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EEG and cerebral blood flow in newborns during quiet sleep
No full textCerebral blood flow (CBF) alterations in the newborns (NB) can lead to brain damage by adecrease in the supply of oxygen and glucose. Aiming at contributing to an understanding of themechanisms involved, the association between the EEG (right front-temporal derivation) and Dopplervelocimetry of the middle cerebral artery from term NB has been investigated. These signals weresimultaneously collected from 20 NB and then epochs during quiet sleep (Tracé Alternant, TA, andHigh Voltage Slow, HVS) were selected. EEG power in theta band (Pthet, 4-8 Hz), was estimated eachsecond. For CBF, obtained from velocimetry, the average velocity (V) was extracted for each heartcycle. To investigate the association in the time (cross correlation function - CCF) and frequencydomains (magnitude square coherence - MSC) signal processing techniques were developed that candeal with interruptions in the data (missing samples). During TA, the CCF between Pthet and V resulted in a maximum value around -5 s (Pthet leading V) in 85% of the NBs with p? 0.05(significance was tested by Monte Carlo simulations). The maximum of the MSC occurred around 0.10Hz in 92 % of the NB (p? 0.05). These findings indicate association between the neuronal activity and CBF during TA. The high coherence could be interpreted as TA
Estimation of coherence between blood flow and spontaneous EEG activity in neonates
No full textBlood flow to the brain responds to changes in neuronal activity and, thus, metabolic demand. In earlier work, we observed correlation between cerebral blood flow and spontaneous electroencephalogram (EEG) activity in neonates. Using coherence, we now found that during Trace/spl acute/ Alternant EEG activity in quiet sleep of normal term neonates, this correlation is strongest at frequencies around 0.1 Hz, reaching statistical significance (p<0.05) in six of the nine subjects studied (p<0.07 in eight subjects). Due to noise, artifact, and spontaneous changes in the subjects' EEG patterns, the signals investigated included epochs of missing samples. We, therefore, developed a novel algorithm for the estimation of coherence in such data and applied a Monte Carlo (surrogate data) method for its statistical analysis. This process provides a test for the statistical significance of the maximum coherence within a selected frequency band. In addition to permitting further insight into the mechanisms of cerebral blood flow control, these algorithms are potentially of great benefit in a wide range of biomedical applications, where interrupted (gapped) recordings are often a problem
Estimation of coherence between cerebral blood flow velocity and EEG activity in newborn babies
No full textIntroduction: Blood flow to the brain is normally regulated by control mechanisms, whose failure has been linked to cerebral ischaemia and intracranial haemorrhage. We have been investigating this control in neonates using transcranial Doppler measurements of cerebral blood flow velocity (CBFV), and have shown correlation between CBFV and the power of the EEG. The aim of the current work is to identify the frequency range in which the EEG activity is most strongly linked to CBFV, using coherence estimates.Methods: CBFV and EEG were simultaneously recorded in normal neonates. In 12 recordings (from 9 neonates), the normal neonatal EEG pattern of Tracé Alternant was identified. Mean CBFV and the RMS value of the EEG were calculated in one-second intervals. The coherence between the resulting signals was estimated using an algorithm developed for signals with missing samples (excluding signal segments with noise or artefact), followed by Monte Carlo statistical tests of significance.Results: It was found that coherence peaked at approximately 0.1 Hz, with a median value of the coherence-magnitude of 0.57. Coherence was significant in 8 of the 12 records. The RMS value of the EEG also showed a spectral peak at 0.1 Hz, but the mean CBFV generally did not
Coherence between one random and one periodic signal for measuring the strength of responses in the electro-encephalogram during sensory stimulation
No full textCoherence between a pulse train representing periodic stimuli and the EEG has been used in the objective detection of steady-state evoked potentials. This work aimed to quantify the strength of the stimulus responses based on the statistics of coherence estimate between one random and one periodic signal, focusing on the confidence limits and power of significance tests in detecting responses. To detect the responses in 95% of cases, a signal-to-noise ratio of about -7.9 dB was required when using 48 windows (M) in the coherence estimation. The ratio, however, increased to -1.2 dB when M was 12. The results were tested in Monte Carlo simulations and applied to EEGs obtained from 14 subjects during visual stimulation. The method showed differences in the strength of responses at the stimulus frequency and its harmonics, as well as variations between individuals and over cortical regions. In contrast to those from the parietal and temporal regions, results for the occipital region gave confidence limits (with M = 12) that were above zero for all subjects, indicating statistically significant responses. The proposed technique extends the usefulness of coherence as a measure of stimulus responses and allows statistical analysis that could also be applied usefully in a range of other biological signals
A statistical technique for measuring synchronism between cortical regions in the EEG during rhythmic stimulation
Get PDFThe coherence function has been widely applied in quantifying the degree of synchronism between electroencephalogram (EEG) signals obtained from different brain regions. However, when applied to investigating synchronization resulting from rhythmic stimulation, misleading results can arise from the high correlation of background EEG activity. The authors, thus propose a modified measure, which emphasizes the synchronized stimulus responses and reduces the influence of the spontaneous EEG activity. Critical values for this estimator are derived and tested in Monte Carlo simulations. The effectiveness of the method is illustrated on data recorded from 12 young normal subjects during rhythmic photic stimulation
Statistical evoked potential detection with number of degrees of freedom estimated from EEG autocorrelation function
No full textCorrelacion entre el EEG y la velocimetria doppler cerebral durante el sueno quieto de recien nacido
No full textEstimated relation between cerebral blood flow and background electroencephalogram activity signals with missing samples in neonates during quiet sleep
No full textEstimation and significance testing of cross-correlation between cerebral blood flow velocity and background electro-encephalograph activity in signals with missing samples
No full textCross-correlation between cerebral blood flow (CBF) and background EEG activity can indicate the integrity of CBF control under changing metabolic demand. The difficulty of obtaining long, continuous recordings of good quality for both EEG and CBF signals in a clinical setting is overcome, in the present work, by an algorithm that allows the cross-correlation function (CCF) to be estimated when the signals are interrupted by segments of missing data. Methods are also presented to test the statistical significance of the CCF obtained in this way and to estimate the power of this test, both based on Monte Carlo simulations. The techniques are applied to the time-series given by the mean CBF velocity (recorded by transcranial Doppler) and the mean power of the EEG signal, obtained in 1 s intervals from nine sleeping neonates. The peak of the CCF is found to be low (?0.35), but reached statistical significance (p<0.05) in five of the nine subjects. The CCF further indicates a delay of 4–6s between changes in EEG and CBF velocity. The proposed signal-analysis methods prove effective and convenient and can be of wide use in dealing with the common problem of missing samples in biological signals
Is there an association between spontaneous neurological activity and cerebral blood flow in newborns?
No full textSydney, Australi
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