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.

现代的二维（2D）多电极阵列允许同时记录来自大量神经元的细胞外活性，并且已用于从视觉皮层中收集数据，Prothetics的运动皮层，以及这些工作的大部分硅均通过对动作的群体进行分散的速度来提取单个NEURONS的大部分型号。因此，有效地浪费了许多数据功能。该项目的目标是（i）使用高级数学方法从2D多电极阵列中提取新信息（以及源重建的EEG数据）和（ii）开发新的神经质量模型，以模拟空间扩展神经活动。目前，使用所谓的电流源密度（CSD）方法来确定电流源和水槽的分布。此方法不提供相关来源的任何详细的空间表征。该项目的第一个目的是开发新的方法来估计本地场电位的当前源密度，这将详细考虑当前源和下沉的空间分布。在较大的空间尺度上，当前的神经质量模型虽然非常成功，但并未考虑神经组织中电流和下沉的空间分布。该项目的第二个目的是通过使用部分微分方程（PDE）将电流通量作为在皮质表上的连续过程进行建模，以构建LFP和EEG数据的广义动态因果模型。此外，我们将使用其模型证据（对于不同的经验数据）来评估这些模型，ODE同源物的改进。这样的努力将对控制皮质活性的空间参数的估计（例如大脑内固有连接的空间范围）具有重要意义。