Pattern analysis of EEG responses to speech and voice: Influence of feature grouping

NeuroImage

Volumn 59, Issue 4, 2012, Pages 3641-3651

  Hausfeld, Lars ^a   De Martino, Federico ^a,b   Bonte, Milene ^a   Formisano, Elia ^a  

^a MAASTRICHT UNIVERSITY   (Netherlands)

^b UNIVERSITY OF MINNESOTA MEDICAL SCHOOL   (United States)

Author keywords

Audition; Classification; EEG; ERP; Machine learning; Speech

Indexed keywords

ALGORITHM; ARTICLE; BRAIN CORTEX; CLASSIFIER; CONTROLLED STUDY; DATA ANALYSIS; ELECTROENCEPHALOGRAPHY; FUNCTIONAL NEUROIMAGING; INDEPENDENT VARIABLE; MAGNETOENCEPHALOGRAPHY; OUTCOME ASSESSMENT; PATTERN RECOGNITION; PRIORITY JOURNAL; SPEECH; STIMULUS RESPONSE; TASK PERFORMANCE; VOICE; VOWEL; WORKING MEMORY;

AUDITORY PERCEPTION; BRAIN MAPPING; ELECTROENCEPHALOGRAPHY; FEMALE; HUMANS; MALE; PATTERN RECOGNITION, PHYSIOLOGICAL; SPEECH; VOICE;

EID: 84855183225     PISSN: 10538119     EISSN: 10959572     Source Type: Journal    
DOI: 10.1016/j.neuroimage.2011.11.056     Document Type: Article

References (35)

1. Åberg M.C., Wessberg J. Evolutionary optimization of classifiers and features for single-trial EEG Discrimination. Biomed. Eng. Online 2007, 6:32. 10.1186/1475-925X-6-32.
2. Bashashati A., Fatourechi M., Ward R.K., Birch G.E. A survey of signal processing algorithms in brain-computer interfaces based on electrical brain signals. J. Neural Eng. 2007, 4(2):R32-R57. 10.1088/1741-2560/4/2/R03.
3. Belin P., Zatorre R.J. Adaptation to speaker's voice in right anterior temporal lobe. Neuroreport 2003, 14(16):2105-2109. 10.1097/01.wnr.0000091689.94870.85.
4. Belin P., Fecteau S., Bédard C. Thinking the voice: neural correlates of voice perception. Trends Cogn. Sci. 2004, 8(3):129-135. 10.1016/j.tics.2004.01.008.
5. Benjamini Y., Hochberg Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J. R. Stat. Soc. Series B Stat. Methodol. 1995, 57(1):289-300.
6. Besserve M., Jerbi K., Laurent F., Baillet S., Martinerie J., Garnero L. Classification methods for ongoing EEG and MEG signals. Biol. Res. 2007, 40. 10.4067/S0716-97602007000500005.
7. Birbaumer N. Breaking the silence: brain-computer interfaces (BCI) for communication and motor control. Psychophysiology 2006, 43(6):517-532. 10.1111/j.1469-8986.2006.00456.x.
8. Bishop C.M. Pattern Recognition and Machine Learning (Information Science and Statistics) 2007, Springer, New York. 2nd ed.
9. Blankertz B., Lemm S., Treder M., Haufe S., Müller K.-R. Single-trial analysis and classification of ERP components - a tutorial. NeuroImage 2011, 56(2):814-825. 10.1016/j.neuroimage.2010.06.048.
10. Bonte M., Valente G., Formisano E. Dynamic and task-dependent encoding of speech and voice by phase reorganization of cortical oscillations. J. Neurosci. 2009, 29(6):1699-1706. 10.1523/JNEUROSCI.3694-08.2009.
11. Charest I., Pernet C.R., Rousselet G.A., Quiñones I., Latinus M., Fillion-Bilodeau S., et al. Electrophysiological evidence for an early processing of human voices. BMC Neurosci. 2009, 10:127. 10.1186/1471-2202-10-127.
12. Darlington R.B., Hayes A.F. Combining independent p values: extensions of the Stouffer and binomial methods. Psychol. Methods 2000, 5(4):496-515. 10.1037/1082-989X.5.4.496.
13. Delorme A., Makeig S. EEGLAB: An open source toolbox for analysis of single-trial EEG dynamics including independent component analysis. J. Neurosci. Meth. 2004, 134(1):9-21. 10.1016/j.jneumeth.2003.10.009.
14. De Martino F., Valente G., Staeren N., Ashburner J., Goebel R., Formisano E. Combining multivariate voxel selection and support vector machines for mapping and classification of fMRI spatial patterns. NeuroImage 2008, 43(1):44-58. 10.1016/j.neuroimage.2008.06.037.
15. Duda R.O., Hart P.E., Stork D.G. Pattern Classification: Pattern Classification 2001, John Wiley & Sons, New York. 2nd ed.
16. Formisano E., De Martino F., Bonte M., Goebel R. "Who" is saying "what"? Brain-based decoding of human voice and speech. Science 2008, 322(5903):970-973. 10.1126/science.1164318.
17. Golland P., Fischl B. Permutation tests for classification: towards statistical significance in image-based studies. Information Processing in Medical Imaging 2003, Vol. 2732:330-341. Springer, Berlin/Heidelberg. 10.1007/978-3-540-45087-0_28. C. Taylor, J. Noble (Eds.).
18. Guyon I., Weston J., Barnhill S., Vapnik V. Gene selection for cancer classification using support vector machines. Mach. Learn. 2002, 46:389-422. 10.1023/A:1012487302797.
19. Haynes J., Rees G. Decoding mental states from brain activity in humans. Nat. Rev. Neurosci. 2006, 7(7):523-534. 10.1038/nrn1931.
20. Hickok G., Poeppel D. The cortical organization of speech processing. Nat. Rev. Neurosci. 2007, 8(5):393-402. 10.1038/nrn2113.
21. Kerlin J.R., Shahin A.J., Miller L.M. Attentional gain control of ongoing cortical speech representations in a "cocktail party". J. Neurosci. 2010, 30(2):620-628. 10.1523/JNEUROSCI.3631-09.2010.
22. Kriegstein K.V., Giraud A. Distinct functional substrates along the right superior temporal sulcus for the processing of voices. NeuroImage 2004, 22(2):948-955. 10.1016/j.neuroimage.2004.02.020.
23. Lotte F., Congedo M., Lécuyer A., Lamarche F., Arnaldi B. A review of classification algorithms for EEG-based brain-computer interfaces. J. Neural Eng. 2007, 4(2):R1-R13. 10.1088/1741-2560/4/2/R01.
24. Luo H., Poeppel D. Phase patterns of neuronal responses reliably discriminate speech in human auditory cortex. Neuron 2007, 54(6):1001-1010. 10.1016/j.neuron.2007.06.004.
25. Makeig S., Westerfield M., Jung T., Enghoff S., Townsend J., Courchesne E., Sejnowski T.J. Dynamic brain sources of visual evoked responses. Science 2002, 295(5555):690-694. 10.1126/science.1066168.
26. Mitchell T. Machine Learning 1997, Mcgraw-Hill. 1st ed.
27. Obleser J., Elbert T., Eulitz C. Attentional influences on functional mapping of speech sounds in human auditory cortex. BMC Neurosci. 2004, 5(1):24. 10.1186/1471-2202-5-24.
28. Pereira F., Mitchell T., Botvinick M. Machine learning classifiers and fMRI: a tutorial overview. NeuroImage 2009, 45(1, Supplement 1):S199-S209. 10.1016/j.neuroimage.2008.11.007.
29. Pfurtscheller G., Lopes da Silva F.H. Event-related EEG/MEG synchronization and desynchronization: basic principles. Clin. Neurophysiol. 1999, 110(11):1842-1857. 10.1016/S1388-2457(99)00141-8.
30. Rieger J.W., Reichert C., Gegenfurtner K.R., Noesselt T., Braun C., Heinze H., Kruse R., et al. Predicting the recognition of natural scenes from single trial MEG recordings of brain activity. NeuroImage 2008, 42(3):1056-1068. 10.1016/j.neuroimage.2008.06.014.
31. Schad A., Schindler K., Schelter B., Maiwald T., Brandt A., Timmer J., Schulze-Bonhage A. Application of a multivariate seizure detection and prediction method to non-invasive and intracranial long-term EEG recordings. Clin. Neurophysiol. 2008, 119(1):197-211. 10.1016/j.clinph.2007.09.130.
32. van Gerven M., Farquhar J., Schaefer R., Vlek R., Geuze J., Nijholt A., Ramsey N., et al. The brain-computer interface cycle. J. Neural Eng. 2009, 6(4):041001. 10.1088/1741-2560/6/4/041001.
33. Vapnik V.N. The Nature of Statistical Learning Theory 1995, Springer. 1st ed.
34. Varela F., Lachaux J., Rodriguez E., Martinerie J. The brainweb: phase synchronization and large-scale integration. Nat. Rev. Neurosci. 2001, 2(4):229-239. 10.1038/35067550.
35. Wolpaw J.R., Birbaumer N., McFarland D.J., Pfurtscheller G., Vaughan T.M. Brain-computer interfaces for communication and control. Clin. Neurophysiol. 2002, 113(6):767-791. 10.1016/S1388-2457(02)00057-3.