Detecting a dipole source by MEG/EEG and generalized likelihood ratio tests

Aleksandar Dogandzic; Arye Nehorai

Detecting a dipole source by MEG/EEG and generalized likelihood ratio tests

Aleksandar Dogandzic, Arye Nehorai

Research output: Contribution to journal › Conference article › peer-review

Abstract

We consider detection of a current dipole source in the head by magnetoencephalography (MEG) and electroencephalography (EEG) using the fundamental statistical techniques of generalized likelihood ratio (GLR) tests. The distributions of the GLR, under the null hypothesis H₀ and the alternative H₁, are estimated in order to find the probabilities of false alarm P_fa and detection P_d under a variety of conditions. We also derive a modified version of the GLR test that enables analytical computation of P_fa and P_d when the dipole's position is unknown. The results may be applied to compare the detection performance of different MEG/EEG systems and to optimize array design.

Original language	English
Pages (from-to)	1196-1200
Number of pages	5
Journal	Conference Record of the Asilomar Conference on Signals, Systems and Computers
Volume	2
State	Published - 1997
Event	Proceedings of the 1996 30th Asilomar Conference on Signals, Systems & Computers. Part 2 (of 2) - Pacific Grove, CA, USA Duration: Nov 3 1996 → Nov 6 1996

Cite this

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abstract = "We consider detection of a current dipole source in the head by magnetoencephalography (MEG) and electroencephalography (EEG) using the fundamental statistical techniques of generalized likelihood ratio (GLR) tests. The distributions of the GLR, under the null hypothesis H0 and the alternative H1, are estimated in order to find the probabilities of false alarm Pfa and detection Pd under a variety of conditions. We also derive a modified version of the GLR test that enables analytical computation of Pfa and Pd when the dipole's position is unknown. The results may be applied to compare the detection performance of different MEG/EEG systems and to optimize array design.",

author = "Aleksandar Dogandzic and Arye Nehorai",

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T1 - Detecting a dipole source by MEG/EEG and generalized likelihood ratio tests

AU - Dogandzic, Aleksandar

AU - Nehorai, Arye

PY - 1997

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N2 - We consider detection of a current dipole source in the head by magnetoencephalography (MEG) and electroencephalography (EEG) using the fundamental statistical techniques of generalized likelihood ratio (GLR) tests. The distributions of the GLR, under the null hypothesis H0 and the alternative H1, are estimated in order to find the probabilities of false alarm Pfa and detection Pd under a variety of conditions. We also derive a modified version of the GLR test that enables analytical computation of Pfa and Pd when the dipole's position is unknown. The results may be applied to compare the detection performance of different MEG/EEG systems and to optimize array design.

AB - We consider detection of a current dipole source in the head by magnetoencephalography (MEG) and electroencephalography (EEG) using the fundamental statistical techniques of generalized likelihood ratio (GLR) tests. The distributions of the GLR, under the null hypothesis H0 and the alternative H1, are estimated in order to find the probabilities of false alarm Pfa and detection Pd under a variety of conditions. We also derive a modified version of the GLR test that enables analytical computation of Pfa and Pd when the dipole's position is unknown. The results may be applied to compare the detection performance of different MEG/EEG systems and to optimize array design.

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M3 - Conference article

AN - SCOPUS:0030647525

SN - 1058-6393

VL - 2

SP - 1196

EP - 1200

JO - Conference Record of the Asilomar Conference on Signals, Systems and Computers

JF - Conference Record of the Asilomar Conference on Signals, Systems and Computers

T2 - Proceedings of the 1996 30th Asilomar Conference on Signals, Systems & Computers. Part 2 (of 2)

Y2 - 3 November 1996 through 6 November 1996

ER -

Detecting a dipole source by MEG/EEG and generalized likelihood ratio tests

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