Translating from Rats to Humans: A Human Foraging Model of Decision-Making

 描述(申请人提供)：上瘾的动物模型是精神病理学中最受推崇的模型之一。因此，针对人类的治疗方法往往是基于动物成瘾模型而开发的。然而，这些临床前模型和治疗结果之间仍然存在脱节。一些研究人员认为，将临床前模型转换为临床模型的差距源于未经测试的假设，即不同物种在建模任务中招募相同的认知底物。因此，有必要进行研究，以验证动物和人类的决策系统具有可比性，这反过来又可以提高这些研究阶段的结果的概括性。需要有效的翻译范式来测试跨物种认知过程的相似性(或差异性)。本提案介绍了一种新的人类体验式觅食范式，它是基于大鼠(Restaurant Row)的去/不去觅食范式而设计的。在Restaurant Row范例中，动物有固定的时间穿过圆形轨道，在可变延迟时间后从不同的“餐馆”收集食物奖励。这一范式成功地捕捉到了个体偏好的差异，以及情绪结构(如后悔、失望)的行为和神经特征。在拟议的人类变体(称为Web-Surf任务)中，人类在不同延迟后呈现不同类型视频片段的视频画廊之间旅行时，会做出一系列进行/不进行的决定。人类的变种被设计成模仿老鼠的变种，同时也考虑了自然的人类行为学。对人类受试者的初步分析表明，这两种模式捕捉到了相似的行为机制。这个被提议的项目的第一个目标是检查网络冲浪任务是否等同地测量情绪结构，例如后悔。第一个目标还试图阐明行为任务表现的个体差异是否映射到冲动特征的变化上。拟议项目的第二个目标是确定Web-Surf任务是否捕捉到了老鼠身上看到的深思熟虑和情绪处理的神经特征。这将使用处理功能神经成像数据的一般线性建模和机器学习方法来完成。这项任务可能在缩小临床前研究和临床研究之间的差距方面发挥关键作用，更重要的是，推动人类成瘾治疗的发展。

 DESCRIPTION (provided by applicant): Animal models of addiction are some of the most highly regarded models of psychopathology. As a result, treatments for humans are often developed based on animal addiction models. However, there remains a disconnection between these pre-clinical models and treatment outcomes. Some researchers suggest that the gap in translating pre-clinical to clinical models stems from untested assumptions that different species recruit the same cognitive substrates on the modeled tasks. Therefore, there is a need for research than can verify that animal and human decision-making systems are comparable, which in turn, could improve the generalizability of results across these research stages. Effective translational paradigms are needed to test similarities (or differences) in cognitive processes across species. The present proposal introduces a novel experiential foraging paradigm for humans, which was designed based on a go/no-go foraging paradigm for rats (Restaurant Row). In the Restaurant Row paradigm, an animal has a fixed amount of time to traverse a circular track collecting food rewards after variable delay times from different "restaurants." This paradigm successfully captured individual differences in preference, as well as behavioral and neural signatures of emotional constructs (e.g. regret, disappointment). In the proposed human variant (called the Web-Surf task), humans make a series of go/no-go decisions as they travel between video galleries that present different types of video clips after variable delays. The human variant was designed to mimic the rat variant while also considering natural human ethology. Preliminary analyses in human subjects suggest the two paradigms capture similar behavioral mechanisms. The first aim of the proposed project is to examine whether the Web- Surf task equivalently measures emotional constructs, such as regret. The first aim also seeks to elucidate whether individual differences in behavioral task performance map onto variations in impulsive traits. The second aim of the proposed project is to determine whether the Web-Surf task captures neural signatures of deliberation and emotional processing as seen in rats. This will be accomplished using general linear modeling and machine learning approaches for processing functional neuroimaging data. This task could be pivotal in reducing the gap between pre-clinical and clinical research, and more importantly, advancing the development of addiction treatments for humans.