Iterative enhancement of event related potentials through sparsity constraints

In this paper we propose an iterative technique that enhances the average event related potential (ERP) by correcting the delay associated with the ERP in each trial. This correction is done in three steps: in the first step a sparse template function is estimated. In the second step, this template is utilized in estimating the inter-trial ERP delays. The ERPs fromeach trial are time-aligned using the estimated delays. In the third step, a new estimate of the ERP waveform is obtained by averaging these time-aligned signals over the trials. The algorithm iterates through these three steps until convergence. The sparse template is estimated in each iteration through the minimization of a convex objective function which compromises between the fit of the estimated ERP waveform to the template, and the sparsity of the estimated ERP waveform.

[1]  D G Wastell,et al.  Statistical detection of individual evoked responses: an evaluation of Woody's adaptive filter. , 1977, Electroencephalography and clinical neurophysiology.

[2]  A Puce,et al.  P3 latency jitter assessed using 2 techniques. I. Simulated data and surface recordings in normal subjects. , 1994, Electroencephalography and clinical neurophysiology.

[3]  A Pfefferbaum,et al.  Clinical application of the P3 component of event-related potentials. I. Normal aging. , 1984, Electroencephalography and clinical neurophysiology.

[4]  Hannu Tiitinen,et al.  Auditory event-related responses are generated independently of ongoing brain activity , 2005, NeuroImage.

[5]  S. Makeig,et al.  Mining event-related brain dynamics , 2004, Trends in Cognitive Sciences.

[6]  N.V. Thakor,et al.  Adaptive estimation of latency changes in evoked potentials , 1996, IEEE Transactions on Biomedical Engineering.

[7]  Stephen P. Boyd,et al.  Convex Optimization , 2004, Algorithms and Theory of Computation Handbook.

[8]  P. Jaskowski,et al.  Amplitudes and latencies of single-trial ERP's estimated by a maximum-likelihood method , 1999, IEEE Transactions on Biomedical Engineering.

[9]  L. Scharf,et al.  Statistical Signal Processing: Detection, Estimation, and Time Series Analysis , 1991 .

[10]  C. Woody.  Characterization of an adaptive filter for the analysis of variable latency neuroelectric signals , 1967, Medical and biological engineering.

[11]  K.D. Donohue,et al.  Audio signal delay estimation using partial whitening , 2007, Proceedings 2007 IEEE SoutheastCon.

[12]  X. Kong,et al.  Adaptive estimation of latency change in evoked potentials by direct least mean p-norm time-delay estimation , 1999, IEEE Transactions on Biomedical Engineering.