MODELING THE TEMPORAL FLUCTUATIONS OF THE CEREBRAL BLOOD-FLOW VELOCITY WAVE-FORMS USING SURROGATE DATA TESTING

The objective of this study is to find out which mathematical model be st explains the temporal fluctuations of the axial blood Now velocity waveforms in the basal arteries of the brain. Blood Now velocity time series were sampled by transcranial Doppler (TCD) examination of the m iddle cerebral arteries in 10 healthy volunteers. A recently developed mathematical test (surrogate data analysis) was used to examine wheth er the spectral Doppler maximum waveform is consistent with some presp ecified model (null hypothesis). We tested lour different null hypothe ses. 1. Uncorrelated white noise. 2. Linearly filtered noise. 3. Linea rly filtered noise with a static nonlinear amplitude transformation. 3 . Noisy nonlinear limit cycle. All null hypotheses except the last one could be rejected. We conclude that the TCD waveforms are best descri bed as a nonlinear limit cycle with some percentage of noise, either d ynamical and/or observational, which is uncorrelated from one single o scillation 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.