临床情感神经科学家，并隶属于了解该国认知神经基础的首要中心之一。拟议的研究将分三个阶段进行，以实现其具体目标。在第一阶段，抑郁和健康的对照参与者将被诱导反刍，同时接受功能性磁共振成像（fMRI）。然后将研究促进解决问题的大脑区域之间的激活和通信的组差异。随后，将通过将其与相关行为结构（例如，反刍的测量）相关联来验证所识别的神经活动。这些结果将有助于映射大脑区域潜在的反刍和点的机制驱动反刍处理。在第二阶段，将创建一个计算模型，以澄清潜在的机制，解决问题的能力差，从而在抑郁症反刍。然后，这个模型将被用来预测抑郁症在解决问题过程中的神经缺陷。这些预测将通过观察抑郁症和健康受试者在使用功能磁共振成像完成解决问题任务期间的大脑活动进行评估。通过研究这种缺陷模式与反刍处理过程中相同缺陷模式的相关程度，将验证假设驱动反刍的问题解决缺陷的神经机制。这些结果将有助于识别抑郁症的潜水反刍机制。在第三阶段，一部分抑郁的参与者将被要求参与一个旨在针对已识别的神经缺陷的认知问题解决训练方案。将使用反刍和解决问题的随访fMRI评估来评价脑活动相对于基线评估的变化。如果成功的话，这些结果将表明一种直接靶向抑郁症中驱动反刍的神经机制的方法，这种方法可以在未来的研究中作为一种预防性治疗方法得到充分发展。总之，这一建议旨在扩大目前的研究重点到抑郁症的神经病理生理学超出其目前的范围检查标记物和机制的快感缺乏和慢性抑郁情绪。目前的建议将阐明抑郁症反刍的神经回路的成像任务，具体激活这些电路，并显示其相关的功能和机制的变化。令人惊讶的是，关于反刍的神经基质知之甚少。目前的概念，反刍抑郁症作为一个中断的功能过程，允许识别新的神经机制，似乎没有在目前的治疗目标。成功地识别和解决这些缺陷可能会在未来的研究中证明，为某些抑郁症患者提供持久的恢复。