### Abstract

Magnetic Field Tomography (MFT) is a source localization method for Magnetoencephalography (MEG), a non-invasive method to observe the brain activity. MFT just requires the source to be a linear combination of lead fields that describe the distribution of the sensitivity of each sensor, while other commonly used MEG source localization methods such as equivalent current dipole (ECD) fitting or the beamformer require some more inappropriate assumptions. However, less requirements on the source results in a huge amount of computational load in MFT. In this paper, the reduction of the computational load for MFT was achieved by considering the coefficients of multipolar expansion as the measurements of virtual sensors. These coefficients are obtained by performing Signal Space Separation (SSS) in which the exclusion of external magnetic field generated by the external sensor arrays is enabled. Based on our simulation, the calculation time was reduced from 6 hours to about 10 seconds preserving the source localization ability.

Original language | English |
---|---|

Title of host publication | AIP Conference Proceedings |

Pages | 178-185 |

Number of pages | 8 |

Volume | 1371 |

DOIs | |

Publication status | Published - 2011 |

Event | 2011 International Symposium on Computational Models for Life Sciences, CMLS-11 - Toyama City, Japan Duration: 2011 Oct 11 → 2011 Oct 13 |

### Other

Other | 2011 International Symposium on Computational Models for Life Sciences, CMLS-11 |
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Country | Japan |

City | Toyama City |

Period | 11/10/11 → 11/10/13 |

### Fingerprint

### Keywords

- Inverse problem
- Magnetic field tomography(MFT)
- Magnetoencephalography(MEG)
- Signal space separation(SSS)

### ASJC Scopus subject areas

- Physics and Astronomy(all)

### Cite this

*AIP Conference Proceedings*(Vol. 1371, pp. 178-185) https://doi.org/10.1063/1.3596641

**Solution for MEG inverse problem using Signal Space Separation and Magnetic Field Tomography.** / Kitahara, Tadashi; Honda, Satoshi.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

*AIP Conference Proceedings.*vol. 1371, pp. 178-185, 2011 International Symposium on Computational Models for Life Sciences, CMLS-11, Toyama City, Japan, 11/10/11. https://doi.org/10.1063/1.3596641

}

TY - GEN

T1 - Solution for MEG inverse problem using Signal Space Separation and Magnetic Field Tomography

AU - Kitahara, Tadashi

AU - Honda, Satoshi

PY - 2011

Y1 - 2011

N2 - Magnetic Field Tomography (MFT) is a source localization method for Magnetoencephalography (MEG), a non-invasive method to observe the brain activity. MFT just requires the source to be a linear combination of lead fields that describe the distribution of the sensitivity of each sensor, while other commonly used MEG source localization methods such as equivalent current dipole (ECD) fitting or the beamformer require some more inappropriate assumptions. However, less requirements on the source results in a huge amount of computational load in MFT. In this paper, the reduction of the computational load for MFT was achieved by considering the coefficients of multipolar expansion as the measurements of virtual sensors. These coefficients are obtained by performing Signal Space Separation (SSS) in which the exclusion of external magnetic field generated by the external sensor arrays is enabled. Based on our simulation, the calculation time was reduced from 6 hours to about 10 seconds preserving the source localization ability.

AB - Magnetic Field Tomography (MFT) is a source localization method for Magnetoencephalography (MEG), a non-invasive method to observe the brain activity. MFT just requires the source to be a linear combination of lead fields that describe the distribution of the sensitivity of each sensor, while other commonly used MEG source localization methods such as equivalent current dipole (ECD) fitting or the beamformer require some more inappropriate assumptions. However, less requirements on the source results in a huge amount of computational load in MFT. In this paper, the reduction of the computational load for MFT was achieved by considering the coefficients of multipolar expansion as the measurements of virtual sensors. These coefficients are obtained by performing Signal Space Separation (SSS) in which the exclusion of external magnetic field generated by the external sensor arrays is enabled. Based on our simulation, the calculation time was reduced from 6 hours to about 10 seconds preserving the source localization ability.

KW - Inverse problem

KW - Magnetic field tomography(MFT)

KW - Magnetoencephalography(MEG)

KW - Signal space separation(SSS)

UR - http://www.scopus.com/inward/record.url?scp=79960099451&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=79960099451&partnerID=8YFLogxK

U2 - 10.1063/1.3596641

DO - 10.1063/1.3596641

M3 - Conference contribution

SN - 9780735409316

VL - 1371

SP - 178

EP - 185

BT - AIP Conference Proceedings

ER -