Parametric estimation of single morphologically varying evoked brain potentials

We present a new parametric estimator for single Morphologically Varying Evoked Potentials (MVEP's). The estimator can detect changes in specific components within the Evoked Potential (EP) complex, extending current methods which only compensate for global latency and magnitude variations with respect to an averaged evoked response. The performance of the estimator is analyzed analytically for variable component amplitudes, implying also on variable latencies. The analytical qualities are compared to simulated results confirming the estimator's capacity to track morphological changes of simulated signals. Depending on the extent of allowed variations, the estimator enables extracting EP's with signal to noise ratios as low as -15 dB. The performance of the estimator is demonstrated on single movement related brain potentials, recorded during changing experimental conditions and thus expected to yield varying EP's. The results presented show that single MVEP's can be successfully estimated from the noisy background activity, which enables tracking of transient qualities of brain responses throughout an experimental session.