Resolving conflicts between decision-making algorithms

项目摘要 目前的理论认为，哺乳动物大脑中的行为选择取决于 多个神经可分离算法之间的相互作用。的 多个决策系统的存在提出了一些新的问题， 在单一决策者中：当这些系统选择时会发生什么 相互矛盾的行为？这些冲突是如何解决的？许多病症 (OCD，饮食失调，药物成瘾）和一些RDOC相关的 功能障碍（强迫性，习惯，认知和“自我”控制问题） 都被建议依赖于这些冲突的解决方案， 决策系统。最近开发的人类任务已经证明能够 将这些决策系统置于冲突中进行研究。我们翻译了， 验证了这个新人类任务的啮齿动物版本。我们将建立在我们的 在神经集成记录和计算分析方面的专业知识 来研究如何解决这些系统之间的冲突。使用DREADD 操作和神经集成记录技术，我们建议识别 解决冲突的机制和计算 这些决策系统。

Project summary Current theories suggest that action-selection in the mammalian brain depends on an interaction between multiple, neurally-separable algorithms. The existence of multiple decision-systems opens up novel questions that do not exist within a unitary decision-maker: What happens when these systems select conflicting actions? How are those conflicts resolved? A number of disorders (OCD, eating disorders, drug addiction) and a number of RDOC-related dysfunctions (compulsivity, habits, and issues of cognitive and “self-” control) have all been proposed to depend on resolutions of conflicts between these decision-systems. Recently developed human tasks have proved capable of putting these decision-systems into conflict for study. We have translated and validated a rodent version of this new human task. We will build on our established expertise in neural ensemble recording and computational analysis to examine how conflicts between these systems is resolved. Using DREADD manipulation and neural ensemble recording technologies, we propose to identify the mechanisms and computations that underlie conflict resolution between these decision-systems.