Cortical microcircuit of performance monitoring: bridging multiscale neuronal activity and electrophysiological signatures in nonhuman primates

项目摘要 错误相关负性（ERN）是衡量管理者核心功能的基本指标 控制自发现以来，研究表明ERN是精神疾病的生物标志物，如 多动症强迫症精神分裂症和焦虑症然而，ERN作为生物标志物的效用取决于我们的 了解它是如何在细胞和电路层面产生的。不同的研究报告称， 由包括前扣带皮层（ACC）和背内侧额叶皮层的内侧额叶区域产生 （DMFC）。然而，皮层机制信号错误和冲突仍然难以捉摸。因此，要移动 研究和临床翻译向前发展，必须克服两个关键障碍：a）需要一个机械的 理解错误/冲突信号中的皮层回路，和B）建立一个理论的 将微电路信号转换为头皮电位的框架。在这个建议中，我将克服这些障碍 通过实施一种新的方法，该方法结合了该区域的解剖信息和连通性， 不同神经元对ERN的贡献，并采用EEG前向建模来翻译它们的贡献 转化为微观信号。我假设，尖峰活动和局部场电位（LFP）从 层状记录可用于预测不同神经元群体对EEG信号的贡献。 该提案的主要研究目标是确定DMFC中引起以下问题的皮质机制 的ERN和阐明ACC的贡献，其EEG签名。培训的主要目标是掌握 有关性能监测和内侧额叶的文献，并获得尖端计算方面的专业知识 神经科学方法在目标1中，我将阐明神经元发电机的ERN在DMFC采用 广义层流群体分析的扩展版本（gLPAextended）。与原始方法相比， 我将把从猕猴的层流记录和解剖学研究中获得的细胞分布 猴子，无颗粒额叶皮层微电路模型的连接性，以及非线性的贡献。 树突机制存在于新皮质锥体细胞上。在目标2中，我将预测 DMFC中皮层电流偶极子的活动，在目标1中获得，采用EEG正向建模。那我就 通过结合逆方法和非线性方法估计ACC中引起ERN的神经元来源， 在从记录的EEG信号中减去DMFC相关EEG之后，使用滤波技术28。使用这些ACC 目前的偶极子估计和gLPA扩展预测的ERN，我将评估的贡献金字塔 从ACC到ERN。这项提案的结果将通过以下方式提供对大脑疾病的回路水平的见解： 将ERN中的变化转化为微电路处理中的变化。我的导师 赞助商，Riera博士和Schall博士，将保证实现本研究和培训目标。 提议

Project Summary The error-related negativity (ERN) is a basic measure of RDoC because it indexes core functions of executive control. Since its discovery, studies have shown that the ERN is a biomarker of psychiatric disorders, such as ADHD, OCD, schizophrenia, and anxiety. However, the utility of the ERN as a biomarker depends on our understanding of how it is generated at the cellular- and circuit-level. Different studies have reported the ERN to be generated by medial frontal areas including anterior cingulate cortex (ACC) and the dorsomedial frontal cortex (DMFC). However, the cortical mechanisms signaling error and conflict remain elusive. Therefore, to move research and clinical translation forward, two critical barriers must be overcome: a) the need for a mechanistic understanding of the cortical circuitry in error/conflict signaling, and b) the establishment of a theoretical framework to translate microcircuit signaling into scalp potentials. In this proposal, I will overcome these barriers by implementing a novel method, which incorporates anatomical information and connectivity of the area, to infer the contributions of distinct neurons to the ERN and employ EEG forward modeling to translate their contributions into microscopic signals. I hypothesize that the spiking activity and local field potentials (LFP) obtained from laminar recordings can be used to predict the contributions of distinct populations of neurons to the EEG signals. The primary research goal of this proposal is to determine the cortical mechanisms in DMFC that give rise to the ERN and elucidate the contribution of ACC to its EEG signatures. The primary training goal is to master the literature on performance monitoring and medial frontal lobe and gain expertise in cutting-edge computational neuroscience methods. In Aim 1, I will elucidate the neuronal generators of the ERN in DMFC employing an extended version of the generalized laminar population analysis (gLPAextended ). In contrast to the original method, I will incorporate the distribution of cells obtained from laminar recordings and anatomical studies in macaque monkeys, the connectivity of a microcircuit model for agranular frontal cortex, and the contribution of nonlinear dendritic mechanisms present on neocortical pyramidal cells. In Aim 2, I will predict the EEG evoked by the activity of cortical current dipoles in DMFC, obtained in Aim 1, employing EEG forward modeling. Then, I will estimate the neuronal sources in ACC that give rise to the ERN by combining inverse methods and nonlinear filtering techniques28 after subtracting the DMFC-related EEG from the recorded EEG signals. Using these ACC current dipoles estimates and gLPAextended predictions for the ERN, I will assess the contribution of pyramidal cells in ACC to the ERN. The outcomes of this proposal will provide circuit-level insights into brain disorders by translating changes in the ERN into changes in microcircuit processing. The combined mentorship of my sponsors, Dr. Riera and Dr. Schall, will guarantee the fulfillment of the research and training goals of this proposal.