Abstract
This chapter deals with the analysis of multitrial electrophysiology datasets coming from neuroelectromagnetic recordings by electro-encephalography and magneto-encephalography (EEG and MEG). For such measurements, multitrial recordings are necessary in order to extract meaningful information. The obtained datasets present several characteristics: no ground-truth data, high level of noise (defined as the part of the data which is uncorrelated across trials), inter-trial variability. This chapter presents tools that deal with such datasets and their properties. The focus is on two families of data processing methods: data-driven methods, in a section on non-linear dimensionality reduction, and model-driven methods, in a section on Matching Pursuit and its extensions. The importance of correctly capturing the inter-trial variability is underlined in the last section which presents four case-studies in clinical and cognitive neuroscience.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
S. Baillet, J.C. Mosher, and R.M. Leahy. Electromagnetic brain mapping. IEEE Signal Processing Magazine, 18(6):14–30, 2001.
M. Belkin and P. Niyogi. Laplacian Eigenmaps for Dimensionality Reduction and Data Representation. Neural Computation, 15:1373–1396, 2003.
C.G. Bénar, T. Papadopoulo, B. Torrésani, and M. Clerc. Consensus matching pursuit for multi-trial eeg signals. Journal of Neuroscience Methods, 180:161–170, 2009.
C.G. Bénar, D. Schön, S. Grimault, B. Nazarian, B. Burle, M. Roth, J.M. Badier, P. Marquis, C. Liegeois-Chauvel, and J.L. Anton. Single-trial analysis of oddball event-related potentials in simultaneous EEG-fMRI. Human Brain Mapping, 28:602–613, 2007.
B. Burle, C. Roger, S. Allain, F. Vidal, and T. Hasbroucq. Error negativity does not reflect conflict: a reappraisal of conflict monitoring and anterior cingulate cortex activity. J. of Cogn. Neurosci., 20(9):1637–55, 2008.
P. Comon. Independent component analysis - a new concept? Signal Processing, 36, 1994.
J. de Munck, F. Bijma, P. Gaura, C. Sieluzycki, M. Branco, and R. Heethaar. A maximum-likelihood estimator for trial-to-trial variations in noisy MEG/EEG data sets. IEEE Trans. Biomed. Eng., 51(12):2123–28, 2004.
S. Debener, M. Ullsperger, M. Siegel, K. Fiehler, D. von Cramon, and A. Engel. Trial-by-trial coupling of concurrent electroencephalogram and functional magnetic resonance imaging identifies the dynamics of performance monitoring. Neuroscience, 2005.
T. Eichele, K. Specht, M. Moosmann, M. Jongsma, R. Quian Quiroga, H. Nordby, and K. Hugdahl. Assessing the spatiotemporal evolution of neuronal activation with single-trial event-related potentials and functional MRI. Proc Natl Acad Sci U.S.A., 2005.
A. Gramfort, R. Keriven, and M. Clerc. Graph-based variability estimation in single-trial event-related neural responses. IEEE Trans. Biomed. Engin., 56(5):1051–1061, 2010.
R. Gribonval, H. Rauhut, K. Schnass, and P. Vandergheynst. Atoms of all channels, unite! Average case analysis of multi-channel sparse recovery using greedy algorithms. The Journal of Fourier Analysis and Applications, 14(5):655–687, 2008.
M. Hein, J. Audibert, and U. von Luxburg. Graph Laplacians and their convergence on random neighborhood graphs. The Journal of Machine Learning Research, 8:1325–1370, 2007.
A. Holm, P. Ranta-aho, M. Sallinen, P. Karjalainen, and K. Müller. Relationship of P300 single-trial responses with reaction time and preceding stimulus sequence. Int. J. Psychophysiol., 2006.
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, 14:166–185, 2001.
M. Kutas, G. McCarthy, and E. Donchin. Augmenting mental chronometry: the P300 as a measure of stimulus evaluation time. Science, 197:792–795, August 1977.
D. Lehmann and W. Skrandies. Spatial analysis of evoked potentials in man - a review. Progr Neurobiol, 23(3):227–250, 1984.
S. Mallat and Z. Zhang. Matching pursuit with time-frequency dictionaries. IEEE Trans. on Signal Processing, 41(12):3397–3414, 1993.
C. Mulert, V. Kirsch, R. Pascual-Marqui, R.W. McCarley, and K.M. Spencer. Long-range synchrony of gamma oscillations and auditory hallucination symptoms in schizophrenia. International Journal of Psychophysiology, 79(1):55–63, January 2011. Special Issue: Correlations between gamma-band oscillations and human behaviour.
J. Polich. Clinical application of the p300 event-related brain potential. Physical Medicine & Rehabilitation Clinics of North America, 15(133), 2004.
R. Quian Quiroga and E. van Luijtelaar. Habituation and sensitization in rat auditory evoked potentials: A single-trial analysis with wavelet denoising. International Journal of Psychophysiology, 43(2):141–153, 2002.
C. Tallon-Baudry, O. Bertrand, C. Delpuech, and J. Pernier. Stimulus specificity of phase-locked and non-phase-locked 40 Hz visual responses in human. J. Neurosci., 16(13):4240–4249, 1996.
F. Vidal, B. Burle, M. Bonnet, J. Grapperon, and T. Hasbroucq. Error negativity on correct trials: a reexamination of available data. Biol. Psychol., 64(3):265–82, 2003.
Acknowledgements
The authors wish to thank Franck Vidal and Boris Burle for useful discussions. This article relates some work published with Alexandre Gramfort, Renaud Keriven and Bruno Torrésani. This work is partially funded by the French ANR project MultiModel.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Clerc, M., Papadopoulo, T., Bénar, C. (2013). Single-Trial Analysis of Bioelectromagnetic Signals: The Quest for Hidden Information. In: Cazals, F., Kornprobst, P. (eds) Modeling in Computational Biology and Biomedicine. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31208-3_7
Download citation
DOI: https://doi.org/10.1007/978-3-642-31208-3_7
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-31207-6
Online ISBN: 978-3-642-31208-3
eBook Packages: Mathematics and StatisticsMathematics and Statistics (R0)