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Quantifying connectivity in a physiology based model using adaptive dynamic causal modelling

机译:基于生理动态因果因果模拟的基于生理学模型中的定量连通性

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This paper proposes an Adaptive Dynamic Causal Modelling based approach to detect and quantify effective connectivity in human brain structures injured by epileptic activities. The identification of the parameters in the physiology based model subtended the Electroencephalographic observations is performed by improving the optimization step in the Expectation Maximization algorithm. Considering unidirectional flow propagation, we show the efficiency of our proposed approach compared to the conventional technique.
机译:本文提出了一种基于自适应动态因果建模的基于自适应性因果建模,以检测和量化癫痫作用损伤的人脑结构有效连通性。通过提高期望最大化算法中的优化步骤,对生理基于模型中的参数的识别子化脑电图观察。考虑到单向流动传播,与传统技术相比,我们展示了我们所提出的方法的效率。

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