The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
Copyrights notice
The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
우리는 두피 뇌전도(EEG)로부터 피질 쌍극자 이미징에 적합한 공간 역필터를 조사했습니다. 신호 및 잡음의 통계 정보를 역과정에 통합하는 효과를 컴퓨터 시뮬레이션과 실험 연구를 통해 조사했습니다. 파라메트릭 투영 필터(PPF)와 파라메트릭 위너 필터(PWF)는 비균질 3구 체적 도체 헤드 모델에 적용되었습니다. 잡음 공분산 행렬은 두피 전위에 독립 성분 분석(ICA)을 적용하여 추정되었습니다. 본 시뮬레이션 결과는 ICA를 이용하여 EEG와 분리된 신호 사이의 미분 잡음으로부터 잡음 공분산을 추정하고, 분리된 신호로부터 신호 공분산을 추정하였을 때 PPF와 PWF가 우수한 성능을 제공함을 시사한다. 또한, 영상 촬영 순간의 차동 잡음을 포함시키고 신호 대 잡음비에 따라 잡음 샘플링 기간을 조정함으로써 잡음의 영향을 억제하면서 피질 쌍극자 영상의 공간 분해능을 향상시켰다. 우리는 제안된 영상 기법을 시각유발전위의 인간 실험 데이터에 적용하여 생리학적 지식과 일치하는 합리적인 결과를 얻었습니다.
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Junichi HORI, Kentarou SUNAGA, Satoru WATANABE, "Signal and Noise Covariance Estimation Based on ICA for High-Resolution Cortical Dipole Imaging" in IEICE TRANSACTIONS on Information,
vol. E93-D, no. 9, pp. 2626-2634, September 2010, doi: 10.1587/transinf.E93.D.2626.
Abstract: We investigated suitable spatial inverse filters for cortical dipole imaging from the scalp electroencephalogram (EEG). The effects of incorporating statistical information of signal and noise into inverse procedures were examined by computer simulations and experimental studies. The parametric projection filter (PPF) and parametric Wiener filter (PWF) were applied to an inhomogeneous three-sphere volume conductor head model. The noise covariance matrix was estimated by applying independent component analysis (ICA) to scalp potentials. The present simulation results suggest that the PPF and the PWF provided excellent performance when the noise covariance was estimated from the differential noise between EEG and the separated signal using ICA and the signal covariance was estimated from the separated signal. Moreover, the spatial resolution of the cortical dipole imaging was improved while the influence of noise was suppressed by including the differential noise at the instant of the imaging and by adjusting the duration of noise sample according to the signal to noise ratio. We applied the proposed imaging technique to human experimental data of visual evoked potential and obtained reasonable results that coincide to physiological knowledge.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.E93.D.2626/_p
부
@ARTICLE{e93-d_9_2626,
author={Junichi HORI, Kentarou SUNAGA, Satoru WATANABE, },
journal={IEICE TRANSACTIONS on Information},
title={Signal and Noise Covariance Estimation Based on ICA for High-Resolution Cortical Dipole Imaging},
year={2010},
volume={E93-D},
number={9},
pages={2626-2634},
abstract={We investigated suitable spatial inverse filters for cortical dipole imaging from the scalp electroencephalogram (EEG). The effects of incorporating statistical information of signal and noise into inverse procedures were examined by computer simulations and experimental studies. The parametric projection filter (PPF) and parametric Wiener filter (PWF) were applied to an inhomogeneous three-sphere volume conductor head model. The noise covariance matrix was estimated by applying independent component analysis (ICA) to scalp potentials. The present simulation results suggest that the PPF and the PWF provided excellent performance when the noise covariance was estimated from the differential noise between EEG and the separated signal using ICA and the signal covariance was estimated from the separated signal. Moreover, the spatial resolution of the cortical dipole imaging was improved while the influence of noise was suppressed by including the differential noise at the instant of the imaging and by adjusting the duration of noise sample according to the signal to noise ratio. We applied the proposed imaging technique to human experimental data of visual evoked potential and obtained reasonable results that coincide to physiological knowledge.},
keywords={},
doi={10.1587/transinf.E93.D.2626},
ISSN={1745-1361},
month={September},}
부
TY - JOUR
TI - Signal and Noise Covariance Estimation Based on ICA for High-Resolution Cortical Dipole Imaging
T2 - IEICE TRANSACTIONS on Information
SP - 2626
EP - 2634
AU - Junichi HORI
AU - Kentarou SUNAGA
AU - Satoru WATANABE
PY - 2010
DO - 10.1587/transinf.E93.D.2626
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E93-D
IS - 9
JA - IEICE TRANSACTIONS on Information
Y1 - September 2010
AB - We investigated suitable spatial inverse filters for cortical dipole imaging from the scalp electroencephalogram (EEG). The effects of incorporating statistical information of signal and noise into inverse procedures were examined by computer simulations and experimental studies. The parametric projection filter (PPF) and parametric Wiener filter (PWF) were applied to an inhomogeneous three-sphere volume conductor head model. The noise covariance matrix was estimated by applying independent component analysis (ICA) to scalp potentials. The present simulation results suggest that the PPF and the PWF provided excellent performance when the noise covariance was estimated from the differential noise between EEG and the separated signal using ICA and the signal covariance was estimated from the separated signal. Moreover, the spatial resolution of the cortical dipole imaging was improved while the influence of noise was suppressed by including the differential noise at the instant of the imaging and by adjusting the duration of noise sample according to the signal to noise ratio. We applied the proposed imaging technique to human experimental data of visual evoked potential and obtained reasonable results that coincide to physiological knowledge.
ER -