Enhanced Functional Brain Imaging by Using Adaptive Filtering and a Depth Compensation Algorithm in Diffuse Optical Tomography
Reflectance diffuse optical tomography (rDOT) of brain function is limited by its high sensitivity to the superficial tissues (i.e., the scalp and skull) and by its severe decrease in measurement sensitivity with increased depth. Significant interference in rDOT results from spontaneous fluctuations that are embedded in both the superficial tissues and brain, such as arterial pulsation and vasomotion. In this study, first we investigate coherence and phase shift of the spontaneous fluctuations in the resting state, within the superficial tissues and at various depths of the brain, respectively. We demonstrate that the spontaneous fluctuations originating from arterial pulsations (similar to 1 Hz) are spatially global and temporally coherent, while the fluctuations originating from vasomotion (similar to 0.1 Hz) tend to have less coherence with increased depth. Second, adaptive cancellation of spontaneous fluctuations with a frequency-specific strategy is utilized and validated in both resting and activation (evoked by a finger-tapping task) states. Third, improved depth localization of motor activation in reconstructed rDOT images is achieved by combining adaptive cancellation with a depth compensation algorithm that we recently reported.
brain biomedical optical imaging biomedical signal processing