Visualization of the Brain Activity during Mental Rotation Processing Using MUSIC-Weighted Lead-Field Synthetic Filtering

Sunao IWAKI; Mitsuo TONOIKE; Shoogo UENO

Visualization of the Brain Activity during Mental Rotation Processing Using MUSIC-Weighted Lead-Field Synthetic Filtering

Sunao IWAKI, Mitsuo TONOIKE, Shoogo UENO

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In this paper, we propose a method to reconstruct current distributions in the human brain from neuromagnetic measurements. The proposed method is based on the weighted lead-field synthetic (WLFS) filtering technique with the weighting factors calculated from the results of previous source space scanning. In this method, in addition to the depth normalization technique, weighting factors of the WLFS are determined by the cost values previously calculated based on the multiple signal classification (MUSIC) scan. We performed computer simulations of this method under noisy measurement conditions and compared the results to those obtained with the conventional WLFS method. The results of the simulations indicate that the proposed method is effective for the reconstruction of the current distributions in the human brain using magnetoencephalographic (MEG) measurements, even if the signal-to-noise ratio of the measured data is relatively low. We applied the proposed method to the magnetoencephalographic data obtained during a mental image processing task that included object recognition and mental rotation operations. The results suggest that the proposed method can extract the neural activity in the extrastriate visual region and the parietal region. These results are in agreement with the results of previous positron emission tomography (PET) and functional magnetic resonance imaging (fMRI) studies.

Publication: IEICE TRANSACTIONS on Information Vol.E85-D No.1 pp.175-183

Publication Date: 2002/01/01

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Type of Manuscript: Special Section PAPER (Special Issue on Measurements and Visualization Technology of Biological Information)

Category: Inverse Problem

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Sunao IWAKI, Mitsuo TONOIKE, Shoogo UENO, "Visualization of the Brain Activity during Mental Rotation Processing Using MUSIC-Weighted Lead-Field Synthetic Filtering" in IEICE TRANSACTIONS on Information, vol. E85-D, no. 1, pp. 175-183, January 2002, doi: .
Abstract: In this paper, we propose a method to reconstruct current distributions in the human brain from neuromagnetic measurements. The proposed method is based on the weighted lead-field synthetic (WLFS) filtering technique with the weighting factors calculated from the results of previous source space scanning. In this method, in addition to the depth normalization technique, weighting factors of the WLFS are determined by the cost values previously calculated based on the multiple signal classification (MUSIC) scan. We performed computer simulations of this method under noisy measurement conditions and compared the results to those obtained with the conventional WLFS method. The results of the simulations indicate that the proposed method is effective for the reconstruction of the current distributions in the human brain using magnetoencephalographic (MEG) measurements, even if the signal-to-noise ratio of the measured data is relatively low. We applied the proposed method to the magnetoencephalographic data obtained during a mental image processing task that included object recognition and mental rotation operations. The results suggest that the proposed method can extract the neural activity in the extrastriate visual region and the parietal region. These results are in agreement with the results of previous positron emission tomography (PET) and functional magnetic resonance imaging (fMRI) studies.
URL: https://global.ieice.org/en_transactions/information/10.1587/e85-d_1_175/_p

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@ARTICLE{e85-d_1_175,
author={Sunao IWAKI, Mitsuo TONOIKE, Shoogo UENO, },
journal={IEICE TRANSACTIONS on Information},
title={Visualization of the Brain Activity during Mental Rotation Processing Using MUSIC-Weighted Lead-Field Synthetic Filtering},
year={2002},
volume={E85-D},
number={1},
pages={175-183},
abstract={In this paper, we propose a method to reconstruct current distributions in the human brain from neuromagnetic measurements. The proposed method is based on the weighted lead-field synthetic (WLFS) filtering technique with the weighting factors calculated from the results of previous source space scanning. In this method, in addition to the depth normalization technique, weighting factors of the WLFS are determined by the cost values previously calculated based on the multiple signal classification (MUSIC) scan. We performed computer simulations of this method under noisy measurement conditions and compared the results to those obtained with the conventional WLFS method. The results of the simulations indicate that the proposed method is effective for the reconstruction of the current distributions in the human brain using magnetoencephalographic (MEG) measurements, even if the signal-to-noise ratio of the measured data is relatively low. We applied the proposed method to the magnetoencephalographic data obtained during a mental image processing task that included object recognition and mental rotation operations. The results suggest that the proposed method can extract the neural activity in the extrastriate visual region and the parietal region. These results are in agreement with the results of previous positron emission tomography (PET) and functional magnetic resonance imaging (fMRI) studies.},
keywords={},
doi={},
ISSN={},
month={January},}

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TY - JOUR
TI - Visualization of the Brain Activity during Mental Rotation Processing Using MUSIC-Weighted Lead-Field Synthetic Filtering
T2 - IEICE TRANSACTIONS on Information
SP - 175
EP - 183
AU - Sunao IWAKI
AU - Mitsuo TONOIKE
AU - Shoogo UENO
PY - 2002
DO -
JO - IEICE TRANSACTIONS on Information
SN -
VL - E85-D
IS - 1
JA - IEICE TRANSACTIONS on Information
Y1 - January 2002
AB - In this paper, we propose a method to reconstruct current distributions in the human brain from neuromagnetic measurements. The proposed method is based on the weighted lead-field synthetic (WLFS) filtering technique with the weighting factors calculated from the results of previous source space scanning. In this method, in addition to the depth normalization technique, weighting factors of the WLFS are determined by the cost values previously calculated based on the multiple signal classification (MUSIC) scan. We performed computer simulations of this method under noisy measurement conditions and compared the results to those obtained with the conventional WLFS method. The results of the simulations indicate that the proposed method is effective for the reconstruction of the current distributions in the human brain using magnetoencephalographic (MEG) measurements, even if the signal-to-noise ratio of the measured data is relatively low. We applied the proposed method to the magnetoencephalographic data obtained during a mental image processing task that included object recognition and mental rotation operations. The results suggest that the proposed method can extract the neural activity in the extrastriate visual region and the parietal region. These results are in agreement with the results of previous positron emission tomography (PET) and functional magnetic resonance imaging (fMRI) studies.
ER -