CRCNS: Macaque Cortex Neuronal Network Dynamics related Cognition and Behavior

复杂的认知和行为是由大脑中神经元的网络相互作用产生的。网络 结构塑造和约束信息编码，网络必须动态协调 以便进行灵活的信息处理。了解神经元信息编码， 神经元网络结构，灵活信息处理的动态协调机制，以及 尤其是它们之间的相互作用，是计算神经科学面临的一个关键挑战。重要的是，这是一个挑战 必须在单个神经元活性的水平上解决，因为较粗糙的大脑信号和记录 由于对高度结构、快速和不同种类的神经元进行平均，技术丢失了重要的细节 回应。拟议的项目旨在a)描述与行为相关的内部和外部环境之间的相互作用 区域间神经元信息编码、网络通讯结构和振荡 在认知上简单的视觉运动决策任务中利用现有的同时进行的交流 猕猴对来自两个皮质区域的许多神经元的记录；b)扩展和概括 识别到较大神经元网络的编码、通信和振荡同步结构 在认知上更复杂的视觉运动决策任务中跨越四个皮质区域，包括 奖赏和努力这两个基本高级认知因素的系统变异。为此，两只猴子 将接受相应决策任务的培训，并植入最先进的电极 用于大规模同时录制的阵列；c)分析动态交互的原因和结果 信息编码、通信和振荡通信在认知简单和 使用所有可用的数据集进行复杂的视觉运动决策。识别网络的动态交互 神经元水平的特性将提供对潜在的神经元机制的重要洞察 认知和行为。 相关性(请参阅说明)： 大脑皮质分布的神经元组之间的网络相互作用对适应很重要 认知和行为。利用经验和计算相结合的方法，该项目将 确定神经元网络中神经元信息的编码和动态协调方式 横跨多个脑区。由此产生的知识将为神经元基础提供新的见解。 大脑功能障碍，包括一系列临床疾病中的大脑网络障碍。

Complex cognition and behavior is generated by network interactions of neurons in the brain. Network structure shapes and constrains information encoding, and networks must be dynamically coordinated in order to allow for flexible information processing. Understanding the neuronal information encoding, the neuronal network structure, the dynamic coordination mechanisms for flexible information processing, and especially their interplay, is a key challenge for computational neuroscience. Importantly, thls challenge must be addressed at the level of single neuron actlvity, since coarser brain signals and recording techniques lose important detail due to averaging over highly-structured, fast and heterogeneous neuronal responses. The proposed project aims to a) characterize the interplay of behaviorally relevant intra- and inter-area neuronal information encoding, network communication structure, and oscillatory communication during a cognitively simple visuomotor decision task utilizing existing simultaneous macaque monkey recordings of many neurons from two cortical areas; b) extend and generalize the identified encoding, communication and oscillatory synchronization structure to larger neuronal networks spanning four cortical areas during a cognitively more complex visuomotor decision task including systematic variation of the essential higher cognitive factors of reward and effort. To this end two monkeys will be trained on a corresponding decision-making task and implanted with state-of-the art electrode arrays for large-scale simultaneous recordings; c) analyze the cause and effect of the dynamic interaction of information encoding, communication and oscillatory communication during cognitively simple and complex visuomotor decisions uslng all available datasets. Identifying the dynamic interaction of network properties at the neuronal level will offer significant insight into the neuronal mechanisms underlying cognition and behavlor. RELEVANCE (See instructions): Network interactions of dlstributed sets of neurons in the cerebral cortex are important for adaptlve cognition and behavior. Using a combination of empirical and computational approaches the project will determine how neuronal information is encoded and dynamically coordinated in neuronal networks spanning multiple brain areas. The resulting knowledge will provide new insights into the neuronal basis of brain function, including disturbances of brain networks in a range of clinical disorders.