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V A Cardenas

Publications and source records attributed to V A Cardenas.

2 recordsLinked to original sources

Equivalent dipole parameter estimation using simulated annealing.

Equivalent-electrical dipole source modeling of evoked potential signals requires complicated non-linear multivariate optimization. Newton and non-linear simplex optimization methods often converge to a local minimum, and their results are affected by the procedure's starting parameter estimates. This paper describes simulated annealing, a more robust and resistant global optimization method. As an illustrative example, both the simplex and simulated annealing algorithms were used for parameter estimation in modeling wave V of the brain-stem auditory evoked potential (BAEP) using a single decaying sinusoid dipole source. Data for a single subject from 3000 responses to stimuli on each of 2 days were recorded, with modeling performed on 1000 response subaverages. Each estimation problem was run with 5 different sets of starting parameters. Simulated annealing always converged to the global minimum regardless of the starting parameter estimates while simplex often converged to markedly different solutions for different starting parameter estimates. No association was apparent between the simplex's converging to a local minimum and the closeness of the starting estimates to the true parameter values. Implementation of simulated annealing is discussed in terms of cooling schedules and other procedure parameters.

Acoustic Stimulation

A multichannel, model-free method for estimation of event-related potential amplitudes and its comparison with dipole source localization.

We present a multichannel, model-free method for estimation of event-related potential (ERP) amplitude ratios and amplitudes using singular value decomposition (SVD), and compare with the Dipole Components Model (DCM). When the ERPs are generated by a single or multiple dipoles with equal amplitude ratios, the SVD method is superior to DCM in terms of reliable estimation of amplitude and is comparable with DCM for reliable and unbiased estimation of amplitude ratios. We show that dipole model misspecification leads to unbiased amplitude ratios and biased amplitudes when the ERP data sets are (1) generated and fit with a single dipole, or (2) generated by N dipoles with equal amplitude ratios and fit with M < or = N dipoles, because the effect of model misspecification 'cancels' for a ratio. Similarly proof that DCM estimates amplitude ratios more reliably than amplitudes for these cases is given.

Algorithms