Studies of vascular responses are usually performed on isolated vessels or on single vessels in vivo. This allows for precise measurements of diameter or blood flow. However, dynamical responses of the whole microvascular network are difficult to access experimentally. We suggest to use full-field laser speckle imaging to evaluate vascular responses of the retinal network. Image segmentation and vessel recognition algorithms together with response mapping allow us to analyze diameter changes and blood flow responses in the intact retinal network upon systemic administration of the vasoconstrictor angiotensin II, the vasodilator acetylcholine or on the changing level of anesthesia in in vivo rat preparations.

Vasomotion is spontaneous or induced rhythmic changes in vascular tone or vessel diameter that lead to rhythmic changes in flow. While the vascular research community debates the physiological and pathophysiological consequence of vasomotion, there is a great need for experimental techniques that can address the role and dynamical properties of vasomotion in vivo. We apply laser speckle imaging to study spontaneous and drug induced vasomotion in retinal network of anesthetized rats. The results reveal a wide variety of dynamical patterns. Wavelet-based analysis shows that (i) spontaneous vasomotion occurs in anesthetized animals and (ii) vasomotion can be initiated by systemic administration of the thromboxane analogue U-46619 and the nitric-oxide donor S-nitroso-acetylDL-penicillamine (SNAP). Although these drugs activate different cellular pathways responsible for vasomotion, our approach can track the dynamical changes they cause.

Conducted vasodilation is part of the physiological response to increasing metabolic demand of the tissue. Similar responses can be elicited by focal electrical or chemical stimulation. Some evidence suggests an endothelial pathway for nondecremental transmission of hyperpolarizing pulses. However, the underlying mechanisms are debated. Here, we focus on dynamical aspects of the problem hypothesizing the existence of a bistability-powered mechanism for regenerative pulse transmission along the endothelium. Bistability implies that the cell can have two different stable resting potentials and can switch between those states following an appropriate stimulus. Bistability is possible if the current–voltage curve is N shaped instead of monotonically increasing. Specifically, the presence of an inwardly rectifying potassium current may provide the endothelial cell with such properties. We provide a theoretical analysis as well as numerical simulations of both single- and multiunit bistable systems mimicking endothelial cells to investigate the self-consistence and stability of the proposed mechanism. We find that the individual cell may switch readily between two stable potentials. An array of coupled cells, however, as found in the vascular wall, requires a certain adaptation of the membrane currents after a switch, in order to switch back. Although the formulation is generic, we suggest a combination of specific membrane currents that could underlie the phenomenon.

While the laser speckle imaging (LSI) is a powerful tool for multiple biomedical applications, such as monitoring of the blood°ow, in many cases it can provide additional information when combined with spatio-temporal rhythm analysis. We demonstrate the application of Graphics Processing Units (GPU)-based rhythm analysis for the post processing of LSI data, discuss the relevant structure of GPU-based computations, test the proposed technique on surrogate 3D data, and apply this approach to kidney blood°ow autoregulation. Experiments with surrogate data demonstrate the ability of the method to extract information about oscillation patterns from noisy data, as well as to detect the moving source of the rhythm. The analysis of kidney data allow us to detect and to localize the dynamics arising from autoregulation processes at the level of individual nephrons (tubuloglomerular feedback (TGF) rhythm), as well as to distinguish between the TGF-active and the TGF-silent zones.

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