The use of spatial light modulators to project computer generated holograms is a common strategy for optogenetic stimulation of multiple structures of interest within a three-dimensional volume. A common requirement when addressing multiple targets sparsely distributed in three dimensions is the generation of a points cloud, focusing excitation light in multiple diffraction-limited locations throughout the sample. Calculation of this type of holograms is most commonly performed with either the high-speed, low-performance random superposition algorithm, or the low-speed, high performance Gerchberg–Saxton algorithm. This paper presents a variation of the Gerchberg–Saxton algorithm that, by only performing iterations on a subset of the data, according to compressive sensing principles, is rendered significantly faster while maintaining high quality outputs. The algorithm is presented in high-efficiency and high-uniformity variants. All source code for the method implementation is available as Supplementary Materials and as open-source software. The method was tested computationally against existing algorithms, and the results were confirmed experimentally on a custom setup for in-vivo multiphoton optogenetics. The results clearly show that the proposed method can achieve computational speed performances close to the random superposition algorithm, while retaining the high performance of the Gerchberg–Saxton algorithm, with a minimal hologram quality loss.

In vivo studies of blood circulation pathologies have great medical relevance and need methods for the characterization of time varying flows at high spatial and time resolution in small animal models. We test here the efficacy of the combination of image correlation techniques and single plane illumination microscopy (SPIM) in characterizing time varying flows in vitro and in vivo. As indicated by numerical simulations and by in vitro experiments on straight capillaries, the complex analytical form of the cross-correlation function for SPIM detection can be simplified, in conditions of interest for hemodynamics, to a superposition of Gaussian components, easily amenable to the analysis of variable flows. The possibility to select a wide field of view with a good spatial resolution along the collection optical axis and to compute the cross-correlation between regions of interest at varying distances on a single time stack of images allows one to single out periodic flow components from spurious peaks on the cross-correlation functions and to infer the duration of each flow component. We apply this cross-correlation analysis to the blood flow in Zebrafish embryos at 4 days after fertilization, measuring the average speed and the duration of the systolic and diastolic phases.

Coherent sources of light are easily available to university undergraduate laboratory courses and the demonstration of electromagnetic wave diffraction is typically made with light. However, the construction of arbitrary patterns for the study of light diffraction is particularly demanding due to the small linear scale needed when using sub-micrometer wavelengths, limiting the possibility to thoroughly investigate diffraction experimentally. We describe and test a simple and affordable method to develop arbitrary light diffraction patterns with first year undergraduate or last year high school students. This method is exploited to investigate experimentally the connection between diffraction and the Fourier transform, leading to the development of the concept of spectral analysis of a (2D) signal. We therefore discuss the possibility of building a teaching unit for first year undergraduate or last year high school students on the interdisciplinary topic of spectral analysis starting from an experimental approach to light diffraction.

Microfluidic devices reproducing 3D networks are particularly valuable for nanomedicine applications such as tissue engineering and active cell sorting. There is however a gap in the possibility to measure how the flow evolves in such 3D structures. We show here that it is possible to map 3D flows in complex microchannel networks by combining wide field illumination to image correlation approaches. For this purpose, we have derived the spatiotemporal image correlation analysis of time stacks of single-plane illumination microscopy images. From the detailed analytical and numerical analysis of the resulting model, we developed a fitting method that allows us to measure, besides the in-plane velocity, the out-of-plane velocity component down to v ≅ 65 μm/s. We have applied this method successfully to the 3D reconstruction of flows in microchannel networks with planar and 3D ramifications. These different network architectures have been realized by exploiting the great prototyping ability of a 3D printer, whose precision can reach few tens of micrometers, coupled to poly dimethyl-siloxane soft-printing lithography.

Ramification of blood circulation is relevant in a number of physiological and pathological conditions. The oxygen exchange occurs largely in the capillary bed, and the cancer progression is closely linked to the angiogenesis around the tumor mass. Optical microscopy has made impressive improvements in in vivo imaging and dynamic studies based on correlation analysis of time stacks of images. Here, we develop and test advanced methods that allow mapping the flow fields in branched vessel networks at the resolution of 10 to 20  μm. The methods, based on the application of spatiotemporal image correlation spectroscopy and its extension to cross-correlation analysis, are applied here to the case of early stage embryos of zebrafish.