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V A Cardenas

Publications and source records attributed to V A Cardenas.

7 recordsLinked to original sources
PubMed2001

Reliability of tissue volumes and their spatial distribution for segmented magnetic resonance images.

Before using MRI tissue segmentation in clinical studies as a dependent variable or as a means to correct functional data for differential tissue contribution, we must first establish the volume reliability and spatial distribution reproducibility of the segmentation method. Although several reports of volume reliability can be found in the literature, there are no articles assessing the reproducibility of the spatial distribution of tissue. In this report, we examine the validity, volume reliability, and spatial distribution reproducibility for our K-means cluster segmentation. Validation was examined by classifying gray matter, white matter, and CSF on images constructed using an MRI simulator and digital brain phantom, with percentage volume differences of less than 5% and spatial distribution overlaps greater than 0.94 (1.0 is perfect). We also segmented repeat scan MRIs from 10 healthy subjects, with intraclass correlation coefficients greater than 0.92 for cortical gray matter, white matter, sulcal CSF, and ventricular CSF. The original scans were also coregistered to the repeat scan of the same subject, and the spatial overlap for each tissue was then computed. Our overlaps ranged from 0.75 to 0.86 for these tissues. Our results support the use of K-means cluster segmentation, and the use of segmented structural MRIs to guide the analysis of functional and other images.

Adult↗
PubMed1997

Human P50 suppression is not affected by variations in wakeful alertness.

The amplitude and suppression of the auditory P50 event-related potential may be useful for studying schizophrenia and drug abuse; however, the low reliability of the P50 suppression measure limits its value for correlation with clinical measures. Reliability can be increased either by improving measurement methods or by reducing or eliminating sources of variance in the recordings. In this paper, the effect on P50 amplitude and suppression of variation in wakeful alertness within an experimental session was examined in 20 normal subjects. The percentage of beta power in the interval immediately prior to the P50 stimuli was used as an index of alertness. P50 amplitudes or C-T ratios were estimated using peak-picking and using the singular value decomposition (SVD) method. No effects of variation of wakeful alertness were observed on any P50 amplitude or suppression measure. Comparing the peak-picking vs SVD estimates replicated our prior results showing markedly higher reliabilities with SVD. We conclude: 1) that variation within an experimental session in wakeful alertness level as indexed by the percentage of beta power does not affect P50 amplitude or suppression, and 2) the SVD method brings the reliability of the C-T ratio up to levels where its usefulness in clinical studies can be examined.

Acoustic Stimulation↗
PubMed1997

A comparison of the repetitive click and conditioning-testing P50 paradigms.

The auditory P50 ERP component has previously been studied either in the repetitive click or the conditioning-testing (C-T) paradigm. For 20 subjects, we compared 4 repetitive click and 4 C-T protocols in a single experimental session with identical recording techniques and with interclick intervals comparable to the C-T intervals. In the C-T protocols, a long interval between click pairs ensured full recovery of P50 to the C click. The analysis of P50 topographies provided strong evidence that the same component was measured in the two paradigms. For both paradigms, P50 amplitude was progressively suppressed as the interclick or C-T interval decreased (P < 0.0001), with parallel interval vs. P50 amplitude regression lines for the two paradigms. There was a strong trend (P = 0.08) for the repetitive click amplitudes to be smaller than T amplitudes for comparable repetitive click and C-T intervals. Equivalently, this strong trend suggests that repetitive click intervals must be longer (by about 300 ms) than the C-T interval to generate equivalent amplitude P50 responses. We conclude that the same component is measured in both paradigms, that P50 amplitude decreases with decreasing interstimulus intervals in both paradigms, and that in normals, for comparable inter-click and C-T intervals, there is greater P50 suppression in the repetitive click paradigm. Finally, we note that the comparison of paradigms within normals does not necessarily apply to clinical samples.

Acoustic Stimulation↗
PubMed1994

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↗
PubMed1993

The reliability of P50 suppression as measured by the conditioning/testing ratio is vastly improved by dipole modeling.

Suppression of auditory P50 evoked potential amplitude to the second of a pair of clicks is potentially important in psychiatric research because it has been shown to be abnormal in both schizophrenics and their relatives. However, its clinical utility using the standard single-channel electroencephalographic (EEG) peak picking methodology is under question because of low test-retest reliability. Dipole Components Modeling of the P50 component was attempted as a method for increasing the reliability of the P50 suppression measure. It was hypothesized that this procedure might work because of pooling of noise from the two responses and because of the use of topographic information. Six replications of a P50 suppression paradigm in 12 subjects were analyzed. Reliability using peak picking was 0.27, and was significantly increased to 0.63 using dipole modeling. Dipole modeling was helpful not only for better modeling the P50 when it was present, but also for deciding that there was no P50 response in one subject.

Acoustic Stimulation↗
PubMedDate not supplied

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↗