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首页> 外文会议>Engineering in Medicine and Biology Society, 2003. Proceedings of the 25th Annual International Conference of the IEEE >Simultaneous extraction and localization of dipolar independent components in evoked potentials
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Simultaneous extraction and localization of dipolar independent components in evoked potentials

机译：诱发电位中偶极独立成分的同时提取和定位

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摘要

EEG stimulus-related responses have been extensively studied to gain insight on the functional behavior of the brain. Traditionally, these responses have been considered as the result of the generation of low-amplitude evoked potentials (EP). When averaged, these low-amplitude potentials come up from the background and can be cleanly observed. Independent component analysis (ICA) is a technique widely used to solve the problem of blind source separation (BSS). When applied to EP, ICA provides a method to obtain activation signals of neural structures responsible for the generation of several components of EP. ICA algorithms may be modified in order to impose some constraints on the independent components (IC) to be extracted or the mixing matrix, resulting in the so-called constrained ICA (cICA). Here, we make use of a cICA approach to get those IC of the EP that can be identified with point-dipolar sources, as well as their position.
机译：脑电刺激相关的反应已被广泛研究，以获取对大脑的功能行为的见解。传统上，这些响应被认为是低振幅诱发电位（EP）产生的结果。平均后，这些低振幅电势会从背景中浮出，并且可以清晰地观察到。独立成分分析（ICA）是一种广泛用于解决盲源分离（BSS）问题的技术。当应用于EP时，ICA提供了一种获得神经结构激活信号的方法，该信号负责生成EP的几种成分。可以修改ICA算法，以便对要提取的独立成分（IC）或混合矩阵施加一些约束，从而导致所谓的受约束ICA（cICA）。在这里，我们利用cICA方法获得可以用点偶极子源及其位置识别的EP的IC。

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