Simultaneous extraction and localization of dipolar independent components in evoked potentials

EEG stimulus-related responses have been extensively studied to gain insight on the functional behavior of the brain. Traditionally, these responses have been considered as the result of the generation of low-amplitude evoked potentials (EP). When averaged, these low-amplitude potentials come up from the background and can be cleanly observed. Independent component analysis (ICA) is a technique widely used to solve the problem of blind source separation (BSS). When applied to EP, ICA provides a method to obtain activation signals of neural structures responsible for the generation of several components of EP. ICA algorithms may be modified in order to impose some constraints on the independent components (IC) to be extracted or the mixing matrix, resulting in the so-called constrained ICA (cICA). Here, we make use of a cICA approach to get those IC of the EP that can be identified with point-dipolar sources, as well as their position.

[1]  P. Berg,et al.  A fast method for forward computation of multiple-shell spherical head models. , 1994, Electroencephalography and clinical neurophysiology.

[2]  Gene H. Golub,et al.  Matrix computations , 1983 .

[3]  L. Carin,et al.  A new algorithm for independent component analysis with or without constraints , 2002, Sensor Array and Multichannel Signal Processing Workshop Proceedings, 2002.

[4]  Z. Zhang,et al.  A fast method to compute surface potentials generated by dipoles within multilayer anisotropic spheres. , 1995, Physics in medicine and biology.

[5]  L. Zhukov,et al.  Independent component analysis for EEG source localization , 2000, IEEE Engineering in Medicine and Biology Magazine.

[6]  J. Cardoso,et al.  Blind beamforming for non-gaussian signals , 1993 .

[7]  Jean Gotman,et al.  Systematic source estimation of spikes by a combination of independent component analysis and RAP-MUSIC II: Preliminary clinical application , 2002, Clinical Neurophysiology.

[8]  Richard M. Leahy,et al.  Source localization using recursively applied and projected (RAP) MUSIC , 1997 .

[9]  J. Gotman,et al.  Systematic source estimation of spikes by a combination of independent component analysis and RAP-MUSIC I: Principles and simulation study , 2002, Clinical Neurophysiology.

[10]  T. Sejnowski,et al.  Dynamic Brain Sources of Visual Evoked Responses , 2002, Science.

[11]  T. Sejnowski,et al.  Functionally Independent Components of the Late Positive Event-Related Potential during Visual Spatial Attention , 1999, The Journal of Neuroscience.

[12]  Terrence J. Sejnowski,et al.  An Information-Maximization Approach to Blind Separation and Blind Deconvolution , 1995, Neural Computation.

[13]  Aapo Hyvärinen,et al.  Fast and robust fixed-point algorithms for independent component analysis , 1999, IEEE Trans. Neural Networks.