Computer Engineering Department, Istanbul Kultur University, Atakoy Campus, Bakirkoy, 34156 Istanbul, Turkey.
Comput Methods Programs Biomed. 2013 Dec;112(3):481-9. doi: 10.1016/j.cmpb.2013.08.011. Epub 2013 Sep 1.
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.
分析大脑不同区域之间的定向信息流模式对于研究脑电（脑皮层电图）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在不同频率下的信息流活动。我们采用格兰杰因果关系来捕捉大脑皮层记录电极之间传播路径和方向的未来状态。由于其大小（约 8cm×8cm），一个网格完全覆盖了右侧运动皮层，但网格区域延伸到周围的皮层区域。在实验过程中，要求受试者想象执行两个动作：左手小手指的运动和/或舌头的运动。在这些试验中，使用一个 8×8（0.016-300Hz 频段）的 ECoG 铂金电极网格记录大脑活动的电时间序列，该网格放置在对侧（右侧）运动皮层上。为了检测电极之间的信息流活动和通信频率，我们提出了一种基于以下步骤的方法：（i）计算来自希尔伯特变换的分析时间序列，如幅度和相位差，（ii）选择对所关注时间序列在滑动窗口中具有最高互相关的频率，在该窗口中我们假设时间序列是静止的，（iii）计算所选频率下每个电极对的格兰杰因果值。成功确定和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。假设网格中电极之间的信息流活动和通信频率对于相同的模式大致相同。格兰杰因果关系和希尔伯特变换的成功应用可用于检测 ECoG 不同子皮层区域之间每个成分的传播路径和方向，从而成功确定神经元群体之间的信息流（因果影响）活动和通信频率。
