Independent component analysis and clustering improve signal-to-noise ratio for statistical analysis of event-related potentials

Clinical Neurophysiology

Volumn 118, Issue 12, 2007, Pages 2591-2604

  Zeman, Philip M ^a   Till, Bernie C ^a   Livingston, Nigel J ^a   Tanaka, James W ^a   Driessen, Peter F ^a  

^a UNIVERSITY OF VICTORIA   (Canada)

Author keywords

Channel pooling; EEG; Effect size; ICA; N170; Signal to noise ratio

Indexed keywords

ADULT; ARTICLE; CONTROLLED STUDY; EVENT RELATED POTENTIAL; FEMALE; HUMAN; HUMAN EXPERIMENT; MALE; METHODOLOGY; NORMAL HUMAN; PRIORITY JOURNAL; SIGNAL NOISE RATIO; STIMULUS RESPONSE; TASK PERFORMANCE;

ADULT; ANALYSIS OF VARIANCE; ARTIFACTS; BRAIN MAPPING; CEREBRAL CORTEX; CLUSTER ANALYSIS; DATA INTERPRETATION, STATISTICAL; ELECTRODES; ELECTROENCEPHALOGRAPHY; EVOKED POTENTIALS; FEMALE; HUMANS; MALE; MIDDLE AGED; OBSERVER VARIATION; PATTERN RECOGNITION, VISUAL; PHOTIC STIMULATION; SIGNAL PROCESSING, COMPUTER-ASSISTED;

EID: 36549022226     PISSN: 13882457     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.clinph.2007.09.001     Document Type: Article

References (43)

1. Achim A., and Bouchard S. Toward a dynamic topographic components model. Electroencephalogr Clin Neurophysiol 103 3 (1997) 381-385
2. Achim A., and Marcantoni W. Principal component analysis of event-related potentials: misallocation of variance revisited. Psychophysiology 34 (1997) 597-606
3. Bell A., and Sejnowski T.J. An information-maximization approach to blind separation and blind deconvolution. Neural Comp 7 (1995) 1129-1159
4. Burman P. A comparative study of ordinary cross-validation, v-fold cross-validation and the repeated learning-testing methods. Biometrika 78 3 (1989) 503-514
5. Cardoso J.F. Entropic contrasts for source separation. In: Haykin S. (Ed). Adaptive unsupervised learning (1999), Wiley, New York
6. Cohen J. A power primer. Psychol Bull 112 (1992) 155-159
7. Comon P. Independent component analysis - a new concept?. Signal Process 36 (1994) 287-314
8. Contreras-Vidal J.L., and Kerick S.E. Independent component analysis of dynamic brain responses during visuomotor adaptation. NeuroImage 21 3 (2004) 936-945
9. Delorme A., and Makeig S. EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis. J Neurosci Methods 134 (2004) 9-21
10. Delorme A, Serby H, Makeig S. EEGLab tutorial: VI. Independent component clustering. Retrieved October 11, 2006 from http://www.sccn.ucsd.edu/eeglab/clusttut/clustertut.html.
11. Dien J. Addressing misallocation of variance in principal components analysis of event-related potentials. Brain Topogr 11 1 (1998) 43-55
12. Dien J., and Santuzzi A.M. Application of repeated measures ANOVA to high-density ERP datasets: a review and tutorial. In: Handy T.C. (Ed). Event-related potentials: a methods handbook (2005), MIT Press, Cambridge 57-82
13. Field A.S., and Graupe D. Topographic components analysis of evoked potentials: parameter estimation and some preliminary results. IEEE Int Symp Circuits Syst 3 (1990) 2049-2052
14. Field A.S., and Graupe D. Topographic component (parallel factor) analysis of multichannel evoked potentials: practical issues in trilinear spatiotemporal decomposition. Brain Topogr 3 4 (1991) 407-423
15. Field A.S., and Graupe D. Trilinear analysis applied to multichannel evoked potentials. IEEE Int Symp Circuits Syst 1 (1991) 726-729
16. Gratton G., Coles M.G.H., and Donchin E. A new method for off-line removal of ocular artifacts. Electroencephalogr Clin Neurophysiol 55 (1983) 468-484
17. Gauthier I., Curran T., Curby K.M., and Collins D. Perceptual interference supports a non-modular account of face processing. Nat Neurosci 6 (2003) 428-432
18. Hyvärinen A., Karhunen J., and Oja E. Independent component analysis (2001), John Wiley and Sons, New York
19. Hyvärinen A., and Oja E. A fast fixed-point algorithm for independent component analysis. Neural Comput 9 7 (1997) 1483-1492
20. Jasper H. The ten-twenty system of the international federation. Electroencephalogr Clin Neurophysiol 10 (1958) 271-275
21. Jung T.P., Makeig S., Westerfield M., Townsend J., Courchesne E., and Sejnowki T.J. Analysis and visualization of single-trial event-related potentials. Human Brain Map 14 3 (2001) 166-185
22. Karhunen J., Mǎlǎroiu S., and Ilmoniemi M. Local linear independent component analysis based on clustering. Int J Neural Syst 10 6 (2000) 439-450
23. Kayser J., and Tenke C.E. Optimizing PCA methodology for ERP component identification and measurement: theoretical rationale and empirical evaluation. Clin Neurophysiol 114 (2003) 2307-2325
24. Lal T.N., Schröder M., Hinterberger T., Weston J., Bogdan M., Birbaumer N., et al. Support vector channel selection in BCI. IEEE Trans Biomed Eng 51 6 (2004) 1003-1010
25. Lee T.W., Girolami M., Bell A.J., and Sejnowski T.J. A unifying information-theoretic framework for independent component analysis. Comput Math Appl 39 (2000) 1-21
26. Makeig S., Bell A., Jung T., and Sejnowski T. Independent component analysis of electroencephalographic data. In: Touretzky D., Mozer M., and Hasselmo M. (Eds). Advances in neural information processing systems vol. 8 (1996), MIT Press, Cambridge, MA 145-151
27. Makeig S., Delorme A., Westerfield M., Jung T.P., Townsend J., Courchesne E., et al. Electroencephalographic brain dynamics following manually responded visual targets. PLoS Biol 2 6 (2004) 0747-0762
28. Makeig S., Jung T.-P., Ghahremani D., and Sejnowski T.J. Independent component analysis of simulated ERP data. In: Nakada T. (Ed). Integrated human brain science: theory, method, applications (music) (2000), Elsevier, Amsterdam
29. McFarland D.J., McCane L.M., David S.V., and Wolpaw J.R. Spatial filter selection for EEG-based communication. Electroencephalogr Clin Neurophysiol 103 3 (1997) 386-394
30. Möcks J. Decomposing event-related potentials: a new topographic components model. Biol Psychol 26 (1998) 199-215
31. Möcks J. Topographic components model for event-related potentials and some biophysical considerations. IEEE Trans Biomed Eng 35 6 (1998) 482-484
32. Montgomery Jr. E.B., Huanga H., and Assadic A. Unsupervised clustering algorithm for N-dimensional data. J Neurosci Methods 144 1 (2005) 19-24
33. Onton J., Delorme A., and Makeig S. Frontal midline EEG dynamics during working memory. NeuroImage 17 2 (2005) 341-356
34. Papoulis A. Probability, random variables, and stochastic processes (1991), McGraw-Hill, New York
35. Parra L., and Sajda P. Converging evidence of linear independent components in eeg. Proc 1st Int IEEE EMBS Conf Neural Eng (2003) 525-528
36. Pham D.T., Garrat P., and Jutten C. Separation of a mixture of independent sources through a maximum-likelihood approach. Proc European Sig Process Conf (1992) 771-774
37. Rossion B., Gauthier I., Tarr M.J., Despland P., Bruyer R., Linotte S., et al. The N170 occipito-temporal component is delayed and enhanced to inverted faces but not to inverted objects: an electrophysiological account of face-specific processes in the human brain. Cogn Neurosci 11 (2000) 69-74
38. Sorensen PL, Zeman PM, Sutherland RJ. Differing patterns of synchronous cortical activity during a virtual spatial navigation task. Canadian Society for Brain, Behaviour and Cognitive Science, 16th Annual Meeting, Paper presentation; 2006.
39. Tabachnick B.G., and Fidell L.S. Using multivariate statistics. 2nd ed. (1989), HarperCollins Publishers, New York
40. Tanaka J, Porterfield A. The search for self-identity: The own-face effect (Abstract). J Vis 2001;1(3):334a.
41. Tanaka J.W., Curran T., Porterfield A., and Collins D. The activation of pre-existing and acquired face representations: The N250 ERP as an index of face familiarity. J Cogn Neurosci 18 (2006) 1488-1497
42. Wang K., Begleiter H., and Porjesz B. Trilinear modeling of event-related potentials. Brain Topogr 12 4 (2000) 263-271
43. Xu L. Bayesian Ying-Yang machine, clustering and number of clusters. Pattern Recogn Lett 18 (1997) 1167-1178