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Artifact Removal Using Simultaneous Current Estimation of Noise and Cortical Sources

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Advances in Neuro-Information Processing (ICONIP 2008)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 5506))

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Abstract

The measurement of magnetoencephalographic (MEG) signals is contaminated by large magnetic artifacts, such as heart beats, eye movements, and muscle activities, and so on. These artifacts can be orders of magnitude larger than the signal from the brain, thus making cortical current estimation extremely difficult. This paper proposes a novel method to remove the effects of artifacts by simultaneously estimating the cortical and artifactual dipole currents. By using proper prior information, we show that this method can estimate the currents of artifacts and cortical activities simultaneously, and the estimated cortical currents are more reasonable in comparison to those of previous methods.

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References

  1. Berg, P., Scherg, M.: Dipole models of eye movements and blinks. Electroencephalogr. Clin. Neurophysiol. 79, 36–44 (1991)

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  2. Fujiwara, Y., Yamashita, O., Kawawaki, D., Doya, K., Kawato, M., Toyama, K., Sato, M.: A hierarchical Bayesian method to resolve an inverse problem of MEG contaminated with eye movement artifacts. NeuroImage (2008) (to appear)

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  3. Sato, M., Yoshioka, T., Kajiwara, S., Toyama, K., Goda, N., Doya, K., Kawato, M.: Hierarchical Bayesian estimation for MEG inverse problem. Neuroimage 23(3), 806–826 (2004)

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  4. Yoshioka, T., Toyama, K., Kawato, M., Yamashita, O., Nishina, S., Yamagishi, N., Sato, M.A.: Evaluation of hierarchical Bayesian method through retinotopic brain activities reconstruction from fMRI and MEG signals. Neuroimage 42(4), 1397–1413 (2008)

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© 2009 Springer-Verlag Berlin Heidelberg

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Morishige, Ki., Kawawaki, D., Yoshioka, T., Sato, Ma., Kawato, M. (2009). Artifact Removal Using Simultaneous Current Estimation of Noise and Cortical Sources. In: Köppen, M., Kasabov, N., Coghill, G. (eds) Advances in Neuro-Information Processing. ICONIP 2008. Lecture Notes in Computer Science, vol 5506. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02490-0_41

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  • DOI: https://doi.org/10.1007/978-3-642-02490-0_41

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-02489-4

  • Online ISBN: 978-3-642-02490-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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