The most studies on functional connectivity have been done by analyzing the brain's hemodynamic response to a stimulation. On the other hand, the low-frequency spontaneous fluctuations in the blood oxygen level dependent (BOLD) signals of functional
MRI have been observed in the resting state. However, the BOLD signals in resting state are significantly corrupted by huge noises arising from cardiac pulsation, respiration, subject motion, scanner, and so forth. Especially, the noise compounds are stronger in the rat brain than in the human brain. To overcome such an artifact, we assumed that fractal behavior in BOLD signals reflects low frequency neural activity, and applied the theorem such that the
wavelet correlation spectrum between long memory processes is scale-invariant over low frequency scales. Here, we report an experiment that shows special correlation patterns not only in correlation of scaling coefficients in very low-frequency band (less than 0.0078Hz) but also in asymptotic
wavelet correlation. In addition, we show the distribution of the
Hurst exponents in the rat brain.
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