Recurrent Neual Circuit Basis of Time Integration and Decision Making

描述(由申请人提供)：我们研究的长期目标是阐明决策及其执行控制的细胞和回路机制。人类和动物的灵活行为依赖于大脑随着时间的推移积累信息、深思熟虑选择选项、抑制优势反应和选择有目的行动的能力。已知额叶和顶叶皮质对决策至关重要，但在机制水平上对这一复杂认知网络的运作仍知之甚少。我们认为，决策中感觉信息或计划动作的积累是由强递归回路的神经活动实例化的，这些回路可以被概念化为吸引子网络。此外，时间整合过程不是固定的，但可以很容易地调整以优化行为。我们将与实验者密切合作，使用基于神经生理学的尖峰网络模型来检验这一假说。我们的模型将根据在眼球运动决策任务中表现良好的猴子收集的行为和生理数据(单细胞和局部场电位)进行定量测试。模型预测将通过实验进行验证。人类和猴子的眼球运动系统的结构相似，因此我们在工作中获得的知识可能有助于我们理解人类的决策。这个应用程序有四个具体目标。在目标1中，我们将分析皮层回路中随机的、但相关的反射神经动力学，该回路是感觉证据的缓慢时间整合和感知决策中反应时间的可变性的基础。目的2将研究感觉和运动过程之间的相互作用，以及对动作的抑制控制，在顶叶-额叶回路中。在目标3中，我们将在一个包括皮质、基底节和上丘的大规模电路模型中，研究决策如何依赖于选择方案的数量及其相似性，以及模拟决策计算如何导致类别选择的读出。目标4将集中于由奖赏依赖的突触可塑性和几种执行控制机制的协同作用所体现的决策的最优化和灵活性。综上所述，这项拟议的研究将首次推进顶叶-额叶-基底神经节网络中感觉-运动决定的详细电路模型。

DESCRIPTION (provided by applicant): The long-term goal of our research is to elucidate the cellular and circuit mechanisms of decision making and its executive control. Flexible behavior in humans and animals relies on the brain's ability to accumulate information over time, deliberate about choice options, inhibit prepotent responses, and select purposeful actions. The frontal and parietal cortices are known to be critical to decision making, but the operation of this complex cognitive network is still poorly understood at the mechanistic level. We propose that accumulation of sensory information or planned action in decision making is instantiated by neural activity of strongly recurrent circuits that can be conceptualized as attractor networks. Moreover, the time integration process is not fixed, but can be readily adjusted to optimize behavior. We will test this hypothesis using neurophysiologically-based spiking network models, in close collaboration with experimentalists. Our models will be quantitatively tested against behavioral and physiological data (single-cell and local field potential) collected from behaving monkeys in oculomotor decision tasks. Model predictions will be checked experimentally. The structure of the oculomotor system is similar in humans and monkeys, therefore the knowledge gained in our work will be likely to contribute to our understanding of human decision making. This application has four Specific Aims. In Aim 1 we will analyze stochastic, yet correlated, reverberatory neural dynamics in a cortical circuit that underlies the slow time integration of sensory evidence and the variability of reaction times in perceptual decisions. Aim 2 will investigate the interplay between sensory and motor processes, and inhibitory control of action, in a parieto-frontal circuit. In Aim 3, we will examine how decision making depends on the number of choice alternatives and their similarity, and how analog decision computation leads to the readout of a categorical choice, in a large-scale circuit model encompassing cortex, basal ganglia, and superior colliculus. Aim 4 will be focused on optimality and flexibility of decision making instantiated by reward-dependent synaptic plasticity and the concerted action of several executive control mechanisms. Taken together, the proposed research will advance, for the first time, a detailed circuit model of sensory-motor decisions in the parieto-fronto-basal ganglia network.