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Application of EEG Source Localization Algorithms to the Monitoring of Active Pathways in Peripheral Nerves

机译:EEG源定位算法在外围神经中监测活性途径的应用

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Improved techniques for identifying active pathways in peripheral nerves using extraneural measurements would have numerous applications in the fields of neuroprostheses, neural system engineering, and diagnostics. In this study, we propose to approach this issue as an inverse problem of bioelectric source localization, using measurements from a multi-contact nerve cuff electrode. This problem is a modified version of the electroencephalogram/magneto-encephalogram (EEG/MEG) source localization problem. We therefore evaluate the performance of two well-known EEG/MEG source localization algorithms, namely sLORETA and sFOCUSS, when they are applied to the peripheral nerve problem. sLORETA is found to be a potentially viable approach, albeit with limited resolution, while sFOCUSS is found to produce too many spurious pathways in the presence of noise.
机译:使用外耳测量的外周神经中鉴定活性途径的改进技术将在神经调节,神经系统,神经系统工程和诊断领域具有许多应用。在这项研究中,我们建议使用来自多触点神经箍电极的测量来接近生物电源定位的逆问题。此问题是脑电图/磁脑(EEG / MEG)源定位问题的修改版本。因此,当它们应用于外周神经问题时,我们评估了两个公知的EEG / MEG源定位算法,即斜面和SFOCUSS的性能。 SloreTa被发现是一种潜在可行的方法,尽管分辨率有限,但发现SFOCUSS在存在噪音的情况下产生太多的杂散途径。

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