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RDoC的一项基本测量，因为它标示了执行的核心功能 控制力。自从它被发现以来，研究表明ERN是精神疾病的生物标记物，例如 多动症、强迫症、精神分裂症和焦虑。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上产生的。不同的研究报告了ERN到 由额叶内侧区域产生，包括前扣带回皮质和背内侧额叶皮质 (DMFC)。然而，发出错误和冲突信号的大脑皮层机制仍然难以捉摸。因此，要搬家 为了推进研究和临床翻译，必须克服两个关键障碍：a)需要一种机械性的 理解大脑皮层回路中的错误/冲突信号，以及b)建立理论 将微电路信号转换为头皮电位的框架。在这项提议中，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，以推断 不同神经元对ERN的贡献及其脑电正向模拟 变成了微观信号。我假设尖峰活动和局域场势(LFP)从 层流记录可以用来预测不同神经元群体对脑电信号的贡献。 这项建议的主要研究目标是确定DMFC中引起 并阐明了ACC对其脑电特征的贡献。培训的主要目标是掌握 有关性能监控和内侧额叶的文献，并获得尖端计算方面的专业知识 神经科学的方法。在目标1，我将阐明DMFC中ERN的神经元发生器 广义层流布居分析的扩展版本(gLPA扩展)。与原来的方法不同， 我将结合从猕猴的层流记录和解剖学研究中获得的细胞分布 猴子，无颗粒额叶皮质微电路模型的连通性，以及非线性的贡献 新皮质锥体细胞上存在树突状机制。在目标2中，我将预测由 DMFC中皮层电流偶极子的活动，在目标1中使用脑电正向模拟获得。那么，我会 用逆方法和非线性相结合的方法估计引起ERN的ACC内神经元来源 从记录的EEG信号减去DMFC相关的EEG之后的滤波技术28。使用这些访问 目前偶极子的估计和gLPA对ERN的扩展预测，我将评估锥体的贡献 Acc中的细胞连接到ERN。这项提议的结果将通过以下方式提供对大脑紊乱的电路层面的洞察 将ERN中的变化转换为微电路处理中的变化。我的联合导师 赞助商Riera博士和Schall博士将保证实现该项目的研究和培训目标 求婚。

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.