Two-photon Bessel beam tomography for fast volume imaging

Dynamic Volumetric Imaging of Mouse Cerebral Blood Vessels In Vivo with an Ultralong Anti-Diffracting Beam

Volumetric imaging of a mouse brain in vivo with one-photon and two-photon ultralong anti-diffracting (UAD) beam illumination was performed. The three-dimensional (3D) structure of blood vessels in the mouse brain were mapped to a two-dimensional (2D) image. The speed of volumetric imaging was significantly improved due to the long focal length of the UAD beam. Comparing one-photon and two-photon UAD beam volumetric imaging, we found that the imaging depth of two-photon volumetric imaging (80 μm) is better than that of one-photon volumetric imaging (60 μm), and the signal-to-background ratio (SBR) of two-photon volumetric imaging is two times that of one-photon volumetric imaging. Therefore, we used two-photon UAD volumetric imaging to perform dynamic volumetric imaging of mouse brain blood vessels in vivo, and obtained the blood flow velocity.

Tilt-angle stimulated Raman projection tomography

Stimulated Raman projection tomography is a label-free volumetric chemical imaging technology allowing three-dimensional (3D) reconstruction of chemical distribution in a biological sample from the angle-dependent stimulated Raman scattering projection images. However, the projection image acquisition process requires rotating the sample contained in a capillary glass held by a complicated sample rotation stage, limiting the volumetric imaging speed, and inhibiting the study of living samples. Here, we report a tilt-angle stimulated Raman projection tomography (TSPRT) system which acquires angle-dependent projection images by utilizing tilt-angle beams to image the sample from different azimuth angles sequentially. The TSRPT system, which is free of sample rotation, enables rapid scanning of different views by a tailor-designed four-galvo-mirror scanning system. We present the design of the optical system, the theory, and calibration procedure for chemical tomographic reconstruction. 3D vibrational images of polystyrene beads and C. elegans are demonstrated in the C-H vibrational region.

Multiscale photoacoustic tomography of neural activities with GCaMP calcium indicators

SIGNIFICANCE

Optical imaging of responses in fluorescently labeled neurons has progressed significantly in recent years. However, there is still a need to monitor neural activities at divergent spatial scales and at depths beyond the optical diffusion limit.

AIM

To meet these needs, we aim to develop multiscale photoacoustic tomography (PAT) to image neural activities across spatial scales with a genetically encoded calcium indicator GCaMP.

APPROACH

First, using photoacoustic microscopy, we show that depth-resolved GCaMP signals can be monitored in vivo from a fly brain in response to odor stimulation without depth scanning and even with the cuticle intact. In vivo monitoring of GCaMP signals was also demonstrated in mouse brains. Next, using photoacoustic computed tomography, we imaged neural responses of a mouse brain slice at depths beyond the optical diffusion limit.

RESULTS

We provide the first unambiguous demonstration that multiscale PAT can be used to record neural activities in transgenic flies and mice with select neurons expressing GCaMP.

CONCLUSIONS

Our results indicate that the combination of multiscale PAT and fluorescent neural activity indicators provides a methodology for imaging targeted neurons at various scales.

Spectrum modulation-based field of view extension in Airy-beam tomographic microscopy

We reveal the self-accelerating performance of an Airy beam under space-variable spectrum modulation, which corresponds to the extension of the field of view (FOV) and imaging depth in Airy-beam tomographic microscopy (ATM), resulting in the decline of fidelity and resolution of a reconstructed image with an increased FOV and depth of field (DOF). A strategy of spectrum modulation is proposed, and high-fidelity, high-resolution 3D imaging is realized in a 150 µm × 50 µm × 12 µm volume. This study offers a paradigm to improve the quality of reconstructed 3D images based on spectrum modulation for other light fields.

Axial motion estimation and correction for simultaneous multi-plane two-photon calcium imaging

Two-photon imaging in behaving animals is typically accompanied by brain motion. For functional imaging experiments, for example with genetically encoded calcium indicators, such brain motion induces changes in fluorescence intensity. These motion-related intensity changes or motion artifacts can typically not be separated from neural activity-induced signals. While lateral motion, within the focal plane, can be corrected by computationally aligning images, axial motion, out of the focal plane, cannot easily be corrected. Here, we developed an algorithm for axial motion correction for non-ratiometric calcium indicators taking advantage of simultaneous multi-plane imaging. Using temporally multiplexed beams, recording simultaneously from at least two focal planes at different z positions, and recording a z-stack for each beam as a calibration step, the algorithm separates motion-related and neural activity-induced changes in fluorescence intensity. The algorithm is based on a maximum likelihood optimisation approach; it assumes (as a first order approximation) that no distortions of the sample occurs during axial motion and that neural activity increases uniformly along the optical axis in each region of interest. The developed motion correction approach allows axial motion estimation and correction at high frame rates for isolated structures in the imaging volume in vivo, such as sparse expression patterns in the fruit fly brain.

Tissue clearing may alter emission and absorption properties of common fluorophores

In recent years, 3D cell culture has been gaining a more widespread following across many fields of biology. Tissue clearing enables optical analysis of intact 3D samples and investigation of molecular and structural mechanisms by homogenizing the refractive indices of tissues to make them nearly transparent. Here, we describe and quantify that common clearing solutions including benzyl alcohol/benzyl benzoate (BABB), PEG-associated solvent system (PEGASOS), immunolabeling-enabled imaging of solvent-cleared organs (iDISCO), clear, unobstructed brain/body imaging cocktails and computational analysis (CUBIC), and ScaleS4 alter the emission spectra of Alexa Fluor fluorophores and fluorescent dyes. Clearing modifies not only the emitted light intensity but also alters the absorption and emission peaks, at times to several tens of nanometers. The resulting shifts depend on the interplay of solvent, fluorophore, and the presence of cells. For biological applications, this increases the risk for unexpected channel crosstalk, as filter sets are usually not optimized for altered fluorophore emission spectra in clearing solutions. This becomes especially problematic in high throughput/high content campaigns, which often rely on multiband excitation to increase acquisition speed. Consequently, researchers relying on clearing in quantitative multiband excitation experiments should crosscheck their fluorescent signal after clearing in order to inform the proper selection of filter sets and fluorophores for analysis.

Automated long-term two-photon imaging in head-fixed walking Drosophila

BACKGROUND

The brain of Drosophila shows dynamics at multiple timescales, from the millisecond range of fast voltage or calcium transients to functional and structural changes occurring over multiple days. To relate such dynamics to behavior requires monitoring neural circuits across these multiple timescales in behaving animals.

NEW METHOD

Here, we develop a technique for automated long-term two-photon imaging in fruit flies, during wakefulness and extended bouts of immobility, as typically observed during sleep, navigating in virtual reality over up to seven days. The method is enabled by laser surgery, a microrobotic arm for controlling forceps for dissection assistance, an automated feeding robot, as well as volumetric, simultaneous multiplane imaging.

RESULTS

The approach is validated in the fly's head direction system and walking behavior as well a neural activity are recorded. The head direction system tracks the fly's walking direction over multiple days.

COMPARISON WITH EXISTING METHODS

In comparison with previous head-fixed preparations, the time span over which tethered behavior and neural activity can be recorded at the same time is extended from hours to days. Additionally, the reproducibility and ease of dissections are improved compared with manual approaches. Different from previous laser surgery approaches, only continuous wave lasers are required. Lastly, an automated feeding system allows continuously maintaining the fly for several days in the virtual reality setup without user intervention.

CONCLUSIONS

Imaging in behaving flies over multiple timescales will be useful for understanding circadian activity, learning and long-term memory, or sleep.

Axially resolved volumetric two-photon microscopy with an extended field of view using depth localization under mirrored Airy beams

It is a great challenge in two-photon microscopy (2PM) to have a high volumetric imaging speed without sacrificing the spatial and temporal resolution in three dimensions (3D). The structure in 2PM images could be reconstructed with better spatial and temporal resolution by the proper choice of the data processing algorithm. Here, we propose a method to reconstruct 3D volume from 2D projections imaged by mirrored Airy beams. We verified that our approach can achieve high accuracy in 3D localization over a large axial range and is applicable to continuous and dense sample. The effective field of view after reconstruction is expanded. It is a promising technique for rapid volumetric 2PM with axial localization at high resolution.

Zeroth- and first-order long range non-diffracting Gauss-Bessel beams generated by annihilating multiple-charged optical vortices

We demonstrate an alternative approach for generating zeroth- and first-order long range non-diffracting Gauss–Bessel beams (GBBs). Starting from a Gaussian beam, the key point is the creation of a bright ring-shaped beam with a large radius-to-width ratio, which is subsequently Fourier-transformed by a thin lens. The phase profile required for creating zeroth-order GBBs is flat and helical for first-order GBBs with unit topological charge (TC). Both the ring-shaped beam and the required phase profile can be realized by creating highly charged optical vortices by a spatial light modulator and annihilating them by using a second modulator of the same type. The generated long-range GBBs are proven to have negligible transverse evolution up to 2 m and can be regarded as non-diffracting. The influences of the charge state of the TCs, the propagation distance behind the focusing lens, and the GBB profiles on the relative intensities of the peak/rings are discussed. The method is much more efficient as compared to this using annular slits in the back focal plane of lenses. Moreover, at large propagation distances the quality of the generated GBBs significantly surpasses this of GBBs created by low angle axicons. The developed analytical model reproduces the experimental data. The presented method is flexible, easily realizable by using a spatial light modulator, does not require any special optical elements and, thus, is accessible in many laboratories.

Wavefront correction for adaptive optics with reflected light and deep neural networks

Light scattering and aberrations limit optical microscopy in biological tissue, which motivates the development of adaptive optics techniques. Here, we develop a method for wavefront correction in adaptive optics with reflected light and deep neural networks compatible with an epi-detection configuration. Large datasets of sample aberrations which consist of excitation and detection path aberrations as well as the corresponding reflected focus images are generated. These datasets are used for training deep neural networks. After training, these networks can disentangle and independently correct excitation and detection aberrations based on reflected light images recorded from scattering samples. A similar deep learning approach is also demonstrated with scattering guide stars. The predicted aberration corrections are validated using two photon imaging.