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Pinpointing the Cerebellum's Contribution to Social Reward Processing

Pinpointing the Cerebellum's Contribution to Social Reward Processing
确定小脑对社会奖励处理的贡献
批准号:
10541308
负责人:
Haroon Skander Popal
金额:
$3.33万
依托单位国家:
美国
项目类别:
财政年份:
2022
资助国家:
美国
项目状态:
未结题
起止时间:
2022-07-01 至 2027-06-30

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中文摘要
翻译
项目摘要 小脑一直被认为只处理运动信息。然而,越来越多的文献 这表明小脑在多个领域的过程中发挥着作用。小脑病变患者 典型的有运动缺陷,但在某些情况下,也有执行功能,情感, 加工、语言和社会认知。多种精神疾病,包括自闭症谱系障碍 (ASD),与小脑的结构和功能差异有关。此外,许多 功能性磁共振成像(fMRI)研究已经报道了小脑的神经反应 与许多非运动任务有关。这些发现提供了证据表明,小脑参与了非- 运动任务,但小脑如何在这些任务中发挥作用仍然完全不清楚。 F99阶段:已经成功地开发了模型来解释小脑在运动中的作用。 处理.这些模型强调小脑作为一个学习机器的作用, 通过将现实与内部模型进行在线比较,从而利用感官 预测误差。最近在人类和小鼠身上的发现表明,小脑的某些部分参与了 奖励处理;主要研究基底神经节的过程。是 不清楚小脑在这种奖励过程中扮演什么样的计算角色,因为小脑一直是 据说是在没有奖励信息的情况下明确操作的。为了理解这一点,目前的建议将使用功能磁共振成像, 研究小脑对传统(例如金钱)和社会奖励的贡献 处理,并将其与基底神经节在奖励处理中的作用区分开来。培训计划 该提议包括与奖励处理有关的计算建模方法的培训。它还 包括社会神经科学理论和任务设计的培训。计算建模将使我们能够 探索不容易从单独的实验行为观察中辨别的参数, 直接测试理论小脑的算法处理,通过提供洞察小脑的 跨多个任务域的算法计算,以及它在传统和社会奖励处理中的作用。 这些发现将提供对小脑机械能力的深入了解。 K 00阶段:ASD患者在社会认知和社会奖励处理方面表现出缺陷。结构上, 功能和连接的差异使小脑与这种疾病有关,新生儿 小脑损伤是ASD的第二大预测因素。K 00阶段将调查 小脑在孤独症患者中的表现,他们在社会奖励处理方面有缺陷。培训计划 在这个阶段的建议将集中在学习强化学习的计算建模, 将这些模型应用于功能磁共振成像的小脑功能。培训计划还包括发展目标 指导技能,以帮助申请人建立一个多元化和包容性的独立研究实验室。
英文摘要
PROJECT SUMMARY The cerebellum has long been thought to solely process motor information. Yet, there is a growing literature that points to a role of the cerebellum in processes across multiple domains. Individuals with cerebellar lesions classically have motor deficits but, in some instances, also have problems with executive functioning, emotion processing, language, and social cognition. Multiple psychiatric disorders, including autism spectrum disorders (ASD), have been linked to structural and functional differences in the cerebellum. Moreover, numerous functional magnetic resonance imaging (fMRI) studies have reported neural responses in the cerebellum related to a host of non-motor tasks. These findings provide evidence that the cerebellum is involved in non- motor tasks, but it remains entirely unclear how the cerebellum contributes to performance on these tasks. F99 Phase: Models have been successfully developed to explain the role of the cerebellum in motor processing. These models emphasize the cerebellum's role as a learning machine that modulates and perfects ongoing processing through the online comparison of reality to an internal model, thereby utilizing sensory prediction errors. Recent findings in humans and mice suggest that portions of the cerebellum are involved in reward processing; a process which has primarily been investigated in regards to the basal ganglia. It is unclear what computational role the cerebellum plays in this reward processing, as the cerebellum has been said to explicitly operate without reward information. To understand this, the present proposal will use fMRI in healthy young adults to study the cerebellum's contribution to both traditional (e.g. monetary) and social reward processing, and to differentiate it from the role of the basal ganglia in reward processing. The training plan for this proposal includes training in computational modeling methods related to reward processing. It also includes training in social neuroscience theories and task design. Computational modeling will allow us to explore parameters that are not easily discernable from behavioral observations of an experiment alone and to directly test theories about the cerebellum's algorithmic processing, by providing insight into the cerebellum's algorithmic computations across multiple task domains, and its role in traditional and social reward processing. These findings will provide insight into the cerebellum's mechanistic capabilities. K00 Phase: Individuals with ASD exhibit deficits in social cognition and in social reward processing. Structural, functional, and connectivity differences have implicated the cerebellum in this disorder, with neonatal cerebellar damage being the second highest predictor of ASD. The K00 phase will investigate how the cerebellum performs in individuals with autism, who have deficits in social reward processing. The training plan in this phase of the proposal will focus on learning computational modeling of reinforcement learning and applying these models to cerebellum functioning with fMRI. The training plan also includes goals to develop mentorship skills to prepare the applicant to establish a diverse and inclusive independent research laboratory.
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