A New Spatiotemporal Filtering Method for Single-Trial Estimation of Correlated ERP Subcomponents

A novel spatiotemporal filtering method for single trial estimation of event-related potential (ERP) subcomponents is proposed here. Unlike some previous works in ERP estimation, the proposed method is able to estimate temporally correlated ERP subcomponents such as P3a and P3b. A new cost function is, therefore, defined which can deflate one of the correlated subcomponents. The method is applied to both simulated and real data and has shown to perform very well even in low signal-to-noise ratio situations. In addition, the method is compared to spatial principal component analysis and its superiority has been confirmed by using simulated signals. The approach can be especially useful in mental fatigue analysis where the relative variability of P300 subcomponents is the key factor in detecting the level of fatigue.

[1]  A. Murata,et al.  Evaluation of mental fatigue in human-computer interaction-analysis using feature parameters extracted from event-related potential , 2001, Proceedings 10th IEEE International Workshop on Robot and Human Interactive Communication. ROMAN 2001 (Cat. No.01TH8591).

[2]  Donald O. Walter,et al.  Mass action in the nervous system , 1975 .

[3]  Saeid Sanei,et al.  Estimation of trial to trial variability of P300 subcomponents by coupled Rao-blackwellised particle filtering , 2009, 2009 IEEE/SP 15th Workshop on Statistical Signal Processing.

[4]  José Carlos Príncipe,et al.  A Spatiotemporal Filtering Methodology for Single-Trial ERP Component Estimation , 2009, IEEE Transactions on Biomedical Engineering.

[5]  Arnaud Delorme,et al.  EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis , 2004, Journal of Neuroscience Methods.

[6]  Joseph Dien,et al.  Evaluation of PCA and ICA of simulated ERPs: Promax vs. infomax rotations , 2007, Human brain mapping.

[7]  Saeid Sanei,et al.  Source Localization of Event-Related Potentials Incorporating Spatial Notch Filters , 2008, IEEE Transactions on Biomedical Engineering.

[8]  Saeid Sanei,et al.  Separation and Localisation of P300 Sources and Their Subcomponents Using Constrained Blind Source Separation , 2007, EURASIP J. Adv. Signal Process..

[9]  J. Daléry,et al.  Alteration of event related potentials in siblings discordant for schizophrenia , 2000, Schizophrenia Research.

[10]  Saeid Sanei,et al.  Separating and tracking ERP subcomponents by constrained particle filtering , 2009, 2009 16th International Conference on Digital Signal Processing.

[11]  Ulrich Hegerl,et al.  Neurochemical Substrates and Neuroanatomical Generators of the Event-Related P300 , 1999, Neuropsychobiology.

[12]  Mingzhou Ding,et al.  Estimation of single-trial multicomponent ERPs: Differentially variable component analysis (dVCA) , 2003, Biological Cybernetics.

[13]  M. Scherg,et al.  Two bilateral sources of the late AEP as identified by a spatio-temporal dipole model. , 1985, Electroencephalography and clinical neurophysiology.

[14]  Joseph Dien,et al.  The ERP PCA Toolkit: An open source program for advanced statistical analysis of event-related potential data , 2010, Journal of Neuroscience Methods.

[15]  J. Polich,et al.  P3a and P3b from typical auditory and visual stimuli , 1999, Clinical Neurophysiology.

[16]  Barak A. Pearlmutter,et al.  Independent Components of Magnetoencephalography: Localization , 2002, Neural Computation.

[17]  Mika P. Tarvainen,et al.  Single-trial dynamical estimation of event-related potentials: a Kalman filter-based approach , 2005, IEEE Transactions on Biomedical Engineering.

[18]  Xue Wang,et al.  Multimodal Effects of Local Context on Target Detection: Evidence from P3b , 2009, Journal of Cognitive Neuroscience.

[19]  S Cerutti,et al.  Analysis of visual evoked potentials through Wiener filtering applied to a small number of sweeps. , 1987, Journal of biomedical engineering.

[20]  Aleksandar Dogandzic,et al.  Estimating evoked dipole responses in unknown spatially correlated noise with EEG/MEG arrays , 2000, IEEE Trans. Signal Process..

[21]  J. Polich.  Updating P300: An integrative theory of P3a and P3b , 2007, Clinical Neurophysiology.

[22]  R. Chapman,et al.  EP Component Identification and Measurement by Principal Components-Analysis , 1995, Brain and Cognition.

[23]  Joseph Dien,et al.  Addressing Misallocation of Variance in Principal Components Analysis of Event-Related Potentials , 2004, Brain Topography.

[24]  M. von Spreckelsen,et al.  Estimation of single-evoked cerebral potentials by means of parametric modeling and Kalman filtering , 1988, IEEE Transactions on Biomedical Engineering.

[25]  Yehoshua Y. Zeevi,et al.  Extraction of a source from multichannel data using sparse decomposition , 2002, Neurocomputing.

[26]  Xue Wang,et al.  Estimating Granger causality after stimulus onset: A cautionary note , 2008, NeuroImage.

[27]  Jian Li,et al.  ASEO: A Method for the Simultaneous Estimation of Single-Trial Event-Related Potentials and Ongoing Brain Activities , 2009, IEEE Transactions on Biomedical Engineering.

[28]  Tzyy-Ping Jung,et al.  Independent Component Analysis of Electroencephalographic Data , 1995, NIPS.

[29]  D. Friedman,et al.  The novelty P3: an event-related brain potential (ERP) sign of the brain's evaluation of novelty , 2001, Neuroscience & Biobehavioral Reviews.