nips nips2003 nips2003-182 nips2003-182-reference knowledge-graph by maker-knowledge-mining
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Author: Sung C. Jun, Barak A. Pearlmutter
Abstract: We describe a system that localizes a single dipole to reasonable accuracy from noisy magnetoencephalographic (MEG) measurements in real time. At its core is a multilayer perceptron (MLP) trained to map sensor signals and head position to dipole location. Including head position overcomes the previous need to retrain the MLP for each subject and session. The training dataset was generated by mapping randomly chosen dipoles and head positions through an analytic model and adding noise from real MEG recordings. After training, a localization took 0.7 ms with an average error of 0.90 cm. A few iterations of a Levenberg-Marquardt routine using the MLP’s output as its initial guess took 15 ms and improved the accuracy to 0.53 cm, only slightly above the statistical limits on accuracy imposed by the noise. We applied these methods to localize single dipole sources from MEG components isolated by blind source separation and compared the estimated locations to those generated by standard manually-assisted commercial software. 1
Abeyratne, U. R., Kinouchi, Y., Oki, H., Okada, J., Shichijo, F., and Matsumoto, K. (1991). Artificial neural networks for source localization in the human brain. Brain Topography, 4:3–21. Ahonen, A. I., H¨ m¨ l¨ inen, M. S., Knuutila, J. E. T., Kajola, M. J., Laine, P. P., Lounasmaa, a aa O. V., Parkkonen, L. T., Simola, J. T., and Tesche, C. D. (1993). 122-channel SQUID instrument for investigating the magnetic signals from the human brain. Physica Scripta, T49:198–205. H¨ m¨ l¨ inen, M., Hari, R., Ilmoniemi, R. J., Knuutila, J., and Lounasmaa, O. V. (1993). a aa Magnetoencephalography—theory, instrumentation, and applications to noninvasive studies of the working human brain. Rev. Modern Physics, 65:413–497. Hoey, G. V., Clercq, J. D., Vanrumste, B., de Walle, R. V., Lemahieu, I., D’Hav´ , M., and e Boon, P. (2000). EEG dipole source localization using artificial neural networks. Phys. Med. Biol., 45:997–1011. Jun, S. C., Pearlmutter, B. A., and Nolte, G. (2002). Fast accurate MEG source localization using a multilayer perceptron trained with real brain noise. Physics in Medicine and Biology, 47(14):2547–2560. Jun, S. C., Pearlmutter, B. A., and Nolte, G. (2003). MEG source localization using a MLP with a distributed output representation. IEEE Transactions on Biomedical Engineering, 50(6):786–789. Kinouchi, Y., Ohara, G., Nagashino, H., Soga, T., Shichijo, F., and Matsumoto, K. (1996). Dipole source localization of MEG by BP neural networks. Brain Topography, 8:317– 321. Kwon, H., Lee, Y. H., Kim, J. M., Park, Y. K., and Kuriki, S. (2002). Localization accuracy of single current dipoles from tangential components of auditory evoked fields. Phys. Med. Biol., 47:4145–4154. Leahy, R. M., Mosher, J. C., Spencer, M. E., Huang, M. X., and Lewine, J. D. (1998). A study of dipole localization accuracy for MEG and EEG using a human skull phantom. Electroencephalography and clinical neurophysiology, 107(2):159–173. Press, W. H., Flannery, B. P., Teukolsky, S. A., and Verrerling, W. T. (1988). Numerical Recipes in C. Cambridge University Press. Rumelhart, D. E., Hinton, G. E., and Williams, R. J. (1986). Learning representations by back–propagating errors. Nature, 323:533–536. Sander, T. H., W¨ bbeler, G., Lueschow, A., Curio, G., and Trahms, L. (2002). Cardiac aru tifact subspace identification and elimination in cognitive MEG data using time-delayed decorrelation. IEEE Transactions on Biomedical Engineering, 49:345–354. Tang, A. C. and Pearlmutter, B. A. (2003). Independent components of magnetoencephalography: Localization and single-trial response onset detection. In Lu, Z.-L. and Kaufman, L., editors, Magnetic Source Imaging of the Human Brain, pages 159–201. Lawrence Erlbaum Associates. Tang, A. C., Pearlmutter, B. A., Malaszenko, N. A., Phung, D. B., and Reeb, B. C. (2002). Independent components of magnetoencephalography: Localization. Neural Computation, 14(8):1827–1858. Tang, A. C., Pearlmutter, B. A., Zibulevsky, M., and Carter, S. A. (2000a). Blind separation of multichannel neuromagnetic responses. Neurocomputing, 32–33:1115–1120. Tang, A. C., Pearlmutter, B. A., Zibulevsky, M., Hely, T. A., and Weisend, M. P. (2000b). An MEG study of response latency and variability in the human visual system during a visual-motor integration task. In Advances in Neural Information Processing Systems 12, pages 185–191. MIT Press. Vig´ rio, R., S¨ rel¨ , J., Jousm¨ ki, V., H¨ m¨ l¨ inen, M., and Oja, E. (2000). Independent a a a a a aa component approach to the analysis of EEG and MEG recordings. IEEE Transactions on Biomedical Engineering, 47(5):589–593.