Spike Timing Defects and State Representation Impairments in Nonhuman Primates

项目总结：项目1 项目1的目的是使用非人类灵长类动物来检查前额叶局部回路和分布 与个人相关的状态表征功能障碍相关的网络损害 精神错乱。项目1将介绍前额叶神经元之间通过突触介导的功能相互作用 网络到支持状态表示过程的计算。在目标1中，我们将量化泛函 通过测量动作电位(尖峰)的时间相关性来实现神经相互作用 神经元之间的突触相互作用。在目标2中，我们将通过药物作用来破坏这些相互作用 阻断NMDA受体(NMDAR)，在此期间诱导一段时间的认知损害 猴子在DPX决策任务中犯下的行为错误模式与人类相似 精神分裂症。我们将记录前额叶皮质和解剖连接的大脑区域的神经活动 (后顶叶皮质和背侧纹状体)在认知损害期间同时存在，而 猴子执行DPX和Bandit任务，这允许我们索引状态估计、状态学习和状态 稳定过程。我们将发现减少NMDAR突触传递如何改变功能相互作用 前额叶网络中神经元之间的相互作用，导致状态表征过程中的计算失败。 为了给我们可以在人体中记录的神经信号提供一座桥梁，我们将记录反射的神经信号 脑活动在微尺度(单个神经元动作电位)、中尺度(局部场电位 皮层)和宏观尺度(局域场电位和跨皮质区域的脑电)，以及 同时连接在一起的结构。我们将使用因果发现分析来确定可以 在人类可用的神经生理学技术更有限的情况下被发现(对于项目3和4)。AS 项目4确定了改善状态估计和状态稳定性的特定认知训练方案 患有早期精神病的个体，项目1将把这些范例反向翻译给猴子，以识别 训练诱导的神经生理学(微观、中观和宏观)吸引器网络参数的变化 电路)级别。

PROJECT SUMMARY: PROJECT 1 The purpose of PROJECT 1 is to use nonhuman primates to examine prefrontal local circuit and distributed network impairments associated with state representation dysfunctions of relevance to individuals with psychosis. PROJECT 1 will relate synaptically mediated functional interactions between neurons in prefrontal networks to computations that support state representation processes. In Aim 1, we will quantify functional neural interactions by measuring temporal correlations in the timing of action potentials (‘spikes’) imposed by synaptic interactions between the neurons. In Aim 2, we will disrupt those interactions by pharmacologically blocking NMDA receptors (NMDAR), which induces a period of transient cognitive impairment during which monkeys commit similar patterns of behavioral errors during the DPX decision-making task as do people with schizophrenia. We will record neural activity in prefrontal cortex and anatomically connected brain areas (posterior parietal cortex and the dorsal striatum) concurrently during the period of cognitive impairment, while monkeys perform the DPX and Bandit tasks, which allow us to index state estimation, state learning, and state stability processes. We will discover how reducing NMDAR synaptic transmission alters functional interactions between neurons in prefrontal networks, leading to computational failures in state representation processes. To provide a bridge to neural signals that we can record in humans, we will record neural signals that reflect brain activity at the microscale (single neuron action potentials), mesoscale (local field potentials within a cortical area) and macroscale (local field potentials and EEG across cortical areas) from prefrontal cortex and connected structures simultaneously. We will use causal discovery analysis to identify the parameters that can be found with more limited neurophysiological techniques available in humans (for PROJECTS 3 and 4). As PROJECT 4 identifies specific cognitive training regimens that improve state estimation and state stability in individuals with early psychosis, PROJECT 1 will back-translate these paradigms to monkeys to identify training-induced changes in attractor network parameters at the neurophysiological (micro-, meso- and macro- circuit) levels.