"Renal autoregulation stabilizes renal blood flow to protect the glomerular capillaries and maintain glomerular filtration rates through two mechanisms: tubuloglomerular feedback (TGF) and the myogenic response (MR). It is considered that the feedback mechanisms operate independently in each nephron (the functional unit of the kidney) within a kidney, but renal autoregulation dynamics can be coupled between vascular connected nephrons. It has also been shown that the mechanisms are time-varying and interact with each other. Understanding of the significance of such complex behavior has been limited by absence of techniques capable of monitoring renal flow signals among more than 2 or 3 nephrons simultaneously. The purpose of this thesis was to develop approaches to allow the identification and characterization of spatial and temporal properties of renal autoregulation dynamics. We present evidence that laser speckle perfusion imaging (LSPI) effectively captures renal autoregulation dynamics in perfusion signals across the renal cortex of anaesthetized rats and that spatial heterogeneity of the dynamics is present and can be investigated using LSPI. Next, we present a novel approach to segment LSPI of the renal surface into phase synchronized clusters representing areas with coupled renal autoregulation dynamics. Results are shown for the MR and demonstrate that when a signal is present phase synchronized regions can be identified. We then describe an approach to identify quadratic phase coupling between the TGF and MR mechanisms in time and space. Using this approach we can identify locations across the renal surface where both mechanisms are operating cooperatively. Finally, we show how synchronization between nephrons can be investigated in relation to renal autoregulation effectiveness by comparing phase synchronization estimates from LSPI with renal autoregulation system properties estimated from renal blood flow and blood pressure measurements. Overall, we have developed approaches to 1) capture renal autoregulation dynamics across the renal surface, 2) identify regions with phase synchronized renal autoregulation dynamics, 3) quantify the presence of the TGF-MR interaction across the renal surface, and 4) determine how the above vary over time. The described tools allow for investigations of the significance and mechanisms behind the complex spatial interactions and time-varying properties of renal autoregulation dynamics. "

It is well known now that there exists a coupling between functional brain activity and regional blood flow response in the somatosensory cortex and other cortical areas. Various modalities, including functional magnetic resonance imaging and optical imaging (intrinsic signals as well as fluorescence), have been developed in the past to map functional brain activity. The complexity and fundamental physical constraints of the instruments preclude functional imaging in awake, behaving small animals. This thesis presents the method of Laser Speckle Imaging (LSI) of brain with high spatial and temporal resolution, and potential for imaging awake and behaving animals. The method has the potential to map brain activation with high sensitivity and spatiotemporal resolution without using any exogenous contrast agents. In LSI, scattered laser light with different paths produces a random interference pattern known as speckle, fluctuations of which contain information about the motion of particles in the underlying medium. A post-processing step is needed to extract information out of the speckle images, two of which we introduce in details. Our first method is based on Laser speckle contrast analysis (LASCA), which has been demonstrated as a full-field method for imaging the cerebral blood flow (CBF). However, conventional LASCA is limited to extremely low dynamic range because of the ambient background field, dark current and anomalies in the circuits of CCD camera, which makes it difficult to analyze the spatiotemporal variabilities in CBF. In this study, we propose an enhanced laser speckle contrast analysis (eLASCA) method to improve the dynamic range of LASCA based on monotonic point transformation (MPT). In addition, eLASCA greatly improves the CBF visualization, which is very helpful in demonstrating the details of CBF change. Our second method involves the second order features (SOFs) of the image; they are derived from the cooccurrence matrix that in turn was calculated over the same spatial and temporal window than for the contrast. The image quality metrics - equivalent number of looks, entropy and objective quality – showed superior performance of the SOFs comparing to the contrast analysis. / --