Analysis of pain-related somatosensory evoked magnetic fields using the MUSIC (multiple signal classification) algorithm for magnetoencephalography

Yotaro Ninomiya; Yoshihiro Kitamura; Shin Yamamoto; Motoi Okamoto; Hisao Oka; Norihito Yamada; Shigetoshi Kuroda

doi:10.1097/00001756-200106130-00029

Analysis of pain-related somatosensory evoked magnetic fields using the MUSIC (multiple signal classification) algorithm for magnetoencephalography

Yotaro Ninomiya, Yoshihiro Kitamura, Shin Yamamoto, Motoi Okamoto, Hisao Oka, Norihito Yamada, Shigetoshi Kuroda

Research output: Contribution to journal › Article › peer-review

10 Citations (Scopus)

Abstract

We evaluated the effectiveness of the Multiple Signal Classification (MUSIC) algorithm by analysing pain-related somatosensory-evoked magnetic fields (SEFs) by 148-channel whole-head-type magnetoencephalography. MUSIC peaks of middle latency components were located around the primary somatosensory cortex (SI), contralateral to the stimulated finger. Long latency components were located around the bilateral secondary somatosensory cortices (SII) and cingulate gyri. Peaks at the SII and cingulate gyri were more prominent on very painful and moderately painful stimulation than on weak stimulation. The results were in very good agreement with results from single dipole estimation. These findings suggest that the MUSIC algorithm could be a useful tool for analysis of pain-related SEFs.

Original language	English
Pages (from-to)	1657-1661
Number of pages	5
Journal	NeuroReport
Volume	12
Issue number	8
DOIs	https://doi.org/10.1097/00001756-200106130-00029
Publication status	Published - Jun 13 2001

Keywords

Multiple signal classification (MUSIC) algorithm
Pain-related somatosensory-evoked magnetic fields
Whole-head-type magnetoencephalography

ASJC Scopus subject areas

Neuroscience(all)

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10.1097/00001756-200106130-00029

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title = "Analysis of pain-related somatosensory evoked magnetic fields using the MUSIC (multiple signal classification) algorithm for magnetoencephalography",

abstract = "We evaluated the effectiveness of the Multiple Signal Classification (MUSIC) algorithm by analysing pain-related somatosensory-evoked magnetic fields (SEFs) by 148-channel whole-head-type magnetoencephalography. MUSIC peaks of middle latency components were located around the primary somatosensory cortex (SI), contralateral to the stimulated finger. Long latency components were located around the bilateral secondary somatosensory cortices (SII) and cingulate gyri. Peaks at the SII and cingulate gyri were more prominent on very painful and moderately painful stimulation than on weak stimulation. The results were in very good agreement with results from single dipole estimation. These findings suggest that the MUSIC algorithm could be a useful tool for analysis of pain-related SEFs.",

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AU - Ninomiya, Yotaro

AU - Kitamura, Yoshihiro

AU - Yamamoto, Shin

AU - Okamoto, Motoi

AU - Oka, Hisao

AU - Yamada, Norihito

AU - Kuroda, Shigetoshi

PY - 2001/6/13

Y1 - 2001/6/13

N2 - We evaluated the effectiveness of the Multiple Signal Classification (MUSIC) algorithm by analysing pain-related somatosensory-evoked magnetic fields (SEFs) by 148-channel whole-head-type magnetoencephalography. MUSIC peaks of middle latency components were located around the primary somatosensory cortex (SI), contralateral to the stimulated finger. Long latency components were located around the bilateral secondary somatosensory cortices (SII) and cingulate gyri. Peaks at the SII and cingulate gyri were more prominent on very painful and moderately painful stimulation than on weak stimulation. The results were in very good agreement with results from single dipole estimation. These findings suggest that the MUSIC algorithm could be a useful tool for analysis of pain-related SEFs.

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KW - Whole-head-type magnetoencephalography

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Analysis of pain-related somatosensory evoked magnetic fields using the MUSIC (multiple signal classification) algorithm for magnetoencephalography

Abstract

Keywords

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