Multivariate evoked response detection based on the spectral F-test.

BACKGROUND: Objective response detection techniques, such as magnitude square coherence, component synchrony measure, and the spectral F-test, have been used to automate the detection of evoked responses. The performance of these detectors depends on both the signal-to-noise ratio (SNR) and the length of the electroencephalogram (EEG) signal. NEW METHOD: Recently, multivariate detectors were developed to increase the detection rate even in the case of a low signal-to-noise ratio or of short data records originated from EEG signals. In this context, an extension to the multivariate case of the spectral F-test detector is proposed. RESULTS: The performance of this technique is assessed using Monte Carlo. As an example, EEG data from 12 subjects during photic stimulation is used to demonstrate the usefulness of the proposed detector. COMPARISON WITH EXISTING METHOD(S): The multivariate method showed detection rates consistently higher than those ones when only one signal was used. CONCLUSIONS: It is shown that the response detection in EEG signals with the multivariate technique was statistically significant if two or more EEG derivations were used.

Protein restriction after weaning modifies the calcium kinetics and induces cardiomyocyte contractile dysfunction in rats.

Protein restriction (PR) is associated with cardiovascular diseases. The purpose of this study was to investigate the effects on single ventricular cardiomyocyte contractile function of a short-term PR after weaning. Male Fischer rats that were 28 days old were randomly divided into a control group (CG, n = 16) and a protein-restricted group (PRG, n = 16). After weaning, CG and PRG animals received isocaloric diets containing 15 and 6% protein, respectively, for 35 days. Biometric parameters were then measured, and the hearts were removed for the analysis of contractile function and calcium transient in isolated cardiomyocytes of the left ventricule (LV), and the quantification of calcium and collagen fibers in LV myocardium. PRG animals had lower body weight (BW) and LV weight (LVW), an increased LVW to BW ratio and a higher proportion of collagen fibers than CG animals. PRG animals exhibited reduced tissue levels of calcium, reduced the length, width and volume of cardiomyocytes and their sarcomere length compared to CG animals. Cardiomyocytes from PRG animals had a lower amplitude of shortening, a slower time to the peak of shortening and a longer time to half-relaxation than those from the CG. Cardiomyocytes from PRG animals also presented a lower peak of calcium transient and a longer calcium transient decay time than CG animals. Taken together, the results indicate that short-term PR after weaning induces a marked structural remodeling of the myocardium parenchyma and stroma that coexists with contractile dysfunctions in single LV cardiomyocytes of rats, which is probably associated with pathological changes of the intracellular calcium kinetics, rather than inadequate available amounts of this mineral in cardiac tissue.

A matrix-based algorithm for estimating multiple coherence of a periodic signal and its application to the multichannel EEG during sensory stimulation.

The coherence between the stimulation signal and the electroencephalogram (EEG) has been used in the detection of evoked responses. The detector's performance, however, depends on both the signal-to-noise ratio (SNR) of the responses and the number of data segments (M) used in coherence estimation. In practical situations, when a given SNR occurs, detection can only be improved by increasing M and hence the total data length. This is particularly relevant when monitoring is the objective. In the present study, we propose a matrix-based algorithm for estimating the multiple coherence of the stimulation signal taking into account a set of N EEG channels as a way of increasing the detection rate for a fixed value of M. Monte Carlo simulations suggest that thresholds for such multivariate detector are the same as those for multiple coherence of Gaussian signals and that using more than six signals is not advisable for improving the detection rate with M = 10. The results with EEG from 12 normal subjects during photic stimulation at 10 Hz showed a maximum detection for N greater than 2 in 58% of the subjects with M = 10, and hence suggest that the proposed multivariate detector is valuable in evoked responses applications.

Multi-channel evoked response detection using only phase information.

The phase consistency of contiguous segments of the electroencephalogram (EEG) has been used in the detection of evoked responses to rhythmic stimulation. One of such techniques is the component synchrony measure (CSM), which is often used since the threshold for the detection task is easily obtained based on the estimates of asymptotic sample distribution. In this work we investigated the appropriateness of such thresholds for practical number of segments (M). The performance of CSM was next evaluated by Monte Carlo simulations with different signal-to-noise ratios (SNR) and values of M, and the results, compared with those for the magnitude-squared coherence. A way of improving the detection with CSM was also proposed, by suggesting the estimation taking into account the mean phase angle of a set of N signals. This multivariate detector was evaluated in simulations and an illustration of the technique was also given with the EEG of 14 subjects during photic stimulation. In simulated signals with equal SNR, the detection rate with this multivariate measure increased with N. The application to EEG data lead to similar results in 70% of the subjects, which suggests that improvements might be expected when more signals are available to detect evoked responses in EEG.

Improving the detection of evoked responses to periodic stimulation by using multiple coherence--application to EEG during photic stimulation.

The coherence between the stimulation signal and the electroencephalogram (EEG) has been used in the detection of evoked responses. However the detector's performance depends on both the signal-to-noise ratio (SNR) of the responses and the number of data segments (M) used in coherence estimation. In this work, a technique for detecting evoked responses was developed based on the extension to the multivariate case of this coherence. Thus, instead of using the EEG collected at a unique region, the estimation is proposed using two EEG derivations. As for the univariate case, this multiple coherence is independent of the stimulation signal. In addition, considering equal SNR in both signals, the detection rate with this multiple coherence is always greater than that one using only one signal. This was verified in Monte Carlo simulations, which also showed that a superior performance is still expected in practical situations, when a smaller SNR is found in the second signal. The results with EEG from 12 normal subjects during photic stimulation confirm this better performance. Since the proposed technique allows a higher detection rate without the need of increasing M, it permits evoked responses to be detected faster, which is very useful during monitored surgeries.