Multiscale Investigation of Neural Circuitry of Visual Cognition in Primates

灵长类动物视觉认知神经回路的多尺度研究

• 批准号: RGPIN-2022-04592
• 负责人: Schall, Jeffrey
• 金额: $ 4.01万
• 依托单位: York University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=745877
• 关键词: Multiscale; Investigation; Neural; Circuitry; Visual

How the brain guides attention and monitors errors to govern behavior has been investigated in humans with noninvasive measures of brain function like the electro-encephalogram (EEG) and in monkeys with invasive measurements of brain cell (neuron) discharges and synaptic local field potentials. We know that the EEG is produced by the brain. But, using the EEG on the head to locate sources in the brain (known as the inverse problem) allows multiple solutions. But deriving the EEG from particular sources in the brain (known as the forward problem) has one solution. This research program seeks the brain mechanisms of human attention and monitoring by building a bridge between human EEG findings and monkey brain function. Our research has verified that monkeys have EEG measures like humans. We have obtained a comprehensive and unique dataset consisting of simultaneous measurements of EEG with discharges and field potentials from four areas of the cerebral cortex of macaque monkeys performing tasks demanding visual attention and error monitoring. Two areas consist of the typical 6 cortical layers. Two lack the dense layer 4. Funds are requested to characterize the diversity of signals found across cortical layers in each of the 4 areas and then to determine how these brain signals produce the EEG signals. High confidence in feasibility is engendered by our application of advanced biophysical theory, sophisticated mathematical approaches, and tractable models of single neurons applied to a dataset that is unique in behavioral relevance, diversity of brain regions, and relevance for understanding human processes. Understanding how brain circuits produce EEG measures will solve a long-standing problem, establish an empirical bridge between two research domains, and improve brain-machine interface technology. Understanding how the brain guides attention and monitors errors will resolve competing theories of human perception and performance and translate into more effective machine vision and robotic systems.

大脑如何引导注意力和监控错误来管理行为，已经在人类中进行了研究，使用非侵入性的脑功能测量，如脑电图（EEG），以及在猴子中进行脑细胞（神经元）放电和突触局部场电位的侵入性测量。我们知道脑电图是由大脑产生的。但是，使用头部的EEG来定位大脑中的源（称为逆问题）允许多种解决方案。但从大脑中的特定来源推导出EEG（称为正向问题）有一个解决方案。该研究计划通过在人类EEG发现和猴子大脑功能之间建立桥梁，寻求人类注意力和监控的大脑机制。我们的研究已经证实，猴子有像人类一样的脑电图测量。我们已经获得了一个全面的和独特的数据集，包括同步测量的EEG放电和场电位从四个地区的猕猴大脑皮层执行任务，要求视觉注意力和错误监测。两个区域由典型的6个皮质层组成。两个缺少致密层4。需要资金来表征在4个区域中的每一个中的皮层层中发现的信号的多样性，然后确定这些大脑信号如何产生EEG信号。我们将先进的生物物理理论、复杂的数学方法和易于处理的单个神经元模型应用于行为相关性、大脑区域多样性和理解人类过程的相关性方面独特的数据集，从而产生了对可行性的高度信心。了解脑回路如何产生EEG测量将解决一个长期存在的问题，建立两个研究领域之间的经验桥梁，并改善脑机接口技术。了解大脑如何引导注意力和监控错误将解决人类感知和性能的竞争理论，并转化为更有效的机器视觉和机器人系统。