Probabilistic maps of spiking and connectivity in human and mouse cortex

人类和小鼠皮层尖峰和连接的概率图

• 批准号: RGPIN-2015-05936
• 负责人: Valiante, Taufik
• 金额: $ 2.48万
• 依托单位: University of Toronto
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2019
• 资助国家: 加拿大
• 起止时间: 2019-01-01 至 2020-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=685335
• 关键词: Probabilistic; maps; spiking; connectivity; human

Animal experiments although providing guiding principles, will always be but a model of the human brain. We propose novel in vitro and in vivo electrophysiological experiments and computational techniques to characterize human cortical neurons, describe how information flows within and between cortical layers, and how this flow of information is modulated by theta oscillations - the most ubiquitous oscillation in the human brain. We start with our critical observation that in human cortical tissue, theta oscillations coordinate activity between superficial and deep cortical layers. To determine the cellular characteristics that generate these synchronous theta oscillations whole-cell recordings will be performed in human excitatory and inhibitory neurons. We will focus on spike and spiking characteristics of these cells and how they are modulated by acetylcholine - a neurotransmitter involved in attention, and required for theta oscillations in human cortical slices. To perform large scale cellular and circuit characterizations we will use high throughput electrophysiological recordings using microelectrode arrays (MEA) to classify cellular spike\spiking characteristics into different spiking phenotypes. By pooling data across patients we will develop the first ever layer specific probabilistic maps of spiking phenotypes for the human brain. To estimate connectivity between the different phenotypes, spike time series will be used to compute information transfer (transfer entropy). To determine how such connectivity maps can be modulated, neurotransmitter agonists will be applied. To validate this technique, parallel experiments will be carried out in mouse cortex, for which some connectivity data exists. To characterize the causal role theta oscillations play in reorganizing connectivity maps, transgenic mice will be used to drive cortical oscillations using optogenetics. A long term goal is to use these computational techniques to create connectivity maps from human in vivo experiments using acute laminar (MEAs across cortical laminae) recordings. The tools developed here will advance the field of recording and interpreting inter-cortical and intra-cortical communication in the human brain. Understanding human cortical circuits in this way will contribute meaningfully to neuromodulatory strategies to treat diseases of the brain, particularly those mediated by theta oscillations. Ongoing fruitful collaborations between the Toronto Western Hospital, the Toronto Western Hospital Research Institute, Institute of Biomaterials and Biomedical Engineering, Psychology, Computer Science, and Computational neuroscience will be further strengthened by funding this research program, and will provide a rich environment to train high quality personnel who will see in action the strength of collaborative neuroscience in the pursuit of probing the human brain. **

动物实验虽然提供了指导原则，但永远只是人脑的模型。 我们提出了新颖的体外和体内电生理学实验和计算技术来表征人类皮质神经元，描述信息如何在皮质层内部和之间流动，以及这种信息流如何通过θ振荡（人脑中最普遍的振荡）进行调节。我们从我们的批判性观察开始，在人类皮质组织中，θ 振荡协调浅层和深层皮质层之间的活动。 为了确定产生这些同步 theta 振荡的细胞特征，将对人类兴奋性和抑制性神经元进行全细胞记录。 我们将重点关注这些细胞的尖峰和尖峰特征，以及它们如何被乙酰胆碱调节，乙酰胆碱是一种与注意力有关的神经递质，是人类皮质切片中θ振荡所必需的。为了进行大规模细胞和电路表征，我们将使用微电极阵列 (MEA) 进行高通量电生理记录，将细胞尖峰/尖峰特征分类为不同的尖峰表型。通过汇集患者的数据，我们将开发出首个人类大脑尖峰表型的特定层概率图。为了估计不同表型之间的连通性，将使用尖峰时间序列来计算信息传递（传递熵）。 为了确定如何调节此类连接图，将应用神经递质激动剂。 为了验证这项技术，将在小鼠皮层中进行并行实验，其中存在一些连接数据。 为了表征θ振荡在重组连通性图谱中所起的因果作用，转基因小鼠将被用于利用光遗传学驱动皮质振荡。长期目标是利用这些计算技术，利用急性层流（跨皮质层的 MEA）记录来创建人体体内实验的连接图。 这里开发的工具将推动记录和解释人脑皮质间和皮质内通信的领域。 以这种方式了解人类皮质回路将对治疗大脑疾病的神经调节策略做出有意义的贡献，特别是那些由 θ 振荡介导的疾病。通过资助该研究项目，多伦多西部医院、多伦多西部医院研究所、生物材料和生物医学工程研究所、心理学、计算机科学和计算神经科学之间正在进行的富有成效的合作将得到进一步加强，并将提供一个丰富的环境来培养高素质人才，他们将在探索人脑的过程中看到协作神经科学的力量。 **