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

性能监测的皮层微电路：桥接非人类灵长类动物的多尺度神经元活动和电生理特征

• 批准号: 10538046
• 负责人: Beatriz Herrera
• 金额: $ 3.36万
• 依托单位: FLORIDA INTERNATIONAL UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-08-15 至 2024-08-14
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10538046
• 关键词: Affect; Anatomy; Anterior; Anxiety; Area; Attention deficit hyperactivity disorder; Biological Markers; Biophysics; Brain; Brain Diseases; Cells; Communication; Conflict (Psychology); Data Set; Diagnostic; Electroencephalography; Electrophysiology (science); Event-Related Potentials; Goals; Knowledge; Learning; Literature; Macaca; Measures; Medial; Mental disorders; Mentors; Mentorship; Methods; Microscopic; Modeling; Monitor; Monkeys; Neurons; Outcome; Performance; Population; Population Analysis; Positioning Attribute; Postdoctoral Fellow; Psychiatric therapeutic procedure; Pyramidal Cells; Reporting; Research; Research Domain Criteria; Research Personnel; Research Proposals; Research Training; Scalp structure; Schizophrenia; Scientist; Signal Transduction; Source; Techniques; Training; Translating; Writing; biophysical analysis; biophysical model; brain machine interface; cingulate cortex; clinical translation; cognitive control; cognitive neuroscience; cognitive performance; computational neuroscience; executive function; experience; frontal lobe; improved; indexing; insight; large datasets; neocortical; nervous system disorder; neurophysiology; nonhuman primate; novel; response; skills; theories

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.

项目概要 错误相关消极性（ERN）是 RDoC 的基本衡量标准，因为它索引了执行的核心功能 控制。自发现以来，研究表明 ERN 是精神疾病的生物标志物，例如 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 了解它是如何在细胞和电路层面产生的。不同的研究报告了 ERN 由内侧额叶区域产生，包括前扣带皮层 (ACC) 和背内侧额叶皮层 （DMFC）。然而，发出错误和冲突信号的皮质机制仍然难以捉摸。因此，要移动 研究和临床转化的进展，必须克服两个关键障碍：a）需要机械 理解错误/冲突信号中的皮质电路，以及 b) 建立理论模型 将微电路信号转化为头皮电位的框架。在这个提案中，我将克服这些障碍 通过实施一种新颖的方法，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，并采用 EEG 正向建模来转化它们的贡献 转化为微观信号。我假设尖峰活动和局部场电位（LFP）从 层流记录可用于预测不同神经元群体对脑电图信号的贡献。 本提案的主要研究目标是确定 DMFC 中产生 ERN 并阐明 ACC 对其脑电图签名的贡献。主要训练目标是掌握 有关表现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，我将使用 DMFC 来阐明 ERN 的神经元生成器 广义层流总体分析的扩展版本 (gLPAextended )。与原来的方法相比， 我将结合从层流记录和解剖学研究中获得的猕猴细胞分布 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，我将预测由 DMFC 中皮质电流偶极子的活动，在目标 1 中使用 EEG 正向建模获得。那么，我将 通过结合逆向方法和非线性来估计 ACC 中产生 ERN 的神经元源 从记录的 EEG 信号中减去 DMFC 相关的 EEG 后采用过滤技术28。使用这些 ACC 当前偶极子估计和 gLPA 对 ERN 的扩展预测，我将评估金字塔的贡献 ACC 中的单元格到 ERN。该提案的结果将通过以下方式提供对脑部疾病的电路级见解： 将 ERN 的变化转化为微电路处理的变化。我的综合指导 赞助商 Riera 博士和 Schall 博士将保证本次研究和培训目标的实现 提议。