Light-field microscopy for fast volumetric brain imaging

3D fluorescence imaging through a scattering medium using the transport of intensity equation and Fresnel ping-pong algorithm

A three-dimensional (3D) fluorescent imaging method through a scattering medium has been presented. The proposed method combines digital phase conjugate reconstruction of the scattered light wave by the transport of intensity equation-based 3D fluorescent imaging to the position of scattering medium and followed phase retrieval method by Fresnel ping-pong algorithm. The effectiveness of the proposed method is experimentally verified by measuring the 3D distribution of fluorescent beads and tobacco-cultured cells through a thin diffuser. Compared to other methods, the reconstructed images show enhancement of the detailed structure of the objects blurred by the diffuser in a wide area. In the simulation, the proposed method is capable of recovering images degraded by scattering in the phase modulation range from 0 to 2π. The capability to identify the depth position is also presented.

High-resolution 3D imaging in light-field microscopy through Stokes matrices and data fusion

The trade-off between the lateral and vertical resolution has long posed challenges to the efficient and widespread application of Fourier light-field microscopy, a highly scalable 3D imaging tool. Although existing methods for resolution enhancement can improve the measurement result to a certain extent, they come with limitations in terms of accuracy and applicable specimen types. To address these problems, this paper proposed a resolution enhancement scheme utilizing data fusion of polarization Stokes vectors and light-field information for Fourier light-field microscopy system. By introducing the surface normal vector information obtained from polarization measurement and integrating it with the light-field 3D point cloud data, 3D reconstruction results accuracy is highly improved in axial direction. Experimental results with a Fourier light-field 3D imaging microscope demonstrated a substantial enhancement of vertical resolution with a depth resolution to depth of field ratio of 0.19%. This represented approximately 44 times the improvement compared to the theoretical ratio before data fusion, enabling the system to access more detailed information with finer measurement accuracy for test samples. This work not only provides a feasible solution for breaking the limitations imposed by traditional light-field microscope hardware configurations but also offers superior 3D measurement approach in a more cost-effective and practical manner.

Light field measurement of specular surfaces by multi-polarization and hybrid modulated illumination

Specular highlights present a challenge in light field microscopy imaging fields, leading to loss of target information and incorrect observation results. Existing highlight elimination methods suffer from computational complexity, false information and applicability. To address these issues, an adaptive multi-polarization illumination scheme is proposed to effectively eliminate highlight reflections and ensure uniform illumination without complex optical setup or mechanical rotation. Using a multi-polarized light source with hybrid modulated illumination, the system achieved combined multi-polarized illumination and physical elimination of specular highlights. This was achieved by exploiting the different light contributions at different polarization angles and by using optimal solution algorithms and precise electronic control. Experimental results show that the proposed adaptive illumination system can efficiently compute control parameters and precisely adjust the light source output in real time, resulting in a significant reduction of specular highlight pixels to less than 0.001% of the original image. In addition, the system ensures uniform illumination of the target area under different illumination configurations, further improving the overall image quality. This study presents a multi-polarization-based adaptive de-highlighting system with potential applications in miniaturization, biological imaging and materials analysis.

Larval zebrafish as a model for studying individual variability in translational neuroscience research

The larval zebrafish is a popular model for translational research into neurological and psychiatric disorders due to its conserved vertebrate brain structures, ease of genetic and experimental manipulation and small size and scalability to large numbers. The possibility of obtaining in vivo whole-brain cellular resolution neural data is contributing important advances into our understanding of neural circuit function and their relation to behavior. Here we argue that the larval zebrafish is ideally poised to push our understanding of how neural circuit function relates to behavior to the next level by including considerations of individual differences. Understanding variability across individuals is particularly relevant for tackling the variable presentations that neuropsychiatric conditions frequently show, and it is equally elemental if we are to achieve personalized medicine in the future. We provide a blueprint for investigating variability by covering examples from humans and other model organisms as well as existing examples from larval zebrafish. We highlight recent studies where variability may be hiding in plain sight and suggest how future studies can take advantage of existing paradigms for further exploring individual variability. We conclude with an outlook on how the field can harness the unique strengths of the zebrafish model to advance this important impending translational question.

Whole-brain imaging of freely-moving zebrafish

One of the holy grails of neuroscience is to record the activity of every neuron in the brain while an animal moves freely and performs complex behavioral tasks. While important steps forward have been taken recently in large-scale neural recording in rodent models, single neuron resolution across the entire mammalian brain remains elusive. In contrast the larval zebrafish offers great promise in this regard. Zebrafish are a vertebrate model with substantial homology to the mammalian brain, but their transparency allows whole-brain recordings of genetically-encoded fluorescent indicators at single-neuron resolution using optical microscopy techniques. Furthermore zebrafish begin to show a complex repertoire of natural behavior from an early age, including hunting small, fast-moving prey using visual cues. Until recently work to address the neural bases of these behaviors mostly relied on assays where the fish was immobilized under the microscope objective, and stimuli such as prey were presented virtually. However significant progress has recently been made in developing brain imaging techniques for zebrafish which are not immobilized. Here we discuss recent advances, focusing particularly on techniques based on light-field microscopy. We also draw attention to several important outstanding issues which remain to be addressed to increase the ecological validity of the results obtained.

Sparse deconvolution for background noise suppression with total variation regularization in light field microscopy

In this Letter, we present a method aiming at background noise removal in the 3D reconstruction of light field microscopy (LFM). Sparsity and Hessian regularization are taken as two prior knowledges to process the original light field image before 3D deconvolution. Due to the noise suppression function of total variation (TV) regularization, we add the TV regularization term to the 3D Richardson-Lucy (RL) deconvolution. By comparing the light field reconstruction results of our method with another state-of-the-art method that is also based on RL deconvolution, the proposed method shows improved performance in terms of removing background noise and detail enhancement. This method will be beneficial to the application of LFM in biological high-quality imaging.

Compact, Hybrid Light-Sheet and Fourier Light-Field Microscopy with a Single Objective for High-Speed Volumetric Imaging In Vivo

Volumetric imaging of biodynamics at high spatiotemporal resolutions in vivo is vital in biomedical studies, in which Fourier light field microscopy (FLFM) is a promising technique. However, the commonly used wide-field illumination strategy in FLFM introduces intense out of depth-of-field background, which not only degrades the image quality, but also introduces reconstruction artifacts. Employing light sheet illumination is an effective way to alleviate the background and reduce photobleaching in light-field microscopy. Unfortunately, the introduction of light-sheet illumination often requires an extra objective and precise alignment, which increases the system complexity. Here, we propose the compact, hybrid light-sheet and FLFM (CLS-FLFM), which uses only a single objective to achieve both light-sheet illumination and Fourier light-field imaging simultaneously. With a micromirror under the objective, we focus the light sheet, which ensures selective-volume-illumination, on the imaging plane of the FLFM to perform volumetric imaging. We demonstrate the superior performance of CLS-FLFM in inhibiting background in both structural and dynamical imaging of larval zebrafish in vivo. We envision that CLS-FLFM finds wide applications in high-speed, background-inhibited volumetric imaging of biodynamics in vivo.