Analysis of magnetic source localization of P300 using the multiple signal classification algorithm

The authors studied the localization of P300 magnetic sources using the multiple signal classification (MUSIC) algorithm. Six healthy subjects (aged 24–34 years old) were investigated with 148‐channel whole‐head type magnetencephalography using an auditory oddball paradigm in passive mode. The autho...

Full description

Saved in:
Bibliographic Details
Published inPsychiatry and Clinical Neurosciences Vol. 60; no. 6; pp. 645 - 651
Main Authors UOHASHI, TETSUO, KITAMURA, YOSHIHIRO, ISHIZU, SUGURU, OKAMOTO, MOTOI, YAMADA, NORIHITO, KURODA, SHIGETOSHI
Format Journal Article
LanguageEnglish
Published Melbourne, Australia Wiley 01.12.2006
Blackwell Publishing Asia
Blackwell Publishing
Subjects
Online AccessGet full text
ISSN1323-1316
1440-1819
DOI10.1111/j.1440-1819.2006.01578.x

Cover

Loading…
More Information
Summary:The authors studied the localization of P300 magnetic sources using the multiple signal classification (MUSIC) algorithm. Six healthy subjects (aged 24–34 years old) were investigated with 148‐channel whole‐head type magnetencephalography using an auditory oddball paradigm in passive mode. The authors also compared six stimulus combinations in order to find the optimal stimulus parameters for P300 magnetic field (P300m) in passive mode. Bilateral MUSIC peaks were located on the mesial temporal, superior temporal and parietal lobes. Interestingly, all MUSIC peaks in these regions emerged earlier in the right hemisphere than in the left hemisphere, suggesting that the right hemisphere has predominance over the left in the processing activity associated with P300m. There were no significant differences among the six stimulus combinations in evoking those P300m sources. The results of the present study suggest that the MUSIC algorithm could be a useful tool for analysis of the time‐course of P300m.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
ObjectType-Article-2
ObjectType-Feature-1
ISSN:1323-1316
1440-1819
DOI:10.1111/j.1440-1819.2006.01578.x