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Computational Intelligence and Neuroscience
Volume 2007, Article ID 14567, 13 pages
http://dx.doi.org/10.1155/2007/14567
Research Article

A Framework to Support Automated Classification and Labeling of Brain Electromagnetic Patterns

1Learning Research and Development Center, University of Pittsburgh, Pittsburgh, PA 15260, USA
2NeuroInformatics Center, University of Oregon, 1600 Millrace Drive, Eugene, OR 97403, USA
3Computer and Information Sciences, University of Oregon, Eugene, OR 97403, USA
4Department of Psychology, University of Kansas, 1415 Jayhawk Boulevard, Lawrence, KS 66045, USA

Received 19 February 2007; Revised 28 July 2007; Accepted 7 October 2007

Academic Editor: Saied Sanei

Copyright © 2007 Gwen A. Frishkoff et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. W. Klimesch, “Memory processes, brain oscillations and EEG synchronization,” International Journal of Psychophysiology, vol. 24, no. 1-2, pp. 61–100, 1996. View at Publisher · View at Google Scholar
  2. T.-P. Jung, S. Makeig, M. Westerfield, J. Townsend, E. Courchesne, and T. J. Sejnowski, “Analysis and visualization of single-trial event-related potentials,” Human Brain Mapping, vol. 14, no. 3, pp. 166–185, 2001. View at Publisher · View at Google Scholar
  3. M. Fabiani, G. Gratton, and M. G. H. Coles, “Event-related brain poten-tials: methods, theory, and applications,” in Handbook of Psychophysiology, J. Cacioppo, L. Tassinary, and G. Berntson, Eds., pp. 53–84, Cambridge University Press, New York, NY, USA, 2000, chapter 3. View at Google Scholar
  4. A. M. Proverbio and A. Zani, “Electromagnetic manifestations of mind and brain,” in The Cognitive Electrophysiology of Mind and Brain, A. Zani and A. M. Proverbio, Eds., pp. 13–37, Academic Press, New York, NY, USA, 2002, chapter 2. View at Google Scholar
  5. T. Gasser, J. C. Schuller, and U. S. Gasser, “Correction of muscle artefacts in the EEG power spectrum,” Clinical Neurophysiology, vol. 116, no. 9, pp. 2044–2050, 2005. View at Publisher · View at Google Scholar
  6. O. Hauk, M. H. Davis, M. Ford, F. Pulvermüller, and W. D. Marslen-Wilson, “The time course of visual word recognition as revealed by linear regression analysis of ERP data,” NeuroImage, vol. 30, no. 4, pp. 1383–1400, 2006. View at Publisher · View at Google Scholar
  7. K. Spencer, “Averaging, detection, and classification of single-trials ERPs,” in Event-Related Potentials: A Methods Handbook, T. Handy, Ed., pp. 209–228, MIT Press, Cambridge, Mass, USA, 2005. View at Google Scholar
  8. E. Donchin and E. Heffley, “Multivariate analysis of event-related potential data: a tutorial review,” in Multidisciplinary Perspectives in Event-Related Brain Potential Research, D. Otto, Ed., pp. 555–572, U.S. Government Printing Office, Washington, DC, USA, 1978. View at Google Scholar
  9. T. W. Picton, S. Bentin, P. Berg et al., “Guidelines for using human event-related potentials to study cognition: recording standards and publication criteria,” Psychophysiology, vol. 37, no. 2, pp. 127–152, 2000. View at Publisher · View at Google Scholar
  10. P. L. Nunez, Electric Fields of the Brain: The Neurophysics of EEG, Oxford University Press, New York, NY, USA, 1981.
  11. G. Gratton, M. G. H. Coles, and E. Donchin, “A procedure for using multi-electrode information in the analysis of components of the event-related potential: Vector filter,” Psychophysiology, vol. 26, no. 2, pp. 222–232, 1989. View at Publisher · View at Google Scholar
  12. K. M. Spencer, J. Dien, and E. Donchin, “A componential analysis of the ERP elicited by novel events using a dense electrode array,” Psychophysiology, vol. 36, no. 3, pp. 409–414, 1999. View at Publisher · View at Google Scholar
  13. T. Handy, “Basic principles of ERP quantification,” in Event-Related Potentials: A Methods Handbook, T. Handy, Ed., pp. 33–56, MIT Press, Cambridge, Mass, USA, 2005. View at Google Scholar
  14. A. C. Nobre and G. McCarthy, “Language-related ERPs: scalp distributions and modulation by word type and semantic priming,” Journal of Cognitive Neuroscience, vol. 6, no. 3, pp. 233–255, 1994. View at Google Scholar
  15. J. Dien, G. A. Frishkoff, A. Cerbone, and D. M. Tucker, “Parametric analysis of event-related potentials in semantic comprehension: evidence for parallel brain mechanisms,” Cognitive Brain Research, vol. 15, no. 2, pp. 137–153, 2003. View at Publisher · View at Google Scholar
  16. G. A. Frishkoff, “Hemispheric differences in strong versus weak semantic priming: evidence from event-related brain potentials,” Brain and Language, vol. 100, no. 1, pp. 23–43, 2007. View at Publisher · View at Google Scholar
  17. P. E. Compton, P. Grossenbacher, M. I. Posner, and D. M. Tucker, “A cognitive-anatomical approach to attention in lexical access,” Journal of Cognitive Neuroscience, vol. 3, no. 4, pp. 304–312, 1991. View at Google Scholar
  18. K. Huang, K. Itoh, S. Suwazono, and T. Nakada, “Electrophysiological correlates of grapheme-phoneme conversion,” Neuroscience Letters, vol. 366, no. 3, pp. 254–258, 2004. View at Publisher · View at Google Scholar
  19. J. Dien and G. A. Frishkoff, “Introduction to principal components analysis of event-related potentials,” in Event-Related Potentials: A Methods Handbook, T. Handy, Ed., pp. 189–208, MIT Press, Cambridge, Mass, USA, 2005. View at Google Scholar
  20. J. Dien, “PCA toolbox (version 1.093),” October 2004, Lawrence, Kan, USA. View at Google Scholar
  21. J. Dien, “Addressing misallocation of variance in principal components analysis of event-related potentials,” Brain Topography, vol. 11, no. 1, pp. 43–55, 1998. View at Publisher · View at Google Scholar
  22. D. Dou, G. Frishkoff, J. Rong, R. M. Frank, A. Malony, and D. M. Tucker, “Development of NeuroElectroMagnetic Ontologies (NEMO): a framework for mining brainwave ontologies,” in Proceedings of the 13th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD '07), pp. 270–279, San Jose, Calif, USA, August 2007. View at Publisher · View at Google Scholar
  23. J. Rong, D. Dou, G. A. Frishkoff, R. M. Frank, A. Malony, and D. M. Tucker, “A semi-automatic framework for mining ERP patterns,” in Proceedings of the 21st International Conference on Advanced Information Networking and Applications Workshops (AINAW '07), vol. 1, pp. 329–334, Niagara Falls, Canada, May 2007. View at Publisher · View at Google Scholar
  24. A. Rodriguez-Fornells, B. M. Schmitt, M. Kutas, and T. F. Münte, “Electrophysiological estimates of the time course of semantic and phonological encoding during listening and naming,” Neuropsychologia, vol. 40, no. 7, pp. 778–787, 2002. View at Publisher · View at Google Scholar
  25. A. P. Dempster, N. M. Laird, and D. B. Rubin, “Maximum likelihood from incomplete data via the EM algorithm,” Journal of the Royal Statistical Society Series B, vol. 39, no. 1, pp. 1–38, 1977. View at Google Scholar
  26. Weka 3, “Data Mining Software in Java,” http://www.cs.waikato.ac.nz/ml/weka/.
  27. J. Quinlan, C4.5: Programs for Machine Learning, Morgan Kaufmann, San Mateo, Calif, USA, 1993.
  28. G. A. Frishkoff, C. Perfetti, and C. Westbury, “ERP measures of partial semantics knowledge: left temporal indices of skill differences and lexical quality,” Biological Psychology, in revision.
  29. D. A. Medler and J. R. Binder, “MCWord: an online orthographic database of the English language,” 2005, http://www.neuro.mcw.edu/mcword/.
  30. M. D. Wilson, “The MRC psycholin-guistic database: machine readable dictionary,” Behavioural Research Methods, Instruments and Computers, vol. 20, no. 1, pp. 6–11, 1988. View at Google Scholar
  31. Electrical Geodesics (EGI), “Eugene, Oregon,” http://www.egi.com/.
  32. J. Dien, “Issues in the application of the average reference: review, critiques, and recommendations,” Behavior Research Methods, Instruments, and Computers, vol. 30, no. 1, pp. 34–43, 1998. View at Google Scholar
  33. M. Junghöfer, T. Elbert, D. M. Tucker, and C. Braun, “The polar average reference effect: a bias in estimating the head surface integral in EEG recording,” Clinical Neurophysiology, vol. 110, no. 6, pp. 1149–1155, 1999. View at Publisher · View at Google Scholar
  34. M. Junghöfer, T. Elbert, D. M. Tucker, and B. Rockstroh, “Statistical control of artifacts in dense array EEG/MEG studies,” Psychophysiology, vol. 37, no. 4, pp. 523–532, 2000. View at Publisher · View at Google Scholar
  35. G. McCarthy and C. C. Wood, “Scalp distributions of event-related potentials: an ambiguity associated with analysis of variance models,” Electroencephalography and Clinical Neurophysiology, vol. 62, no. 3, pp. 203–208, 1985. View at Publisher · View at Google Scholar
  36. R. Rosenthal and R. Rosnow, Essentials of Behavioral Research: Methods and Data Analysis, McGraw-Hill, New York, NY, USA, 2nd edition, 1991.
  37. D. Lehmann and W. Skrandies, “Spatial analysis of evoked potentials in man—a review,” Progress in Neurobiology, vol. 23, no. 3, pp. 227–250, 1984. View at Publisher · View at Google Scholar
  38. “Cartool software,” Functional Brain Mapping Laboratory, Geneva, Switzerland, http://brainmapping.unige.ch/Cartool.htm.
  39. T. Koenig, K. Kochi, and D. Lehmann, “Event-related electric microstates of the brain differ between words with visual and abstract meaning,” Electroencephalography and Clinical Neurophysiology, vol. 106, no. 6, pp. 535–546, 1998. View at Publisher · View at Google Scholar
  40. T. Koenig and D. Lehmann, “Microstates in language-related brain potential maps show noun-verb differences,” Brain and Language, vol. 53, no. 2, pp. 169–182, 1996. View at Publisher · View at Google Scholar