Neural Computation for Innate Behaviors in the Superior Colliculus

上丘先天行为的神经计算 这项拟议中的研究的长期目标是了解大脑如何理解 仅提取做出决定所需的几个相关知识的感官数据。具体来说，我们将 关注实验室老鼠的先天行为，如逃避威胁，追逐小猎物， 和视觉导航。这些都是健壮可靠的行为，需要快速而灵敏的检测和 视觉场景中特定特征的本地化。 哺乳动物有两个专门负责视觉处理的大脑区域：丘脑-皮质通路和上脑 丘脑。上丘(SC)是进化上更古老的通路，与非哺乳动物共有 脊椎动物。它从视网膜接受直接的感觉输入，它的输出神经元产生运动信号， 可以控制动物的动作。一般说来，上丘被认为是最能识别 场景中的突出点，用于公开定向动作。它还可以指导隐蔽的方向 神经资源，比如当我们“注意”场景中的某个位置时。 在最近的研究中，我们发现了SC中神经计算的三个方面，它们远远超出了 在视网膜中进行的处理。在这项工作的背景下，结合前面的分析，我们 开发了SC内部神经处理的假设模型。在这里，我们建议测试以下关键方面 这一模型的目标是开发其量化细节，以便正确地解释提取 视觉场景中突出的图像特征。 这项研究结合了行为方法、大规模神经活动的电学和光学记录， 神经电路、电路跟踪工具和电路建模的操作。我们将致力于实现以下目标： (1)了解SC的不寻常功能解剖，由此视野的不同部分强调 不同的视觉特征。(2)确定SC如何利用两者实现精选视觉特征的提取 专一性和不变性。(3)理解SC中一种有趣的图像记忆形式，它抑制了 对熟悉的刺激的反应。两个共同的主题将这些目标联系在一起：这些神经计算是否需要 来自视觉皮质的贡献？不同类型的细胞在基本神经回路中扮演什么角色？ 如果这些目标得以实现，它们将有助于对大脑如何可靠地和 自动识别环境中最显著的特征，这是我们交互的基本功能 和世界在一起。反过来，这将有助于阐明这一过程的失败，就像在各种精神障碍中发生的那样 关注度。

Neural computation for innate behaviors in the superior colliculus The long-term goal of the proposed research is to understand how the brain makes sense of the onslaught of sensory data to extract just the few bits of relevant knowledge needed to make a decision. Specifically we will focus on innate behaviors of the laboratory mouse, such as the escape from a threat, the pursuit of small prey, and visual navigation. These are robust and reliable behaviors that require rapid and sensitive detection and localization of specific features in the visual scene. Mammals have two brain areas dedicated to visual processing: the thalamo-cortical pathway and the superior colliculus. The superior colliculus (SC) is the evolutionarily more ancient pathway, shared with non-mammalian vertebrates. It receives direct sensory input from the retina, and its output neurons produce motor signals that can steer the animal's movements. In general terms, the superior colliculus is thought to identify the most salient points in the scene for the purpose of overt orienting actions. It may also direct the orienting of covert neural resources, like when we “pay attention” to a location in the scene. In recent research we identified three aspects of neural computation in the SC that extend much beyond the processing performed in the retina. On the background of this work, combined with earlier analysis, we developed a hypothetical model of neural processing within the SC. Here we propose to test key aspects of this model, with the goal of developing its quantitative details such that it correctly accounts for the extraction of salient image features from the visual scene. The research combines behavioral methods, large-scale electrical and optical recordings of neural activity, manipulations of neural circuitry, circuit tracing tools, and circuit modeling. We will pursue the following aims: (1) Understand the unusual functional anatomy of the SC whereby different parts of the visual field emphasize different visual features. (2) Determine how the SC achieves the extraction of select visual features with both specificity and invariance. (3) Understand an intriguing form of image memory in the SC that suppresses the response to familiar stimuli. Two common themes connect these aims: Do these neural computations require a contribution from the visual cortex? And what is the role of different cell types in the underlying neural circuits? If these aims are achieved, they will contribute to an integrated understanding of how the brain reliably and automatically identifies the most salient features of the environment, an essential function for our interactions with the world. In turn that will help illuminate failure of that process, as occurs in various psychiatric disorders of attention.