Spatiotemporal models of brain electrophysiology

脑电生理学的时空模型

• 批准号: EP/G053944/1
• 负责人: Karl Friston
• 金额: $ 11.6万
• 依托单位: University College London
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2009
• 资助国家: 英国
• 起止时间: 2009 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FG053944%2F1
• 关键词: Spatiotemporal; models; brain; electrophysiology

Modern two-dimensional (2D) multi-electrode arrays allow for the simultaneous recording of extracellular activity from a large number of neurons and have been used to collect data among others from the visual cortex, the motor cortex for prosthetics, along with one dimensional (1D) silicon probes etc. Most of this work uses arrays to extract the action potentials of single neurons by focusing on the relevant spike rates. Thus, many data-features are effectively wasted.The goals of this project are (i) to use advanced mathematical methods to extract new information from 2D multi-electrode arrays (and sources reconstructed EEG data) and (ii) to develop novel neural mass models which model spatially extended neural activity. At present, the determination of the distribution of current sources and sinks is carried out using the so-called Current Source-Density (CSD) method. This method does not provide any detailed spatial characterisation of the relevant sources. The first aim of this project is to develop new methods for the estimation of the current source density from local field potentials, which will take into detailed consideration the spatial distribution of the current sources and sinks. At a larger spatial scale, current neural mass models, although quite successful, do not consider the spatial distribution of current sources and sinks in the neural tissue. The second aim of this project is to construct generalised dynamic causal models of LFP and EEG data by modelling current fluxes as continuous processes on the cortical sheet using partial differential equations (PDE). Furthermore, we will evaluate the improvement in these models, over their ODE homologues, using their model evidence (for different sorts of empirical data). Such an endeavour will have important implications regarding the estimation of spatial parameters that govern cortical activity, such as the spatial extent of intrinsic connections in the brain.

现代二维（2D）多电极阵列允许同时记录大量神经元的细胞外活动，并已被用来收集数据，其中包括从视觉皮层，运动皮层的假肢，沿着与一维（1D）硅探针等。这项工作的大部分使用阵列提取单个神经元的动作电位，通过专注于相关的尖峰率。本项目的目标是（i）使用先进的数学方法从2D多电极阵列（和源重建EEG数据）中提取新的信息;（ii）开发新的神经块模型，该模型模拟空间扩展的神经活动。目前，使用所谓的电流源密度（CSD）方法来确定电流源和电流汇的分布。这种方法不提供任何详细的空间特性的相关来源。该项目的第一个目标是开发新的方法，用于从局部场电位估计电流源密度，该方法将详细考虑电流源和电流汇的空间分布。在更大的空间尺度上，目前的神经质量模型，虽然相当成功，不考虑在神经组织中的电流源和汇的空间分布。该项目的第二个目的是构建广义动态因果模型的LFP和EEG数据的模拟电流通量作为连续的过程中使用偏微分方程（PDE）的皮质片。此外，我们将评估这些模型的改进，在他们的ODE同系物，使用他们的模型证据（不同种类的经验数据）。这样的努力将有重要的影响，关于空间参数的估计，支配皮层活动，如在大脑中的内在连接的空间范围。