Massively Parallel Classification of Single-Trial EEG Signals Using a Min-Max Modular Neural Network

IEEE Transactions on Biomedical Engineering

Volumn 51, Issue 3, 2004, Pages 551-558

  Lu, Bao Liang ^a   Shin, Jonghan ^b   Ichikawa, Michinori ^c  

^a SHANGHAI JIAO TONG UNIVERSITY   (China)

^b Korea Institute of Science and Technology   (South Korea)

^c RIKEN BRAIN SCIENCE INSTITUTE   (Japan)

Author keywords

Brain computer interface; Classification of EEG; Min max modular neural network; Module combination; Parallel learning; Singletrial EEG; Task decomposition; Wavelet transform

Indexed keywords

HIERARCHICAL SYSTEMS; LARGE SCALE SYSTEMS; MULTILAYER NEURAL NETWORKS; WAVELET TRANSFORMS;

ELECTROENCEPHALOGRAM (EEG) SIGNALS;

ELECTROENCEPHALOGRAPHY;

ANIMAL EXPERIMENT; ARTICLE; ARTIFICIAL NEURAL NETWORK; BRAIN; COGNITION; COMPUTER INTERFACE; CONTROLLED STUDY; DISCRIMINATION LEARNING; ELECTROENCEPHALOGRAM; HIPPOCAMPUS; LEARNING; NONHUMAN; RAT; SIMULATION; WAVEFORM;

ALGORITHMS; ANIMALS; COGNITION; COMPUTING METHODOLOGIES; DIAGNOSIS, COMPUTER-ASSISTED; ELECTROENCEPHALOGRAPHY; EVOKED POTENTIALS; EXPERT SYSTEMS; HIPPOCAMPUS; MODELS, NEUROLOGICAL; NEURAL NETWORKS (COMPUTER); RATS; SIGNAL PROCESSING, COMPUTER-ASSISTED;

EID: 1242300104     PISSN: 00189294     EISSN: None     Source Type: Journal    
DOI: 10.1109/TBME.2003.821023     Document Type: Article

References (33)

1. J. Shin, B. L. Lu, A. Talnov, G. Matsumoto, and J. Brankack, "Reading auditory discrimination behavior of freely moving rats from hippocampal EEG," Neurocomputing, vol. 38-40, pp. 1557-1566, 2001.
2. A. A. petrosian, D. V. Prokhorov, W. Lajara-Nanson, and R. B. Schiffer, "Recurrent neural network-based approach for early recognition of Alzheimer's disease in EEG," Clin. Neurophysiol., vol. 112, pp. 1378-1387, 2001.
3. C. W. Anderson, "Effects of variations in neural network topology and output averaging on the discrimination of mental tasks from spontaneous electroencephalogram," J. Intell. Syst., vol. 7, no. 1-2, pp. 165-190, 1997.
4. B. O. Peters, G. Pfurtscheller, and H. Flyvbjerg, "Automatic differentiation of multichannel EEG signals," IEEE Trans. Biomed. Eng., vol. 48, pp. 111-116, Jan. 2001.
5. M. A. L. Nicolelis, "Actions from thoughts," Nature, vol. 409, pp. 403-407, 2001.
6. J. del R. Millan, J. Mourino, M. franze, F. Cincotti, M. Varsta, J. Heikkonen, and F. Babiloni, "A local neural classifier for the recognition of EEG patterns associated to mental tasks," IEEE Trans. Neural Networks, vol. 13, pp. 678-686, May 2002.
7. A. C. Tsoi, D. So, and A. A. Sergejew, "Classification of electroencephalogram using artificial neural networks," in Advances in Neural Information Processing Systems. San Mateo, CA: Morgan Kaufmann, 1994, vol. 6, pp. 1151-1158.
8. N. Masic and G. Pfurtscheller, "Neural network based classification of single-trial EEG data," Artif. Intell. Med., vol. 5, pp. 503-513, 1993.
9. B. H. Jansen and P. R. Desai, "K-complex detection using multi-layer perceptrons and recurrent networks," Int. J. Biomed. Computing, vol. 37, pp. 249-257, 1994.
10. C. Robert, J. Gaudy, and A. Limoge, "Electroencephalogram processing using neural networks," Clin. Neurophysiol., vol. 113, pp. 694-701, 2002.
11. N. Hazarika, J. Z. Chen, A. C. Tsoi, and A. Sergejew, "Classification of EEG signals using the wavelet transform," Signal Processing, vol. 59, pp. 61-72, 1997.
12. B. L. Lu and M. Ito, "Task decomposition based on class relations: A modular neural network architecture for pattern classification," in Biological and Artificial Computation: From Neuroscience to Technology, J. Mira, R. Moreno-Diaz, and J. Cabestany, Eds. Berlin, Germany: Springer-Verlag, 1997, vol. 1240, Lecture Notes in Computer Science, pp. 330-339.
13. -, "Task decomposition and module combination based on class relations: A modular neural network for pattern classification," IEEE Trans. Neural Networks, vol. 10, pp. 1244-1256, Sept. 1999.
14. J. Brankack, T. Seidenbecher, and H. Muller-Gartner, "Task-relevant late positive component in rats: Is it related to hippocampal theta rhythm?," Hippocampus, vol. 6, pp. 475-482, 1996.
15. S. Mallat, A Wavelet Tour of Signal Processing, 2nd ed. New York: Academic, 2001.
16. B. L. Lu, J. Shin, and M. Ichikawa, "Massively parallel classification of EEG signals using min-max modular neural networks," in Artificial Neural Networks-ICANN 2001, G. Dorffiner, H. Bischof, and K. Hornik, Eds. Berlin, Germany: Springer-Verlag, 2001, vol. 2130, Lecture Notes in Computer Science, pp. 601-608.
17. R. Anand, K. G. Mehrotra, C. K. Mohan, and S. Ranka, "An improved algorithm for neural network classification of imbalanced training sets," IEEE Trans. Neural Networks, pp. 962-973, Nov. 1993.
18. G. S. Almasi and A. Gottlieb, Highly Parallel Computing, 2nd ed. San Francisco, CA: Benjamin/Cummings, 1994.
19. B. L. Lu, Q. Ma, M. Ichikawa, and H. Isahara, "Efficient part-of-speech tagging with a min-max modular neural-network model," Appl. Intell., vol. 19, pp. 65-81, 2003.
20. N. Sundararajan and P. Saratchandran, Parallel Architectures for Artificial Neural Networks. Los Alamitos, CA: IEEE Comput. Soc. Press. 1998.
21. B. L. Lu and M. Ichikawa, "Emergence of learning: An approach to coping with NP-complete problems in learning," in Proc. IJCNN'2000, vol. IV, Como, Italy, July 24-27, 2000, pp. 159-164.
22. D. E. Rumelhart, G. E. Hinton, and R. J. Williams, "Learning internal representations by error propagation," in Parallel Distributed Processing: Exploration in the Microstructure of Cognition. Cambridge, MA: The MIT Press, 1986, vol. 1.
23. Q. Ma, B. L. Lu, M. Murata, M. Ichikawa, and H. Isahara, "On-line error detection of annotated corpus using modular neural networks," in Artificial Neural Networks-ICANN 2001, G. Dorffiner, H. Bischof, and K. Hornik, Eds. Berlin, Germany: Springer-Verlag, 2001, vol. 2130, Lecture Notes in Computer Science, pp. 1185-1192.
24. S. Haykin, Neural Networks: A Comprehensive Foundation, 2nd ed. Englewood Cliffs, NJ: Prentice-Hall, 1999.
25. J. S. Judd, Neural Network Design and the Complexity of Learning. Cambridge, MA: MIT Press, 1990.
26. E. Basar, Brain Function and Oscillations, II. Integrative Brain Function Neurophysiology and Cognitive Processes. Berlin, Germany: Springer-Verlag, 1998.
27. T. W. Picton, "The P300 wave of the human event-related potential," J. Clin. Neurophysiol., vol. 9, pp. 456-479, 1992.
28. C. Basar-Eroglu, E. Basar, and F. Schmielau, "P300 in freely moving cats with intracranial electrodes," Int. J. Neurosci., vol. 60, pp. 215-226, 1991.
29. W. Klimesch, "EEG alpha and theta oscillations reflect cognitive and memory performance: A review and analysis," Brain Res. Rev., vol. 29, pp. 169-195, 1999.
30. C. H. Vanderwolf, "Hippocampal electrical activity and voluntary movement in the rat," Electroenceph. Clin. Neurophysiol., vol. 26, pp. 407-418, 1969.
31. M. J. Kahana, R. Sekuler, J. B. Caplan, M. Kirschen, and J. R. Madsen, "Human theta oscillations exhibit task dependence during virtual maze navigation," Nature, vol. 399, pp. 781-784, 1999.
32. J. O'Keefe and N. Burgess, "Theta activity, virtual navigation and the human hippocampus," Trends Cogn. Sci., vol. 3, pp. 403-407, 1999.
33. E. Donchin, K. M. Spencer, and R. Wijesinghe, "The mental prosthesis: Assessing the speed of a P300-based brain-computer interface", IEEE Trans Rehab. Eng., vol. 8, pp. 174-179, June 2000.