Localizing Synchronized Dipole Sources Using a Modified RAP-MUSIC Algorithm

Conference Proceedings. 2nd International IEEE EMBS Conference on Neural Engineering, 2005. Pub Date : 2005-03-16 DOI:10.1109/CNE.2005.1419571

P. Schimpf, Hesheng Liu

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引用次数: 1

Abstract

Synchronization across different brain regions is suggested to be a possible mechanism for functional integration. Analyzing the synchronization of cortical activity is possible if the source activity can be estimated by solving the inverse problem. RAP-MUSIC and R-MUSIC are well-known inverse algorithms that employ an independent topography (IT) source model which allows for synchronous sources. However, these two algorithms have difficulty distinguishing highly correlated sources because of their dependence on a correlation threshold. In this paper we modify RAP-MUSIC to a multi-stage process which analyzes the correlation of candidate sources and searches ITs among pre-correlated groups. This algorithm is not dependent on a subspace correlation threshold to identify synchronous sources and also avoids an exhaustive multidimensional search for such sources among numerous possible combinations. A comparative study was carried out on simulated data, and the results demonstrate superior performance with the modified algorithm compared to the original RAP-MUSIC in recovering synchronous sources. The modified algorithm thus has potential in the study of brain synchronization

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基于改进RAP-MUSIC算法的同步偶极子源定位

不同脑区的同步被认为是功能整合的可能机制。如果可以通过求解逆问题来估计源活动，那么分析皮质活动的同步性是可能的。RAP-MUSIC和R-MUSIC是众所周知的反向算法，它们采用允许同步源的独立地形(IT)源模型。然而，这两种算法难以区分高度相关的源，因为它们依赖于一个相关阈值。本文将RAP-MUSIC改进为一个多阶段的过程，分析候选源的相关性，并在预相关组中搜索ITs。该算法不依赖于子空间相关阈值来识别同步源，也避免了在众多可能的组合中对同步源进行详尽的多维搜索。仿真数据对比研究表明，改进后的算法在同步源恢复方面优于原有的RAP-MUSIC算法。因此，改进后的算法在大脑同步的研究中具有潜力

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Conference Proceedings. 2nd International IEEE EMBS Conference on Neural Engineering, 2005.

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