[Another case of West Nile fever in the Netherlands: a man with encephalitis following a trip to Canada]. / Opnieuw West-Nijl-virus in Nederland: een man met encefalitis na een reis in Canada.

Shortly after his return to the Netherlands from a trip to Ontario, a part of Canada where infection with West-Nile virus has been reported, a 69-year-old man became increasingly confused and generally unwell, accompanied by fever. The clinical picture was compatible with viral encephalitis and this was supported by EEG findings and the results of the cerebrospinal-fluid examination. MRI of the brain did not contribute to the diagnosis. The patient was treated with aciclovir because herpes simplex encephalitis was suspected, and he recovered from his illness within a few days. The EEG normalised as well. The most important remaining symptom was diminished short-term memory function. After the patient was discharged, rising antibody titres against West-Nile virus were found in two consecutive sera; there were no antibodies to other encephalitis-causing viruses (such as Q fever virus and St. Louis encephalitis virus). This case report concerns the second imported case of West-Nile fever in the Netherlands and the first one with encephalitis.

Changes in functional coupling between neural networks in the brain during maturation revealed by omega complexity.

To study age-dependent changes in coupling between cortical neural networks we applied a new method (omega complexity) to determine overall coherence of EEGs of 34 subjects ranging in age from 3 months to 16 years. We found that the functional coupling between different brain regions is low at birth and increases significantly in the first two decades of life. We suggest that this coupling depends critically upon the system of associational and callosal fibers which is unmyelinated at birth, and which only finishes myelinization in the second or third decade. Thus age-dependant changes in omega complexity may reflect maturation of brain structures underlying higher cerebral functions. If these results can be replicated, preferably in prospective, cohort rather than transectional type studies, omega complexity might prove to be clinically useful as an objective, quantitative measure of brain maturation.

Investigation of the dynamics underlying periodic complexes in the EEG.

Periodic complexes (PC), occurring lateralised or diffuse, are relatively rare EEG phenomena which reflect acute severe brain disease. The pathophysiology is still incompletely understood. One hypothesis suggested by the alpha rhythm model of Lopes da Silva is that periodic complexes reflect limit cycle dynamics of cortical networks caused by excessive excitatory feedback. We examined this hypothesis by applying a recently developed technique to EEGs displaying periodic complexes and to periodic complexes generated by the model. The technique, non-linear cross prediction, characterises how well a time series can be predicted, and how much amplitude and time asymmetry is present. Amplitude and time asymmetry are indications of non-linearity. In accordance with the model, most EEG channels with PC showed clear evidence of amplitude and time asymmetry, pointing to non-linear dynamics. However, the non-linear predictability of true PC was substantially lower than that of PC generated by the model. Furthermore, no finite value for the correlation dimension could be obtained for the real EEG data, whereas the model time series had a dimension slighter higher than one, consistent with a limit cycle attractor. Thus we can conclude that PC reflect non-linear dynamics, but a limit cycle attractor is too simple an explanation. The possibility of more complex (high dimensional and spatio-temporal) non-linear dynamics should be investigated.

Modeling the temporal fluctuations of the cerebral blood flow velocity waveforms using surrogate data testing.

The objective of this study is to find out which mathematical model best explains the temporal fluctuations of the axial blood flow velocity waveforms in the basal arteries of the brain. Blood flow velocity time series were sampled by transcranial Doppler (TCD) examination of the middle cerebral arteries in 10 healthy volunteers. A recently developed mathematical test (surrogate data analysis) was used to examine whether the spectral Doppler maximum waveform consistent with some prespecified model (null hypothesis). We tested four different null hypothesis. 1. Uncorrelated white noise. 2. Linearly filtered noise. 3. Linearly filtered noise with a static nonlinear amplitude transformation. 4. Noisy nonlinear limit cycle. All null hypotheses except the last one could be rejected. We conclude that the TCD waveforms are best described as nonlinear limit cycle with some percentage of noise, either dynamical and/or observational, which is uncorrelated from one single oscillation to the next. These results are a strong argument to perform nonlinear analysis in future TCD studies in order to obtain a better understanding of the cerebral hemodynamics.

The electroencephalogram during normal third trimester pregnancy and six months postpartum.

In 1942 Gibbs and Reid described a slowing of the electroencephalogram (EEG) at the end of a normal pregnancy. To the best of our knowledge this is the only report that addresses the modification of the EEG in normal pregnancy. We performed a spectral multichannel EEG analysis and revealed no differences during third trimester pregnancy and six months postpartum. Therefore EEG changes seen during pregnancy, which were previously regarded as 'subtle changes of pregnancy', may turn out to be clinically relevant changes which indicate either pre-existing EEG dysfunction or EEG abnormalities in the context of a pregnancy-related disorder.

Rejection of the 'filtered noise' hypothesis to explain the variability of transcranial Doppler signals: a comparison of original TCD data with Gaussian-scaled phase randomized surrogate data sets.

Until the last few years the correlation dimension (D2) or the Lyapunow exponent were the two dominant mathematical methods which were applied to identify possible chaotic behavior in biological systems. Detection of deterministic chaos is important, because it suggests that a relatively simple nonlinear model might explain the data. It was however discovered that these methods could give rise to an erroneous detection of chaos. For this reason a new method was proposed in which the originally measured data set was directly compared with a computer generated 'surrogate' data set with exactly the same linear correlations as the original. The basic idea is then to compute a nonlinear statistic for the original data and for each of the surrogate data sets. In principle any statistic can be used. We used the correlation dimension (D2), which measures the complexity of a time series. In this study we applied this surrogate method to estimate whether the variability of the transcranial Doppler (TCD) waveforms is the result of nonlinearity or not. From 10 healthy volunteers, left middle cerebral artery (MCA) blood flow velocities were measured by TCD examinations. An artifact free epoch of each TCD was used for analysis. From each original data set 50 surrogate data sets were constructed using the Gaussian-scaled phase-randomized Fourier transform. For both the original and the surrogate data sets the D2 was measured. The D2 values of the original TCD waveforms differed significantly from the mean D2 of the surrogate data sets. Therefore the null hypothesis, which stated that the original TCD time series arise from filtered noise, is rejected and nonlinearity is detected. The clinical significance and implications are discussed.

Nonlinear transcranial Doppler analysis demonstrates age-related changes of cerebral hemodynamics.

We studied the age- and gender-related changes in complexity of arterial blood flow by analyzing the maximum velocity waveforms. Data were collected by insonation of the middle cerebral artery blood flow by a 2-MHz transcranial pulsed Doppler system. Following the paradigm of nonlinear dynamical systems or "chaos" theory, complexity is best evaluated by estimating the correlation dimension (D2) and the largest Lyapunov exponent (lambda 1). Forty healthy persons (male/female ratio: 1/1; mean age 48.6 y; range 19-86 y) were studied. No gender-related differences were observed. The age-effect showed a diminishing lambda 1 [df(1, 36) = 5.687; p < 0.022] and an increasing D2 at higher age [df(1, 36) = 4.997; p < 0.032]. The age-related decline of the lambda 1 implies a more prominent periodicity, explained by reduced fluctuations in R-R intervals and an altered gain of the baroreceptor reflex. The increased D2 might be related to more prominent vessel wall oscillations due to the increased vessel wall stiffness at higher age.

The physiological and clinical significance of nonlinear TCD waveform analysis in occlusive cerebrovascular disease.

In order to compare the results of nonlinear analysis of hemodynamically compromised and noncompromised cerebral circulations we measured consecutive transcranial Doppler (TCD) waveforms of fourteen patients with a unilateral or bilateral occlusion of the internal carotid artery. The cerebral vasomotor reactivity (VMR) to acetazolamide in both middle cerebral artery (MCA) territories was established by using TCD. Conventional TCD data and nonlinear TCD analysis of data were compared. Nonlinear analysis of the TCD time series suggested dynamical chaos based on the fractal dimension of the TCD curve and the positive Lyapunov exponents in the compromised and noncompromised MCA territories. In the areas with the compromised circulation the positive Lyapunov exponents were significantly lower compared to the noncompromised side and in some cases with a negative VMR, the Lyapunov exponent was almost zero. The latter is suggestive for periodic behavior of the impaired cerebral circulation instead of the dynamical chaos which is found under normal conditions. The TCD time series of a hemodynamic compromised cerebral territory not only shows phenomena related to a decreased perfusion pressure (such as a 'damped waveform') but also phenomena which are related to a more prominent periodicity. We speculate that conventional and nonlinear TCD analysis could be used to determine the VMR.

Dynamical chaos determines the variability of transcranial Doppler signals.

In order to estimate whether or not the variability of a timeseries of transcranial Doppler (TCD) waveforms is the result of a random or a deterministic process the following study was designed. From eight normal volunteers the middle cerebral artery blood flow velocities were measured for 50 sec and the maximum blood flow velocities (or waveforms) were analysed. From these waveforms socalled attractors were reconstructed and shown in a two dimensional phase portrait. The attractor of the TCD timeseries shows the entire range of states the cardiovascular system can display. The geometric structure of the attractor can be estimated by calculation of the correlation dimension D2. The correlation dimension D2 shows that the time evolution of the TCD timeseries is essentially nonperiodic and can be characterized by low dimensional chaos. It has been shown that the D2 value during hypocapnia has a significant higher value compared to the D2 values during normocapnia. The biological and clinical significance of these observations are outlined.

Abnormal cerebral hemodynamics in pregnancy-related hypertensive encephalopathy.

A patient with an imminent pregnancy-related hypertensive encephalopathy is presented in whom transcranial Doppler ultrasound studies revealed increased middle cerebral artery blood flow velocities before and up to 7 days after cesarean section. These increased velocities are normally caused by cerebral vasospasm and subsequent hypoperfusion in pregnancy-related hypertensive encephalopathy. Additional duplex volume flow studies of the common carotid artery were in favor of cerebral hyperperfusion as a cause of the increased blood flow velocities. The clinical implications of these findings are discussed.