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Biomedical subjects

J Raz

Publications and source records attributed to J Raz.

18 recordsLinked to original sources

Modeling NMR lineshapes using logspline density functions.

Distortions in the FID and spin echo due to magnetic field inhomogeneity are proved to have a representation as the characteristic function of some probability distribution. In the special case that the distribution is Cauchy, the model reduces to the conventional Lorentzian model. A more general and flexible representation is presented using the Fourier transform of a logspline density. An algorithm for fitting the model is described, the performance of the model and algorithm is investigated in applications to real and simulated data sets, and the logspline approach is compared to a previous Hermitian spline approach and to the Lorentzian model. The logspline model is more parsimonious than the Hermitian spline model, provides a better fit to real data, and is much less biased than the Lorentzian model.

Algorithms

Intra-hemispheric alpha coherence decreases with increasing cognitive impairment in HIV patients.

Inter-hemispheric and intra-hemispheric canonical coherences in the alpha range between EEG signals collected from frontal and posterior groups of electrodes were estimated for 38 HIV positive subjects and 23 uninfected controls. Neuropsychological testing was used to categorize the degree of cognitive impairment evident in each of the subjects. A linear regression analysis provided evidence that intra-hemispheric coherence decreased with increasing cognitive impairment in impaired HIV+ subjects, as measured by a Global Impairment Score (GIS). There was no evidence that cognitively unimpaired HIV+ subjects differed in coherence when compared to uninfected control subjects. Severely impaired HIV+ subjects showed significantly decreased coherence compared to uninfected controls. These data contradict previous work demonstrating increased intra-hemispheric and inter-hemispheric alpha coherence in impaired HIV subjects. In addition, they provide evidence that intra-hemispheric (and possibly inter-hemispheric) disconnection is associated with cognitive impairment in HIV.

Adult

Linear mixed models with heterogeneous within-cluster variances.

This paper describes an extension of linear mixed models to allow for heterogeneous within-cluster variances in the analysis of clustered data. Unbiased estimating equations based on quasilikelihood/pseudolikelihood and method of moments are introduced and are shown to give consistent estimators of the regression coefficients, variance components, and heterogeneity parameter under regularity conditions. Cluster-specific random effects and variances are predicted by the posterior modes. The method is illustrated through an analysis of menstrual diary data and its properties are evaluated in a simulation study.

Adolescent

Frequency domain estimation of covariate effects in multichannel brain evoked potential data.

An evoked potential is the recorded brain electrical response to a stimulus such as an auditory click. In most evoked potential experiments, the response is studied as a function of covariates such as stimulus characteristics and drug states. We propose a frequency domain model of multichannel evoked potential data that includes parameters representing the effects of covariates on the amplitude and latency (time from stimulus presentation) of the response. The variability of the response among scalp electrodes is modeled by the activity of one or more equivalent electrical dipoles. The frequency domain representation allows considerable data reduction, facilitates modeling of the noise, and leads to a simple approximate expression for the latency effects. We describe maximum likelihood estimation of the model parameters and construction of approximate confidence intervals for the covariate effects. We report the results of a simulation study in which we evaluated the bias of the estimators and the coverage rate of the confidence intervals. We also report the results of an application to auditory evoked potentials recorded from five subjects.

Algorithms

Autosomal recessive colobomatous microphthalmia.

Colobomatous microphthalmia was studied in multiple relatives of 5 families. In these families, the disorder was an autosomal recessive trait as opposed to the usual autosomal dominant form of the disorder. A relatively high incidence of this recessive allele is found in the Iranian Jewish community.

Adult

Frequency domain dipole localization: extensions of the method and applications to auditory and visual evoked potentials.

We describe a statistical frequency domain approach to localizing equivalent dipole generators of human brain evoked potentials. The frequency domain representation allows considerable data reduction, constrains the magnitude function of the dipoles to be smooth, and accounts for the statistical properties of the background EEG. A previous paper described a restrictive model in which the dipole orientations were assumed to be fixed over time, and only one dipole was allowed. In this paper, we consider the more general model in which the orientation can vary over time, and which includes multiple dipole generators. The varying orientation model has the practical advantage of being more nearly linear and more flexible than the fixed orientation model, which facilitates convergence of the iterative fitting algorithm. We suggest a measure of goodness-of-fit that compares the likelihood of the dipole model with the likelihoods of saturated and null models. We report the results of fitting the model to recorded auditory and visual evoked potentials. A single dipole with fixed orientation seems to be an adequate model of the auditory midlatency response, while two dipoles with varying orientation are needed to fit the later P200 component. Analysis of the visual P100 response to unilateral stimulation localized a generator in the contralateral occipital cortex, as expected from anatomical considerations. A two-dipole model fit the visual P100 response of bilateral stimulations, and the locations of the two dipoles were similar to the locations obtained by single-dipole fits to the responses to left and right unilateral stimuli.

Computer Simulation

Behr's syndrome and 3-methylglutaconic aciduria.

We examined three patients from two families of Jewish-Iraqi origin who had progressive reduction of visual acuity and childhood onset of bilateral optic nerve atrophy without additional retinal abnormalities. They had neurologic symptoms compatible with Behr's syndrome. Neurologic signs included increased tendon reflexes, a positive Babinski sign, progressive spastic paraplegia, dysarthria, head nodding, and horizontal nystagmus. Neurologic involvement varied between affected siblings. The patients excreted excessive amounts of 3-methylglutaconic acid and 3-methylglutaric acid in their urine. We compared the characteristic ophthalmic features and the spectrum of neurologic signs encountered in this recently delineated autosomal recessive clinical entity with those of previously described entities associated with 3-methylglutaconic aciduria. Patients with early-onset optic atrophy should be examined for neurologic signs and screened for organic aciduria. A detailed ophthalmic examination is important in patients with neurologic abnormalities compatible with Behr's syndrome.

Child

EEG spectra in dyslexic and normal readers during oral and silent reading.

EEGs of extensively screened dyslexics and normal readers were recorded while they read easy and difficult texts silently and orally, and during two other verbal tasks which also differed in overt speaking but had no reading component: narrative speaking and listening to a story. Mid-temporal, central and parietal leads were referenced to linked ears and to Cz. Large differences between tasks and between groups were found. With the linked ears reference, power was higher in all bands in oral reading than in silent reading, with the largest change occurring in the temporal leads. In the theta and low beta bands the difference between oral and silent reading was greater for controls than for dyslexics. These effects were not accounted for by differences in reading speed or in difficulty. Similar results were found in two cohorts of subjects. The difference between groups in theta was found only in the reading tasks. In contrast, the group difference in low beta was also found in the change from listening to speaking. This implies that the oral-silent group difference in theta is related to some aspect of the reading tasks other than the presence or absence of overt speaking, and that the low beta group difference is related to some aspect of overt speaking rather than to reading per se. With the Cz reference no group differences were found. It is suggested that the groups differ in the reading strategies they use, and the degree to which they shift strategy between the silent and oral tasks. We hypothesize that these cognitive differences are reflected in the theta activity from the temporal lobe. While there were many differences between the tasks in alpha power and asymmetry, no group differences involving alpha were found.

Adolescent

Artifactually high coherences result from using spherical spline computation of scalp current density.

Coherence computed from common reference montages inextricably confounds true coherence with power and phase at the recording and reference electrodes. Direct measurement of coherence requires reference-free EEG data, such as data from EEG scalp current densities (SCDs), which estimate the potential gradient perpendicular to the scalp. Perrin et al. (1989) presented a method for computing SCDs by taking the Laplacian of the scalp potential surface generated by spherical spline interpolation. When this method of computing SCDs was applied to EEG data gathered from young adults, very high values were observed for inter-electrode coherences computed from the spherical spline derived SCD data but not from coherences computed from the common reference data. These high coherences prompted further examination of the properties of the spherical spline function and of spherical spline derived SCDs. Simulated data were constructed, and coherence was computed on the simulated data and on the SCDs derived from the spherical spline procedure and from the Hjorth (1980) procedure. The results of those simulations are presented, which demonstrate that a major artifact is introduced by using the spherical spline procedure. This artifact results from the spline weighting matrix used to derive the SCDs and strongly inflates the inter-electrode coherences of the SCD transformed data.

Artifacts

Representation of multi-channel evoked potential data using a dipole component model of intracranial generators: application to the auditory P300.

A number of procedures have been employed to decompose recorded scalp potential wave forms into their hypothesized constituent elements. The shortcomings of the various decomposition methods (principal components analysis, topographic components modeling, inverse dipole localization and spatio-temporal dipole modeling) are reviewed and a new dipole components model, which incorporates the strengths of the topographic components model and the spatio-temporal dipole model, is presented. This model decomposes ERPs into subcomponents reflecting the activity of dipole sources with location and orientation fixed across subjects and with the temporal activity of each dipole modeled as a decaying sinusoid. The requirement that the equivalent dipole generators be the same across subjects and experimental conditions permits analysis of inter-group differences and of the effects of experimental variables. An application of the model to data from a 3-tone auditory target detection task is presented, and equivalent dipole sources of the components of the auditory evoked potential are described. Assumptions inherent in the model, as well as practical obstacles to its widespread implementation, are discussed.

Acoustic Stimulation

Estimation of trial-to-trial variation in evoked potential signals by smoothing across trials.

Averaging single trial evoked potential data to produce an estimate of the underlying signal obscures trial-to-trial variation in the response. We describe a method for estimating slow changes in the evoked potential signal by smoothing the data over trials. We discuss the crucial issue of deciding how much to smooth and suggest that an appropriate smoothing parameter is one that minimizes the estimated mean average square error of the smoothed data. Equations to estimate the mean average square error for a one-dimensional local linear regression smoother are presented. Performance of the method is assessed using simulated evoked potential data with several different models of a changing signal and different values of the signal-to-noise ratio. We find that the method rarely imputes trial-to-trial variation to data sets that have an unchanging signal, while it almost always produces less error than averaging when estimating a varying signal. The ability of the method to reveal signal heterogeneity is hampered by very low signal-to-noise ratios. When applied to real auditory evoked potential data from a sample of elderly subjects, the method indicated a changing signal in 35% of all subjects and in 56% of subjects with signal-to-noise ratios above 0.6. Consistent patterns of variation in the auditory evoked potential were present in this sample.

Aged

Selecting the smoothing parameter for estimation of slowly changing evoked potential signals.

Brain evoked potential (EP) data consist of a true response ("signal") and random background activity ("noise"), which are observed over repeated stimulus presentations ("trials"). A signal that changes slowly from trial to trial can be estimated by smoothing across trials and over time within trials. We present a method for selecting the smoothing parameter by minimizing an estimate of the mean average squared error (MASE). We evaluate the performance of this method using simulated EP data, and apply the method to an example set of real flash evoked potentials.

Analysis of Variance

Analysis of repeated measurements using nonparametric smoothers and randomization tests.

The mixed-model analysis of variance (ANOVA), which is commonly applied to repeated measurements taken over time, depends on specialized assumptions about the error distribution and fails to exploit information contained in the ordering of the data points over time. This paper describes a procedure that overcomes these disadvantages while preserving familiar features of the mixed-model ANOVA. Group profiles are estimated by nonparametric smoothing of observed mean profiles. Group and time main effects, and the group by time interaction effect, are tested using randomization tests. Results of Zerbe (1979, Journal of the American Statistical Association 74, 215-221) are used to construct F-test approximations for the randomization tests of the group and group by time effects. A new approximate F-test for time effect is proposed. A simulation study demonstrates that the approximations perform well and that smoothing increases the power of the tests for time main effect and group by time interaction. The procedure is applied to data on hormone levels in cows.

Analysis of Variance

Common reference coherence data are confounded by power and phase effects.

Coherence analysis of the EEG is used to study the coupling between cortical regions. High coherence between signals recorded at 2 electrodes is interpreted as evidence for neuroanatomic connections between the cortical areas underlying the electrodes. When common reference recordings are used, coherence measures the relationship between 2 time series, each of which is the difference between 2 signals measured at the scalp and is confounded by spectral power and phase at the recording and reference electrodes. Using multi-channel EEG data from 3 subjects, we illustrate the confounding of common reference data coherence computations and demonstrate the extreme effects of power and phase changes on coherence by simulating these changes in the EEG data. Common reference coherence data can be either inflated or deflated as a consequence of activity (i.e., spectral power) at the reference. Phase relationships among the reference and recording time series modulate the power effects on coherence. Both the power and phase effects can vary dramatically across frequencies, having profound and complicated effects on the shape of the coherence function. Based on these considerations, we conclude that common reference coherence data must be interpreted very cautiously and recommend that a new body of EEG coherence data must be gathered using reference-free recording methods before the utility of EEG coherence analysis for understanding brain function can be determined.

Cerebral Cortex

Obesity prognosis: a longitudinal study of children from the age of 6 months to 9 years.

The development of body fatness and leanness is examined in an ongoing prospective nutrition and growth study. Individual skinfold thicknesses, relative weights, weight gains, activity levels, and caloric intakes were examined at seven ages between 6 months and 9 years. Changes in body fatness in this group of children provide evidence that the obese infant usually does not become the obese child. Weight gain in infancy is also a poor predictor of 9-year old obesity. Changes from obese to non-obese or lean are often not linear. There is evidence that impending or actual obesity begins at ages 6 to 9 years with some predictability provided as early as age 2 years for girls, age 3 years for boys.

Anthropometry

Noise and signal power and their effects on evoked potential estimation.

Signal power, noise power and their ratio (SNR) are important variables underlying estimation of evoked potential signals, yet, they are rarely explicitly considered in the design or analysis of EP experiments. A model is developed which relates the reliability of the average evoked potential (AEP) wave form to signal power, noise power, SNR, and the number of single trials included in the average. Measurements taken from auditory and visual EP experiments in elderly subjects show that noise power is highly reliable across experimental conditions and probably reflects global CNS anatomic or physiologic factors. In contrast, signal power and SNR are variable across conditions and sensory modalities, but are stable across replications. Thus signal power reflects CNS processes specific to the experimental paradigm. These results have importance for EP estimation. The expected reliability of the AEP cannot be adequately predicted from estimates of a subject's noise power, or from SNR estimated under different experimental conditions. These findings suggest the need for on-line estimation of SNR during data acquisition to ensure adequate reliability of AEPs.

Aged