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 结构化塑造和约束信息编码，网络必须动态协调， 以便灵活处理信息。了解神经元信息编码， 神经网络结构，灵活信息处理的动态协调机制，以及 特别是它们之间的相互作用，是计算神经科学的一个关键挑战。重要的是， 必须在单个神经元活动的水平上解决，因为粗糙的大脑信号和记录 由于对高度结构化的、快速的和异质的神经元进行平均， 应答拟议项目的目的是：a）描述行为相关的内部和 区域间神经元信息编码、网络通信结构和振荡 在认知上简单的视觉决策任务期间，利用现有的同步通信， 猕猴记录了来自两个皮层区域的许多神经元; B）扩展和概括了 识别编码，通信和振荡同步结构，以更大的神经元网络 在认知上更复杂的视觉决策任务中跨越四个皮层区域， 奖励和努力的基本高级认知因素的系统变化。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 用于大规模同步记录的阵列; c）分析动态相互作用的原因和影响 信息编码，沟通和振荡沟通的认知简单， 复杂的可视化决策需要考虑所有可用的数据集。识别网络的动态交互 在神经元水平上的性质将提供重要的洞察神经机制的基础上， 认知与认知 相关性（参见说明）： 大脑皮层中分散的神经元之间的网络相互作用对于适应性神经元的形成是非常重要的。 认知和行为。使用经验和计算方法相结合的项目将 确定神经元信息如何在神经元网络中编码和动态协调 跨越多个大脑区域由此产生的知识将为神经元基础提供新的见解 包括一系列临床疾病中的脑网络紊乱。

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.