Investigating the effects of opioid drugs on electrocortical activity using wavelet transform

Topographic time-frequency decomposition of the EEG

Frequency-transformed EEG resting data has been widely used to describe normal and abnormal brain functional states as function of the spectral power in different frequency bands. This has yielded a series of clinically relevant findings. However, by transforming the EEG into the frequency domain, the initially excellent time resolution of time-domain EEG is lost. The topographic time-frequency decomposition is a novel computerized EEG analysis method that combines previously available techniques from time-domain spatial EEG analysis and time-frequency decomposition of single-channel time series. It yields a new, physiologically and statistically plausible topographic time-frequency representation of human multichannel EEG. The original EEG is accounted by the coefficients of a large set of user defined EEG like time-series, which are optimized for maximal spatial smoothness and minimal norm. These coefficients are then reduced to a small number of model scalp field configurations, which vary in intensity as a function of time and frequency. The result is thus a small number of EEG field configurations, each with a corresponding time-frequency (Wigner) plot. The method has several advantages: It does not assume that the data is composed of orthogonal elements, it does not assume stationarity, it produces topographical maps and it allows to include user-defined, specific EEG elements, such as spike and wave patterns. After a formal introduction of the method, several examples are given, which include artificial data and multichannel EEG during different physiological and pathological conditions.

Effects of maternal alcohol intake on fractal properties in human fetal breathing dynamics

Fractal methods have been found to be useful in characterizing biomedical signals. The use of fractal estimation requires the estimation of parameter H, which is directly related to the fractal dimension D. Here, we propose a new approach which is a combination of the wavelet transform and fractal estimators to characterize the human fetal breathing signals before and after the intake of two glasses of wine by a mother. This study was performed on 26 fetuses. The variances of the wavelet coefficients were estimated at each scale. The slope of the representation on a logarithmic plot from the scales 5 to 1 was found to be increased after alcohol intake. Our results suggested that fetal breathing rates have a rough structure before the alcohol intake and a smooth structure after alcohol intake.

Real-time spike detection in EEG signals using the wavelet transform and a dedicated digital signal processor card

This paper describes a complete real-time system for EEG signal analysis. Specific software and hardware have been designed to provide biologists with an efficient tool, which allows a complete study of the different states of vigilance as well as the paroxysmal activities. The analysis method which is based on the wavelet transform is first presented and compared to the standard spectral approach. The dedicated digital signal processor card, based on the Motorola 96002 processor chip, that has been designed to support real-time acquisition and real-time processing of EEG signals is then presented. We finally illustrate the proposed method by processing real EEG signals of rats, and show that it opens up new prospects in the domain of EEG-based diagnosis. We propose a new representation, called globalization, that provides a global view and better detection of paroxysmal activities.

Investigating the effect of maternal alcohol intake on human fetal breathing rate using adaptive time-frequency analysis methods

In this study, the matching pursuit (MP) method which is a modified version of the wavelet transform (WT) method was proposed to examine the effects of alcohol on human fetal breathing rates in both time and frequency domains. The matching pursuit method was chosen since the classical Fourier transform may not represent signals which have stationary characteristics and wavelet transform may not represent signals whose Fourier transforms have a narrow frequency support. Our results show that the horizontal structured atoms representing the sinusoidal activity at all frequency ranges disappeared and the vertical structured atoms representing the discontinuous spike type activity increased. In addition, the circular structured atoms at the high frequency range shifted to the low frequencies after the alcohol intake. The results also suggested that the matching pursuit is most suitable for analyzing the fetal breathing rate signals with and without alcohol intake.

The effects of morphine on the relationship between fetal EEG, breathing and blood pressure signals using fast wavelet transform

In this study, we introduce the fast wavelet transform (WT) as a method for investigating the effects of morphine on the electroencephalogram (EEG), respiratory activity and blood pressure in fetal lambs. Morphine was infused intravenously at 25 mg/h. The EEG, respiratory activity and blood pressure signals were analyzed using WT. We performed wavelet decomposition for five sets of parameters D2j where -1 < j < -5. The five series WTs represent the detail signal bandwidths: 1, 16-32 Hz; 2, 8-16 Hz; 3, 4-8 Hz; 4, 2-4 Hz; 5, 1-2 Hz. Before injection of the high-dose morphine, power in the EEG was high in all six frequency bandwidths. The respiratory and blood pressure signals showed common frequency components with respect to time and were coincident with the low-voltage fast activity (LVFA) EEG signal. Respiratory activity was observed during only some of the LVFA periods, and was completely absent during high-voltage slow activity (HVSA) EEG. The respiratory signal showed dominant power in the fourth wavelet band, and less power in the third and fifth bands. The blood pressure signal was also characterized by dominant power in the fourth wavelet band. This power was significantly increased during periods of respiratory activity. There was a strong relationship between fetal EEG, blood pressure and breathing movements. However, the injection of high-dose morphine resulted in a disruption of the normal cyclic pattern between the two EEG states and a significant increase in power in the first wavelet band. In addition, the high-dose drug resulted in a significant increase in the power of respiratory signal in the fourth and fifth wavelet bands, while power was reduced in the third wavelet band. Breathing activity was also continuous after the drug. The high-dose morphine also caused a temporary power shift from the third wavelet band to the fourth wavelet band for the 30-min period after injection of drug. Finally, high-dose morphine completely destroyed the correlation between EEG, breathing and blood pressure signals.

Endogenous opiates: 1995

This article is the eighteenth installment of our annual review of research concerning the opiate system. It includes articles published during 1995 reporting the behavioral effects of the opiate peptides and antagonists, excluding the purely analgesic effects. The specific topics covered this year include stress: tolerance and dependence; eating; drinking; gastrointestinal, renal, and hepatic function; mental illness and mood; learning, memory, and reward; cardiovascular responses; respiration and thermoregulation; seizures and other neurological disorders; electrical-related activity; general activity and locomotion; sex, pregnancy, and development; immunological responses; and other behaviors.

Investigating the relationship between fetus EEG, respiratory, and blood pressure signals during maturation using wavelet transform

In this study, we introduce the fast wavelet transform as a method for characterizing maturational changes in electrocortical activity, respiratory activity, and blood pressure in fetal lambs in early (110-122 days), mid (123-135 days), and late (136-144 days) third trimester (term 145 days). Each recording was 2 hr in duration. Wavelet decomposition was performed for six sets of parameters D2j where 1 < or = j < or = 6. The six series wavelet transforms represent the following signal frequency bands: 1. 16-32 Hz; 2. 8-16 Hz; 3. 4-8 Hz; 4. 2-4 Hz; 5. 1-2 Hz; 6. 0.5-1 Hz. In the early group, power in the electrocephalogram (EEG) was highest in the fourth wavelet band, with relatively low power in the other bands. Increase in gestational age was characterized by increased power in all four wavelet bands. Power in the first wavelet band was significantly increased during low-voltage fast activity (LVFA) in the late group. The respiratory and blood pressure signals showed common frequency components with respect to time and were coincident with the LVFA EEG signal. Respiratory activity was only observed during some of the LVFA periods and was completely absent during high-voltage slow activity (HVSA) EEG. The respiratory signal showed dominant power in the fourth wavelet band, and less power in the third and fifth band. The blood pressure signal was also characterized by dominant power in the fourth wavelet band. This power was significantly increased during periods of respiratory activity. These results suggest a strong relationship between fetal EEG, blood pressure, and breathing movements.