title: Evoked potential enhancement using a neurophysiologically-based model.
abstract: OBJECTIVE
  Single trial evoked potentials (EP) are generally obscured by the much larger spontaneous or background electroencephalogram (EEG). A novel method was developed to enhance single trial EPs. The potential of this approach was explored using actual flash evoked visual EPs.
  
  
  METHODS
  The basic procedure is a variant of the adaptive filtering approach. At the core of our method is a mathematical, but neurophysiologically-realistic, nonlinear model of the cortical structures involved in generating EEG and EP activity. The model parameters are adjusted by a genetic algorithm in such a way that the model output resembles the actually observed pre-stimulus EEG activity. When post-stimulus EEG is passed through the inverse model, enhancement of the single trial EP should, theoretically, occur.
  
  
  RESULTS
  Evidence was found that, in case of visual evoked potentials obtained by flashing light through closed eyelids, alpha activity continues to around 150 ms post-stimulus, at which point a low frequency potential arises, cresting 100 ms later and disappearing after another 100 ms or so. Also, it was found that an individual's response varies considerably from trial to trial.
  
  
  CONCLUSIONS
  The inverse modeling approach presented here is effective at enhancing single trial EP activity. One potential application is to distinguish trials that contain a response from those that do not, which could result in improved ensemble averages.
authors.affiliation: Department of Electrical and Computer Engineering, and Bioengineering Research Center, University of Houston, Houston, USA. bjansen@uh.edu
authors.forename: B H
authors.initials: BH
authors.lastname: Jansen
authors.forename: A B
authors.initials: AB
authors.lastname: Kavaipatti
authors.forename: O
authors.initials: O
authors.lastname: Markusson
mesh_terms: D000328:Adult; D000465:Algorithms; D004569:Electroencephalography / Q000379:methods*; D005074:Evoked Potentials, Visual; D006801:Humans; D008297:Male; D008959:Models, Neurological; D009415:Nerve Net; D017711:Nonlinear Dynamics; D012815:Signal Processing, Computer-Assisted