Understanding the neural and cognitive mechanisms of attributional styles and credit assignment in depression

了解抑郁症归因风格和信用分配的神经和认知机制

• 批准号: MR/N014448/1
• 负责人: Jacqueline Scholl
• 金额: $ 61.23万
• 依托单位: University of Oxford
• 依托单位国家: 英国
• 项目类别: Fellowship
• 财政年份: 2016
• 资助国家: 英国
• 起止时间: 2016 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=MR%2FN014448%2F1
• 关键词: Understanding; neural; cognitive; mechanisms; attributional

Depression is the most common psychiatric illness. Yet, its causes remain poorly understood, despite considerable amount of research. I propose a novel approach to understanding depression, namely to investigate the role of credit assignment - or causal attribution - in depression. Credit assignment is about learning the causes of events when there are different potential causes. My experiments will involve measuring credit assignment behaviour in human participants, as well as assessing the underlying neural processes using modern brain imaging techniques.In a nutshell, I will examine whether in depression, patients have problems with correctly attributing positive or negative outcomes to different sources - do they have a tendency to falsely belief that they are the source of negative outcomes? But that on the other hand, positive outcomes are due to external causes, such as the environment or other people? Do they only have problems identifying the source for outcomes external to them or does this extend to their own emotions, such as low mood? Any of these aberrant credit assignment processes could explain how depression maintains itself by continuously reinforcing negative views and attitudes about the self, thus leading to low mood.To investigate what types of credit assignment are changed in depression, I propose a set of paradigms each testing experimentally a different aspect of credit assignment in depression. For this, I will use a computational psychiatry approach. This means, I will develop models describing the complex process of credit assignment in my paradigms in terms of mathematically defined aspects. For example, firstly making a decision in the expectation that it will lead to a certain outcome. Then assessing how the actual outcome compares to your expectation. And finally assigning credit to the internal or external causes that seem most likely. I can then assess which of the different aspects are more specifically affected in depression. To test the neural effects, I will combine these measurements of behaviour with measurements of brain activity using functional magnetic resonance imaging (fMRI). I will use fMRI to identify the brain areas that are particularly engaged by specific aspects of credit assignment. Subsequently, I can test how deficits in credit assignment in depression can be linked to specific brain areas. In the past, cognitive neuroscience has been particularly fruitful in dissociating cognitive sub-processes as they often map onto very distinct brain regions. To summarise, I am proposing a series of experiments looking at how patients with depression assign credit to different outcomes when there are multiple causes. I will investigate this question neurally and using quantitative computational modelling. Thus my proposal is an attempt to bridge the gap between psychiatric concepts and mechanistic models from cognitive neuroscience and psychology. In particular, my work will contribute to understanding some of the neural and behavioural mechanisms of the changes occurring in depression and attempts to treat it, using a multi-disciplinary approach.

抑郁症是最常见的精神疾病。然而，尽管进行了大量研究，但对其原因仍知之甚少。我提出了一种理解抑郁症的新方法，即研究信用分配（或因果归因）在抑郁症中的作用。学分分配是指当存在不同的潜在原因时了解事件的原因。我的实验将涉及测量人类参与者的信用分配行为，以及使用现代大脑成像技术评估潜在的神经过程。简而言之，我将检查患有抑郁症的患者是否在正确地将积极或消极结果归因于不同来源方面存在问题——他们是否倾向于错误地相信自己是消极结果的根源？但另一方面，积极的结果是由于外部原因，例如环境或其他人吗？他们是否只在识别外部结果的来源方面存在问题，还是这会延伸到他们自己的情绪，例如情绪低落？任何这些异常的信用分配过程都可以解释抑郁症如何通过不断强化对自我的负面看法和态度来维持自身，从而导致情绪低落。为了研究抑郁症中哪些类型的信用分配发生了变化，我提出了一组范式，每个范式都通过实验测试抑郁症中信用分配的不同方面。为此，我将使用计算精神病学方法。这意味着，我将开发模型，根据数学定义的方面，描述我的范式中学分分配的复杂过程。例如，首先做出决定，期望它会导致某种结果。然后评估实际结果与您的期望的比较。最后将功劳归因于最有可能的内部或外部原因。然后我可以评估哪些不同方面更具体地受到抑郁症的影响。 为了测试神经效应，我将使用功能磁共振成像 (fMRI) 将这些行为测量与大脑活动测量结合起来。我将使用功能磁共振成像来识别与学分分配的特定方面特别相关的大脑区域。随后，我可以测试抑郁症的学分分配缺陷如何与特定的大脑区域联系起来。过去，认知神经科学在分离认知子过程方面特别富有成效，因为它们通常映射到非常不同的大脑区域。总而言之，我提出了一系列实验，看看抑郁症患者在有多种原因时如何将不同的结果归咎于不同的结果。我将使用定量计算模型从神经角度研究这个问题。因此，我的建议是试图弥合精神病学概念与认知神经科学和心理学的机械模型之间的差距。特别是，我的工作将有助于理解抑郁症发生变化的一些神经和行为机制，并尝试使用多学科方法来治疗抑郁症。

项目成果

Differential Relationship Between Meditation Methods and Psychotic-Like and Mystical Experiences

冥想方法与精神病和神秘体验之间的区别关系

• DOI: 10.31234/osf.io/7cwhv
• 发表时间: 2023
• 作者: Palmer T

Single-dose hydrocortisone administration does not enhance motor sequence learning or reward learning in humans.

单剂量氢化可的松给药不会增强人类的运动序列学习或奖励学习。

• DOI: 10.1177/0269881118760664
• 发表时间: 2018
• 期刊: Journal of psychopharmacology (Oxford, England)
• 作者: Günthner J

Prospection, Perseverance, and Insight in Sequential Behavior.

对顺序行为的抗辩，毅力和见识。

• DOI: 10.1016/j.neuron.2018.08.018
• 发表时间: 2018-09-05
• 期刊: Neuron
• 影响因子: 16.2
• 作者: Kolling N;Scholl J;Chekroud A;Trier HA;Rushworth MFS
• 通讯作者: Rushworth MFS

The NMDA receptor partial agonist d-cycloserine does not enhance motor learning.

• DOI: 10.1177/0269881116658988
• 发表时间: 2016-10
• 期刊: Journal of psychopharmacology (Oxford, England)
• 作者: Günthner J;Scholl J;Favaron E;Harmer CJ;Johansen-Berg H;Reinecke A
• 通讯作者: Reinecke A

The relationship between apathy and impulsivity in large population samples.

• DOI: 10.1038/s41598-021-84364-w
• 发表时间: 2021-03-01
• 期刊: Scientific reports
• 影响因子: 4.6
• 作者: Petitet P;Scholl J;Attaallah B;Drew D;Manohar S;Husain M
• 通讯作者: Husain M