CRCNS: Collective Coding in Retinal Circuits

CRCNS：视网膜回路的集体编码

• 批准号: 1208027
• 负责人: Eric Shea-Brown
• 金额: $ 50万
• 依托单位: University of Washington
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-09-15 至 2017-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1208027&HistoricalAwards=false
• 关键词: CRCNS; Collective; Coding; Retinal; Circuits

Circuits across the brain display correlated activity, in which the responses among neurons are coordinated at a level beyond that expected from the stimulus structure itself. What role does such correlated activity play in neural coding? The retina provides a strong opportunity for progress: widespread correlated activity is generated by key circuit mechanisms that recur throughout the brain. Moreover, the impact of these mechanisms can be studied in the context of stimuli with clear functional significance. Nevertheless, circuit-level nonlinearities at multiple locations cause retinal outputs to depend on stimuli in a manner that defies traditional filter-based models. This demands a tightly coupled computational and experimental approach: purely computational attacks will become lost in the combinatorics of all possible circuit configurations at the difficult "mesoscales" relevant to retinal computation, where averaging approaches fail; purely experimental strategies cannot predict and prioritize the most critical circuit mechanisms and stimulus parameters to explore. The investigators apply this interdisciplinary approach to the mechanisms producing correlated activity in directionally-selective (DS) ganglion cells. In particular, they determine how convergent and divergent pathways in the DS cell circuit interact to shape correlations and encoded information across the cell population, and asses the possible roles of recurrent coupling in modulating this process. These circuit features are the basis of correlated activity in many retinal pathways, and in circuits throughout the brain. Thus, our findings will guide studies of collective neural computation and dynamics currently under intense study in a variety of domains. The brain translates the sensory environment into its own code, that of neural spikes distributed across vast numbers of neurons. Neuroscience seeks to understand the nature of this code -- what aspects of the spiking activity carry what information, how it is implemented by the cellular hardware of the brain, and how this process can fail in disease. A key puzzle is deciphering what it means when many neurons spike simultaneously -- is this just inevitable statistical coincidence, an artifact of neural hardware, or a key symbol in the code? The investigators take a direct approach to answering this question in the earliest stage of the visual pathway, the retina. Here, the team rigorously combines experiment and theory to connect biological circuit mechanisms and coding, and to identify principles that could be tested in other brain areas. Matching the interdisciplinary demands of this endeavor, investigators from Applied Mathematics and Physiology and Biophysics will unite, and will mentor a small team of undergraduate, graduate, and postdoctoral researchers with diverse backgrounds including both mathematics and biology. They will share their results with peers through an open, user-friendly database, and their most exciting findings with students in the interdisciplinary courses that they teach.

整个大脑的回路显示出相关的活动，其中神经元之间的反应被协调到一个超出刺激结构本身预期的水平。这种相互关联的活动在神经编码中扮演什么角色？视网膜为进步提供了强大的机会：广泛相关的活动是由大脑中反复出现的关键电路机制产生的。此外，这些机制的影响可以在具有明确功能意义的刺激的背景下进行研究。然而，多个位置的电路级非线性导致视网膜输出依赖于刺激，其方式与传统的基于过滤器的模型不符。这需要一种紧密耦合的计算和实验方法：纯粹的计算攻击将在与视网膜计算相关的困难“中尺度”的所有可能电路配置的组合中迷失，其中平均方法失败；纯粹的实验策略不能预测和优先考虑最关键的电路机制和刺激参数来探索。研究人员将这种跨学科的方法应用于定向选择性(DS)神经节细胞产生相关活动的机制。特别是，他们确定了DS细胞电路中的会聚和发散通路如何相互作用，以形成跨细胞群体的相关性和编码信息，并评估了反复耦合在调节这一过程中的可能作用。这些回路特征是许多视网膜通路和整个大脑回路相关活动的基础。因此，我们的发现将指导对集体神经计算和动力学的研究，目前这些研究正在各个领域进行密集研究。大脑将感觉环境转化为自己的代码，即分布在大量神经元上的神经峰。神经科学试图理解这种代码的性质--尖峰活动的哪些方面携带什么信息，它是如何由大脑的细胞硬件实现的，以及这个过程如何在疾病中失败。一个关键的难题是，当许多神经元同时放电时，破译它意味着什么--这只是不可避免的统计巧合，是神经硬件的产物，还是代码中的关键符号？研究人员在视觉通路的最早阶段--视网膜--采取了直接的方法来回答这个问题。在这里，研究小组将实验和理论严格结合起来，将生物回路机制和编码联系起来，并确定可以在其他大脑区域测试的原理。与这一努力的跨学科需求相匹配，应用数学、生理学和生物物理学的研究人员将联合起来，并将指导一小批具有不同背景的本科生、研究生和博士后研究人员，包括数学和生物学。他们将通过一个开放的、用户友好的数据库与同行分享他们的结果，并与他们教授的跨学科课程的学生分享他们最令人兴奋的发现。