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SignificanceTwo-photon microscopy is used routinely forin vivoimaging of neural and vascular structure and function in rodents with a high resolution. Image quality, however, often degrades in deeper portions of the cerebral cortex. Strategies to improve deep imaging are therefore needed. We introduce such a strategy using gates of high repetition rate ultrafast pulse trains to increase signal level.AimWe investigate how signal generation, signal-to-noise ratio (SNR), and signal-to-background ratio (SBR) improve with pulse gating while imagingin vivomouse cerebral vasculature.ApproachAn electro-optic modulator is used with a high-power (6 W) 80 MHz repetition rate ytterbium fiber amplifier to create gates of pulses at a 1 MHz repetition rate. We first measure signal generation from a Texas Red solution in a cuvette to characterize the system with no gating and at a 50%, 25%, and 12.5% duty cycle. We then compare signal generation, SNR, and SBR when imaging Texas Red-labeled vasculature using these conditions.ResultsWe find up to a 6.73-fold increase in fluorescent signal from a cuvette when using a 12.5% duty cycle pulse gating excitation pattern as opposed to a constant 80 MHz pulse train. We verify similar increases forin vivoimaging to that observed in cuvette testing. For deep imaging we find pulse gating to result in a 2.95-fold increase in SNR and a 1.37-fold increase in SBR on average when imaging mouse cortical vasculature at depths ranging from 950 μm to 1050 μm.ConclusionsWe demonstrate that a pulse gating strategy can either be used to limit heating when imaging superficial brain regions or used to increase signal generation in deep regions. These findings should encourage others to adopt similar pulse gating excitation schemes for imaging neural structure through two-photon microscopy.

A potential method for tracking neurovascular disease progression over time in preclinical models is multiphoton fluorescence microscopy (MPM), which can image cerebral vasculature with capillary-level resolution. However, obtaining high-quality, three-dimensional images with a traditional point scanning MPM is time-consuming and limits sample sizes for chronic studies. Here, we present a convolutional neural network-based algorithm for fast upscaling of low-resolution or sparsely sampled images and combine it with a segmentation-less vectorization process for 3D reconstruction and statistical analysis of vascular network structure. In doing so, we also demonstrate that the use of semi-synthetic training data can replace the expensive and arduous process of acquiring low- and high-resolution training pairs without compromising vectorization outcomes, and thus open the possibility of utilizing such approaches for other MPM tasks where collecting training data is challenging. We applied our approach to large field of view images and show that our method generalizes across imaging depths, disease states and other differences in neurovasculature. Our pre-trained models and lightweight architecture can be used to reduce MPM imaging time by up to fourfold without any changes in underlying hardware, thereby enabling deployability across a range of settings.

The inverse correlation time (ICT) is a key quantity in laser speckle contrast imaging (LSCI) measurements. Traditionally, ICT is regarded as a metric of blood flow, such as speed or perfusion. However, we highlight that ICT not only contains important information about blood flow, but also reflects the underlying structure of the vascular network. In the past, ICT has been found to be correlated with vessel diameter. Here, we further report that ICT exhibits a different sensitivity to blood flow depending on vessel orientation. Specifically, ICT is more sensitive to blood flow speed changes in vessels descending from or arising to the tissue surface, compared with those laying parallel to the surface. Those findings shift our understanding of ICT from purely blood flow to a combination of blood flow and vascular network structure. We also develop theories to facilitate the study of vascular network’s impact on ICT.

We demonstrate a simple, low-cost two-photon microscope design with both galvo-galvo and resonant-galvo scanning capabilities. We quantify and compare the signal-to-noise ratios and imaging speeds of the galvo-galvo and resonant-galvo scanning modes when used for murine neurovascular imaging. The two scanning modes perform as expected under shot-noise limited detection and are found to achieve comparable signal-to-noise ratios. Resonant-galvo scanning is capable of reaching desired signal-to-noise ratios using less acquisition time when higher excitation power can be used. Given equal excitation power and total pixel dwell time between the two methods, galvo-galvo scanning outperforms resonant-galvo scanning in image quality when detection deviates from being shot-noise limited.

Here we introduce a fiber amplifier and a diamond Raman laser that output high powers (6.5 W, 1.3 W) at valuable wavelengths (1060 nm, 1250 nm) for two-photon excitation of red-shifted fluorophores. These custom excitation sources are both simple to construct and cost-efficient in comparison to similar custom and commercial alternatives. Furthermore, they operate at a repetition rate (80 MHz) that allows fast image acquisition using resonant scanners. With our system we demonstrate compatibility with fast resonant scanning, the ability to acquire neuronal images, and the capability to image vasculature at deep locations (>1 mm) within the mouse cerebral cortex.

We demonstrate a simple, low-cost two-photon microscope design with both galvo-galvo and resonant-galvo scanning capabilities. We quantify and compare the signal-to-noise ratios and imaging speeds of the galvo-galvo and resonant-galvo scanning modes when used for murine neurovascular imaging. The two scanning modes perform as expected under shot-noise limited detection and are found to achieve comparable signal-to-noise ratios. Resonant-galvo scanning is capable of reaching desired signal-to-noise ratios using less acquisition time when higher excitation power can be used. Given equal excitation power and total pixel dwell time between the two methods, galvo-galvo scanning outperforms resonant-galvo scanning in image quality when detection deviates from being shot-noise limited.

We report the design of a graduating hexagonal ring porous-core Photonic Crystal Fibre. The design was analyzed for various parameters like the effective mode area, confinement loss, material loss, etc. using the COMSOL Multiphysics software and a total loss of 0.11019 dB/cm is observed at an operating frequency of 1 THz. The design was found to exhibit low losses and thus can be used for short-range communication in the Terahertz regime.

We propose a design of a rectangular porous-core Photonic Crystal Fibre (PCF) with a hexagonal-shaped lattice of air holes in the cladding. The design was analysed using COMSOL for different frequencies and different values of the Air Fill Factor (AFF) of the core. We observe that at an operating frequency of 1.2 THz and AFF of the core at 0.88, the fibre exhibits a low total loss of 0.0677 cm−1. We propose this design for the use in low-loss short-range Terahertz data communication.

Here we introduce a fiber amplifier and a diamond Raman laser that output high powers (6.5 W, 1.3 W) at valuable wavelengths (1060 nm, 1250 nm) for two-photon excitation of red-shifted fluorophores. These custom excitation sources are both simple to construct and cost-efficient in comparison to similar custom and commercial alternatives. Furthermore, they operate at a repetition rate (80 MHz) that allows fast image acquisition using resonant scanners. With our system we demonstrate compatibility with fast resonant scanning, the ability to acquire neuronal images, and the capability to image vasculature at deep locations (>1 mm) within the mouse cerebral cortex.

Photonic Crystal Fibers have proved to be an efficient medium for propagation of electromagnetic radiation especially in the Terahertz regime. Located between the infra-red and microwave region, the Terahertz frequency range lies within 0.1 to 1 Terahertz. We report a design of a graduating ring rectangular-core Photonic Crystal Fiber, having background material as Cyclic-Olefin Copolymer (COC), with extremely low confinement loss of 4.9399 × 10−7 dB/cm and material loss of 0.2 cm−1 at 0.22 mm pitch value. Due to the very low loss values, such a structure of the Photonic Crystal Fiber can be used for efficient low-loss data communication.