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Neural Computation for Innate Behaviors in the Superior Colliculus

上丘先天行为的神经计算

基本信息

批准号：
10684649
负责人：
MARKUS MEISTER
金额：
$ 37.84万
依托单位：
CALIFORNIA INSTITUTE OF TECHNOLOGY
依托单位国家：
美国
项目类别：
财政年份：
2019
资助国家：
美国
起止时间：
2019-08-15 至 2025-06-30
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10684649
关键词：
Amphibia Anatomy Animals Area Attention Behavior Behavioral Birds Bite Brain Brain Diseases Cells Computer Models Data Dedications Detection Environment Eye Failure Familiarity Fishes Genetic Goals Hippocampus Human Image Instinct Interdisciplinary Study Knowledge Label Laboratory mice Link Literature Location Mammals Memory Mental disorders Methods Modeling Molecular Motor Movement Mus Neurons Neurosciences Optics Output Pathway interactions Process Productivity Research Research Project Grants Resources Retina Retinal Ganglion Cells Role Sensory Signal Transduction Specificity Stimulus Testing Time Vertebrates Vision Visual Visual Cortex Visual Fields Work awake cell type comparative directed attention image processing multisensory neural neural circuit neural model neurotransmission novel programs response sensory input superior colliculus Corpora quadrigemina tool visual information visual memory visual processing visual stimulus

项目摘要

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.

上丘先天行为的神经计算拟议研究的长期目标是了解大脑如何理解大脑的冲击感官数据仅提取做出决策所需的少量相关知识。具体我们将关注实验室小鼠的先天行为，例如逃避威胁、追逐小猎物、和视觉导航。这些都是稳健且可靠的行为，需要快速、灵敏的检测和视觉场景中特定特征的定位。哺乳动物有两个专门负责视觉处理的大脑区域：丘脑皮质通路和上丘脑皮质通路。丘。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。它接收来自视网膜的直接感觉输入，其输出神经元产生运动信号，可以引导动物的动作。一般来说，上丘被认为是识别最场景中的显着点，用于明显的定向动作。它还可以指导隐蔽的方向神经资源，例如当我们“注意”场景中的某个位置时。在最近的研究中，我们确定了 SC 中神经计算的三个方面，这些方面远远超出了 SC 的范围。在视网膜中进行的处理。以本工作为背景，结合前期分析，我们开发了 SC 内神经处理的假设模型。在这里，我们建议测试以下关键方面该模型的目标是开发其定量细节，以便正确地解释提取视觉场景中的显着图像特征。该研究结合了行为方法、神经活动的大规模电学和光学记录，神经回路的操作、回路追踪工具和回路建模。我们将追求以下目标： (1) 了解 SC 不寻常的功能解剖结构，其中视野的不同部分强调不同的视觉特征。 (2) 确定SC如何利用两者来实现选择视觉特征的提取特异性和不变性。 (3) 了解 SC 中一种有趣的图像存储器形式，它可以抑制对熟悉刺激的反应。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视觉皮层的贡献？不同细胞类型在底层神经回路中的作用是什么？如果这些目标得以实现，它们将有助于全面理解大脑如何可靠地、自动识别环境最显着的特征，这是我们互动的重要功能与世界。反过来，这将有助于阐明该过程的失败，正如在各种精神疾病中发生的那样的关注。