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首页> 外文期刊>Computer Methods and Programs in Biomedicine: An International Journal Devoted to the Development, Implementation and Exchange of Computing Methodology and Software Systems in Biomedical Research and Medical Practice >Determination of ECoG information flow activity based on Granger causality and Hilbert transformation
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Determination of ECoG information flow activity based on Granger causality and Hilbert transformation

机译：基于格兰杰因果关系和希尔伯特变换的ECoG信息流活动确定

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摘要

Analysis of directional information flow patterns among different regions of the brain is important for investigating the relation between ECoG (electrocorticographic) and mental activity. The objective is to study and evaluate the information flow activity at different frequencies in the primary motor cortex. We employed Granger causality for capturing the future state of the propagation path and direction between recording electrode sites on the cerebral cortex. A grid covered the right motor cortex completely due to its size (approx. 8 cm × 8 cm) but grid area extends to the surrounding cortex areas. During the experiment, a subject was asked to imagine performing two activities: movement of the left small finger and/or movement of the tongue. The time series of the electrical brain activity was recorded during these trials using an 8. × 8 (0.016-300 Hz band with) ECoG platinum electrode grid, which was placed on the contralateral (right) motor cortex. For detection of information flow activity and communication frequencies among the electrodes, we have proposed a method based on following steps: (i) calculation of analytical time series such as amplitude and phase difference acquired from Hilbert transformation, (ii) selection of frequency having highest interdependence for the electrode pairs for the concerned time series over a sliding window in which we assumed time series were stationary, (iii) calculation of Granger causality values for each pair with selected frequency. The information flow (causal influence) activity and communication frequencies between the electrodes in grid were determined and shown successfully. It is supposed that information flow activity and communication frequencies between the electrodes in the grid are approximately the same for the same pattern. The successful employment of Granger causality and Hilbert transformation for the detection of the propagation path and direction of each component of ECoG among different sub-cortex areas were capable of determining the information flow (causal influence) activity and communication frequencies between the populations of neurons successfully.
机译：分析大脑不同区域之间的方向性信息流模式对于研究ECoG（脑电图）与心理活动之间的关系非常重要。目的是研究和评估初级运动皮层中不同频率的信息流活动。我们采用格兰杰因果关系来捕获大脑皮层上记录电极部位之间的传播路径和方向的未来状态。网格由于其尺寸（大约8 cm×8 cm）而完全覆盖了右运动皮层，但是网格区域扩展到了周围的皮层区域。在实验过程中，要求受试者想象进行两项活动：左小指的运动和/或舌头的运动。在这些试验中，使用8××（0.016-300 Hz带）ECoG铂电极网格记录了脑电活动的时间序列，该电极网格置于对侧（右侧）运动皮层上。为了检测电极之间的信息流动活动和通信频率，我们提出了一种基于以下步骤的方法：（i）计算分析时间序列，例如从希尔伯特变换获取的幅度和相位差，（ii）选择频率最高的在假设时间序列固定的滑动窗口中，相关时间序列的电极对之间的相互依赖性，（iii）计算选定频率下每对电极的格兰杰因果关系值。确定并成功显示了网格中电极之间的信息流（因果影响）活动和通信频率。假设对于同一图案，信息流活动和网格中电极之间的通信频率大致相同。成功地利用Granger因果关系和希尔伯特变换来检测ECoG的每个成分在不同皮层下区域之间的传播路径和方向，能够成功确定神经元群体之间的信息流（因果关系）活动和通信频率。

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