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A common issue in blood-related brain-function measurements, such as optical topography, is that the observed signals are usually corrupted with strong noise that is primarily spontaneous low-frequency oscillations (LFOs) in cerebral hemodynamics, which are difficult to separate from the signals due to functional brain activity because of their common spectral range. We discuss the analysis of information transfer between LFOs around 0.1 Hz in the hemoglobin concentration change (HbCC) in the cerebral cortex, the heart rate (HR), and the mean arterial blood pressure (ABP) to understand the origin of spontaneous LFOs in cerebral hemodynamics. As measures of information transfer, we used transfer entropy (TE) for two-variable system analysis and introduced intrinsic transfer entropy for further analysis of three-variable systems by extending the original TE. Data for analysis were obtained from simultaneous …