Biomedical subjects

R Biscay

Publications and source records attributed to R Biscay.

12 recordsLinked to original sources

PubMed1995

Modeling the electroencephalogram by means of spatial spline smoothing and temporal autoregression.

A spatial-temporal model for the description of electroencephalographic (EEG) data is introduced that combines smooth reconstruction in the spatial domain and autoregressive representation in the time domain. Its spatial aspect is formulated in a general framework that covers interpolation, smoothing, and regression. Contrary to the multivariate time series models used for EEG analysis up to date, the introduced model provides a smooth spatial reconstruction of the EEG cross-spectrum, keeping the condition of nonnegative definiteness. As an instance of practical importance, the case in which the spatial reconstruction is based on spherical splines is developed in detail. Illustrative examples are presented that show the flexibility of the model to describe both normal and abnormal EEG data.

Electroencephalography↗

PubMed1995

Multiresolution decomposition of non-stationary EEG signals: a preliminary study.

Wavelet representation is a recent development in the analysis of non-stationary signals. Its possibilities for use in the description of time-frequency characteristics of both transients in spontaneous EEG and time-varying rhythms in event related brain activity are explored here. By way of illustration, multiresolution decompositions of a wide variety of EEG transients are carried out in this work, including spike-and-waves, single spikes, sharp waves, blink artifacts, frontal intermittent rhythmic delta activity (FIRDA) and paroxysmal delta activity. Also, the application of the wavelet representation to study related spectra perturbations is illustrated with data from psychophysical experiments on the perception of image motion. The results demonstrate the capabilities of the wavelet transform, as an alternative to the Fourier transform, for the representation and analysis of non-stationary EEG signals.

Artifacts↗

PubMed1995

Measuring the dissimilarity between EEG recordings through a non-linear dynamical system approach.

A new measure of dissimilarity between two EEG segments is proposed. It is derived from the application of the mathematical concept of distance between series of one-step predictions according to the estimated non-linear autoregressive functions. The non-linear autoregressive estimation is performed by non-parametric regression using kernel estimators. The possibility of applying this measure for automatic classification of EEG segments is explored. For this purpose multidimensional scaling and cluster analyses are applied on the basis of the calculated dissimilarity measures. In particular, its application to different EEG segments with delta activity and also with alpha waves reveals high agreement with visual classification by EEG specialists.

Algorithms↗

PubMed1995

Maximum a posteriori estimation of change points in the EEG.

A new approach for EEG segmentation is introduced. This is based on a methodology for optimal segmentation of non-stationary signals derived from the maximum a posteriori estimation principle. It is a model-based, not sequential approach that allows for segmentation at different resolution levels. The features of the methodology are illustrated by its application to EEG recordings containing several types of spectral changes due to normal and pathological variations of spontaneous brain rhythmic activities, as well as physiological artifacts.

Algorithms↗

PubMed1995

EEG predictability: adequacy of non-linear forecasting methods.

The predictive properties of EEG segments were analyzed. The sample included alpha, delta as well as spike and wave EEG activity recordings. Most of these segments are better described with non-linear autoregressive models, and a non-linear forecasting algorithm is routinely required. In terms of their predictive properties, segments can be divided into unpredictable, predictable and very predictable, these three groups being similarly represented among the alpha activity EEG segments. In EEG segments with alpha activity, poor predictability is associated with poor organization of the rhythmic pattern. Concerning dynamic properties, it was found that cyclic skeletons were highly represented among the very predictable segments, which reflect a contribution of the deterministic component of the autoregressive model to the predictability of the segments. Notable contributions of the noise component may explain the properties of unpredictable segments. These results point to a great diversity of predictive patterns among EEG recordings. Other factors besides the existence of chaotic dynamics must be regarded.

Algorithms↗

PubMed1994

Multivariate statistical brain electromagnetic mapping.

Brain Electromagnetic Topography (BET) has attained widespread use. The representation of EEG or MEG parameters as scalp maps (BETm) aids its clinical interpretation. However, some critical issues limit the usefulness of BETm. In particular, the conventional statistical assessment of BETm with respect to normative data is based upon marginal significance probability scales which involve multiple univariate comparisons (one at each recording site). As a consequence, the probability of false positive findings (type I error) is increased above its nominal level. The use of conservative levels avoids this phenomenon but results in a considerable increase of the probability of not detecting real abnormality (type II error). Furthermore, BETm are constructed without taking into consideration the patterns of correlations characteristic of electromagnetic data under normal states of brain functioning. This limits the capability of BETm of representing multivariate aspects of abnormality. This paper introduces some techniques to approach these difficulties. Multivariate Brain Electromagnetic Topographic maps (MBETm) are defined, which retain the attractive features of mapping but also take advantage of multivariate characteristics (in the spatial and frequency domains) to highlight aspects of neuropathology. Moreover, simultaneous significance probability (SSP) scales, valid for both BETm and MBETm, are introduced for the global control of the probability of a type I error. The use of these techniques is illustrated with data from patients with cortical tumours and with epilepsy. ROC analysis shows that in some cases there is a significant improvement in both detection and localization accuracy.

Brain↗

PubMed1994

High resolution quantitative EEG analysis.

High resolution spectral methods are explored as an alternative to broad band spectral parameters (BBSP) in quantitative EEG analysis. In a previous paper (Valdes et al. 1990b) regression equations ("Developmental surfaces") were introduced to characterize the age-frequency distribution of the mean and standard deviation of the log spectral EEG power in a normative sample. These normative surfaces allow the calculation of z transformed spectra for all derivations of the 10/20 system and z maps for each frequency. Clinical material is presented that illustrates how these procedures may pinpoint frequencies of abnormal brain activity and their topographic distribution, avoiding the frequency and spatial "smearing" that may occur using BBSP. The increased diagnostic accuracy of high resolution spectral methods is demonstrated by means of receiver operator characteristic (ROC) curve analysis. Procedures are introduced to avoid type I error inflation due to the use of more variables in this type of procedure.

Adolescent↗

PubMed1994

A global scale factor in brain topography.

In this paper statistical resampling techniques are used to support the presence of an equiangular first principal component in EEG log spectra and therefore the existence of a global scale factor in EEG recordings. the Log transformed spectra from a normal sample (n = 211, age 5-97) were analyzed. To reach this conclusion a method for estimating the scale factor is introduced. It is also shown that this factor remains constant in each individual for all derivations and frequencies and across functional states. The contribution of this scale factor to the overall variance of the normal EEG reaches 42% of the total variance of age corrected data. Part of the variance of the scale factor exhibits age dependency. Scale factor correction of EEG spectra data improves the diagnostic accuracy for detecting pathological EEG spectra from an almost random level (Area under the ROC curve = .6) to .84.

Adolescent↗

PubMed1992

QEEG in a public health system.

For the past decade the Cuban Neuroscience Center has organized on behalf of the Ministry of Public Health of the Republic, a nationwide Program for the introduction of quantitative EEG (qEEG). This Program has involved a) development of standardized equipment for "paperless" EEG, qEEG and brain topography; b) establishment of a network of 21 laboratories of clinical neurophysiology; c) creation of the specialty of clinical neurophysiology which trains physicians from all provinces in both traditional and quantitative electrophysiological methods; d) introduction of standardized protocols for the collection of clinical and electrophysiological information; e) organization of a national normative and neuropsychiatric database; f) establishment of normative regression equations. Among the special issues discussed are: 1) relationship between traditional and quantitative methods; 2) evaluation of the effectiveness of the technology introduced; 3) use of qEEG in the early detection of brain dysfunction.

Adolescent↗

PubMed1992

Frequency domain models of the EEG.

The structure of the normal resting EEG crosspectrum SVV(omega) is analyzed using complex multivariate statistics. Exploratory data analysis with Principal Component Analysis (PCA) is followed by hypothesis testing and computer simulations related to possible neural generators. The SVV(omega) of 211 normal individuals (ages 5 to 97) may be decomposed into two types of processes: the xi process with spatial isotropicity reflecting diffuse, correlated cortical generators with radial symmetry, and processes that seem to be generated by more spatially concentrated, correlated sources. The latter are reflected as spectral peaks such as the process. The eigenvectors of the xi process are the Spherical Harmonic Functions which explains the recurring pattern of maps characteristic of the spatial PCA of qEEG data. A new method for estimating sources in the frequency domain which fits dipoles to the whole crosspectrum is applied to explain the characteristics of the localized sources.

Age Factors↗

PubMed1988

Different functional properties of on and off components in auditory brainstem responses to tone bursts.

Auditory brainstem responses to tone bursts of constant rise and fall time and variable plateau were obtained in 7 normal hearing adults with a vertex to mastoid electrode configuration. In all records, two vertex-positive components (A, B) were present. Peak A is probably an onset response. Peak B latency increased linearly with plateau duration (r = 0.93) and seems to be an off response. White and notched acoustic noise masking had a different effect on the two components. A greater latency shift was observed for peak A than for peak B, thus reducing the interpeak interval in the masked response. When using high-pass noise, as we lowered the cut-off points from 4 to 0.5 kHz, there was also a greater latency increment for peak A than for peak B. These results suggest a more apical cochlear origin for the off response.

Adult↗

PubMedDate not supplied

Brain-stem auditory evoked potentials and brain death.

BAEP records were obtained from 30 brain-dead patients. Three BAEP patterns were observed: (1) no identifiable waves (73.34%), (2) an isolated bilateral wave I (16.66%), and (3) an isolated unilateral wave I (10%). When wave I was present, it was always significantly delayed. Significant augmentation of wave I amplitude was present bilaterally in one case and unilaterally in another. On the other hand, in serial records from 3 cases wave I latency tended to increase progressively until this component disappeared. During the same period, wave I amplitude fluctuations were observed. A significant negative correlation was found for wave I latency with heart rate and body temperature in 1 case. Two facts might explain the progressive delay and disappearance of wave I in brain-dead patients: a progressive hypoxic-ischaemic dysfunction of the cochlea and the eighth nerve plus hypothermia, often present in brain-dead patients. Then the incidence of wave I preservation reported by different authors in single BAEP records from brain-dead patients might depend on the moment at which the evoked potential study was done in relation to the onset of the clinical state. It is suggested that, although BAEPs provide an objective electrophysiological assessment of brain-stem function, essential for BD diagnosis, this technique could be of no value for this purpose when used in isolation.

Adolescent↗