We introduce the concept of spatial and temporal complexity with emphasis on how its
fractal characterization for 1D, 2D or 3D hemodynamic brain signals can be carried
out. Using high-resolution experimental data sets acquired in animal and human brain
by noninvasive methods - such as laser Doppler flowmetry, laser speckle, near infrared,
or functional magnetic resonance imaging - the spatiotemporal complexity of cerebral
hemodynamics is demonstrated. It is characterized by spontaneous, seemingly random
(that is disorderly) fluctuation of the hemodynamic signals. Fractal analysis, however,
proved that these fluctuations are correlated according to the special order of self-similarity.
The degree of correlation can be assessed quantitatively either in the temporal or
the frequency domain respectively by the Hurst exponent (H) and the spectral index
(beta). The values of H for parenchymal regions of white and gray matter of the rat
brain cortex are distinctly different. In human studies, the values of beta were instrumental
in identifying age-related stiffening of cerebral vasculature and their potential
vulnerability in watershed areas of the brain cortex such as in borderline regions
between frontal and temporal lobes. Biological complexity seems to be present within
a restricted range of H or beta values which may have medical significance because
outlying values can indicate a state of pathology.
