Melanopsin, a tri-stable photopigment found in intrinsically-photosensitive retinal ganglion cells (ipRGCs), drives circadian rhythms and other non-image forming functions in the nervous system. Despite increased understanding of the biomolecular and spectroscopic properties of melanopsin, its multiphoton and ultrafast optical absorption properties remain underexplored. We demonstrate the effects of two-photon absorption of melanopsin using 900-1160 nm optical stimulation. Excitation in this bandwidth causes consistent increases in calcium levels in transfected HEK293T cells. Our results demonstrate the first reported nonlinear optical properties and corresponding functional responses of two-photon excitation of melanopsin in vitro, along with the effects of spectral-phase modulation on activation.
We present Superfast Polarization-sensitive Off-axis Full-field Optical Coherence Microscopy (SPoOF OCM) as a novel all-optical technique for neurophysiology. Both the optical path length and birefringence induced by the millisecond-scale electrical activity of neurons are captured by SPoOF OCM at 4000 frames per second and with a field-of-view of 200×200 µm sq., 1 µm transverse resolution, 4.5 µm axial resolution, and 300 pm phase sensitivity. With an ability to capture responses spanning three orders of magnitude in both space and time, SPoOF OCM meets the exacting needs of a comprehensive neurophysiology tool and overcomes the existing limitations of traditional electrophysiology and fluorescence microscopy.
The electrical activity of neurons is invariably accompanied by a flux of ions and the motion of the cell membrane. This leads to subtle changes in the refractive index and birefringence of the sample. We present Superfast Polarization-sensitive Off-axis Full-field Optical Coherence Microscopy (SPoOF OCM), a novel setup to capture these variations. Using two orthogonal spatial modulations for each polarization state and a high-speed camera that can operate at up to 4000 Hz, we demonstrate the ability of our setup to observe label-free electrical activity in both the short (1-10 ms) and long (50-500 ms) term.
Significance: Recent advances in nonlinear optics in neuroscience have focused on using two ultrafast lasers for activity imaging and optogenetic stimulation. Broadband femtosecond light sources can obviate the need for multiple lasers by spectral separation for chromatically targeted excitation.
Aim: We present a photonic crystal fiber (PCF)-based supercontinuum source for spectrally resolved two-photon (2P) imaging and excitation of GCaMP6s and C1V1-mCherry, respectively.
Approach: A PCF is pumped using a 20-MHz repetition rate femtosecond laser to generate a supercontinuum of light, which is spectrally separated, compressed, and recombined to image GCaMP6s (930 nm excitation) and stimulate the optogenetic protein, C1V1-mCherry (1060 nm excitation). Galvanometric spiral scanning is employed on a single-cell level for multiphoton excitation and high-speed resonant scanning is employed for imaging of calcium activity.
Results: Continuous wave lasers were used to verify functionality of optogenetic activation followed by directed 2P excitation. Results from these experiments demonstrate the utility of a supercontinuum light source for simultaneous, single-cell excitation and calcium imaging.
Conclusions: A PCF-based supercontinuum light source was employed for simultaneous imaging and excitation of calcium dynamics in brain tissue. Pumped PCFs can serve as powerful light sources for imaging and activation of neural activity, and overcome the limited spectra and space associated with multilaser approaches.
All-optical systems for stimulating and imaging neuronal activity have served as powerful tools for understanding the underlying circuitry of the brain. Experiments using these setups, however, tend to choose stimulation locations based solely on what brain regions are of interest, and take for granted that stimulation effects may vary even within localized brain regions. We thus have developed an algorithm for acquiring neuronal activity via calcium imaging data to assess network connectivity. These parameters include the signal rise time, decay time, inter-event intervals, and the timing and amplitude of signal peaks. These parameters are then compared between cell clusters for similarities, and used as a basis for establishing interconnectivity. Additionally, we have incorporated both temporal and spatial correlation functions to assess inter-neuronal connectivity based on these parameters. This data is then run through a genetic algorithm, applying weights to cells with similar parameters to learn which are interconnected in a given field-of-view. For this study, hippocampal neurons extracted from 2 day old transgenic mice (GCaMP6s, Jackson Labs), - cultured for 2 weeks and imaged under single and two-photon conditions. Single-photon imaging was performed under a commercial Zeiss microscope, whereas two-photon imaging was performed with an in-house imaging system. Results demonstrate a strong correlation between these parameters and cellular connectivity, making them noteworthy markers for targeted stimulation. This study demonstrates an efficient method of assessing network connectivity for various imaging techniques, and hence directed targeting for optogenetic stimulation.
By combining optical and genetic methods, optogenetics has become a very important tool in neuroscience research for manipulating neuron activities. The rapid development of novel opsins and fluorescent indicators has introduced a large palette of biochemical probes for optogenetic stimulation and cellular imaging, which makes the all-optical neural circuit excitation and neural activity recording possible. Compared to visible-light illumination, two-photon excitation and imaging avoids the crosstalk from optogenetic probes and calcium sensors, and provides for deeper penetration and higher spatial-temporal resolution for single-cell-level precise manipulation. Two-photon interactions frequently necessitate the use of high-power sources with narrow bandwidth outputs. Although tunable sources, such as the titanium-sapphire laser, offer some degree of flexibility, multiple bulky and expensive lasers are required for simultaneous two-photon optogenetic stimulation and calcium imaging. Here, we propose to use fiber-based supercontinuum generation as a broadband coherent light source for two-photon excitation and imaging. A custom-made photonic crystal fiber is pumped by a Yb:KYW laser (1041 nm, 220 fs, 80 MHz) to generate a femtosecond output with a wide range of wavelengths, 900 - 1170 nm, which covers most of the two-photon excitation wavelengths of the molecules used in optogenetics, e.g. C1V1-2A-mCherry and GCaMP6s in our study. A pulse shaper is utilized to modulate the phases of partial wavelengths to tailor the temporal shape of the femtosecond pulse, which manipulates the absorption of optogenetic probes and provides a unique approach for controllable optogenetic excitation. Video-rate calcium imaging results suggest that spectral-temporal programmable supercontinuum pulses provide a powerful tool for neural network activity research.
Aberrations in an optical system cause a reduction in imaging resolution and poor image contrast, and limit the imaging depth when imaging biological samples. Computational adaptive optics (CAO) provides an inexpensive and simpler alternative to the traditionally used hardware-based adaptive optics (HAO) techniques. In this paper, we present an automated computational aberration correction method for broadband interferometric imaging techniques, e.g. optical coherence tomography (OCT) and optical coherence microscopy (OCM). In the proposed method, the process of aberration correction is modeled as a filtering operation on the aberrant image using a phase filter in the Fourier domain. The phase filter is expressed as a linear combination of Zernike polynomials with unknown coefficients, which are estimated through an iterative optimization scheme based on maximizing an image sharpness metric. The Resilient backpropagation (Rprop) algorithm, which was originally proposed as an alternative to the gradient-descent-based backpropagation algorithm for training the weights in a multilayer feedforward neural network, is employed to optimize the Zernike polynomial coefficients because of its simplicity and the robust performance to the choice of various parameters. Stochastic selection of the number and type of Zernike modes is introduced at each optimization step to explore different trajectories to enable search for multiple optima in the multivariate search space. The method was validated on various tissue samples and shows robust performance for samples with different scattering properties, e.g. a phantom with subresolution particles, an ex vivo rabbit adipose tissue, and an in vivo photoreceptor layer of the human retina.
It is well known that patient-specific ocular aberrations limit imaging resolution in the human retina. Previously,
hardware adaptive optics (HAO) has been employed to measure and correct these aberrations to acquire high-resolution
images of various retinal structures. While the resulting aberration-corrected images are of great clinical importance,
clinical use of HAO has not been widespread due to the cost and complexity of these systems. We present a technique
termed computational adaptive optics (CAO) for aberration correction in the living human retina without the use of
hardware adaptive optics components. In CAO, complex interferometric data acquired using optical coherence
tomography (OCT) is manipulated in post-processing to adjust the phase of the optical wavefront. In this way, the
aberrated wavefront can be corrected. We summarize recent results in this technology for retinal imaging, including
aberration-corrected imaging in multiple retinal layers and practical considerations such as phase stability and image
optimization.
We demonstrate high-resolution imaging of the living human retina by computationally correcting highorder ocular aberrations. These corrections are performed post-acquisition and without the need for a deformable mirror or wavefront sensor that are commonly employed in hardware adaptive optics (HAO) systems. With the introduction of HAO to ophthalmic imaging, high-resolution near diffraction-limited imaging of the living human retina has become possible. The combination of a deformable mirror, wavefront sensor, and supporting hardware/software, though, can more than double the cost of the underlying imaging modality, in addition to significantly increasing the system complexity and sensitivity to misalignment. Optical coherence tomography (OCT) allows 3-D imaging in addition to naturally providing the complex optical field of backscattered light. This is unlike a scanning laser ophthalmoscope which measures only the intensity of the backscattered light. Previously, our group has demonstrated the utility of a technique called computational adaptive optics (CAO) which utilizes the complex field measured with OCT to computationally correct for optical aberrations in a manner similar to HAO. Until now, CAO has been applied to exvivo imaging and invivo skin imaging. Here, we demonstrate invivo imaging of cone photoreceptors using CAO. Additional practical considerations such as imaging speed, and stability are discussed.
High-resolution tomography is of great importance to many areas of biomedical imaging, but with it comes several apparent tradeoffs such as a narrowing depth-of-field and increasing optical aberrations. Overcoming these challenges has attracted many hardware and computational solutions. Hardware solutions, though, can become bulky or expensive and computational approaches can require high computing power or large processing times. This study demonstrates memory efficient implementations of interferometric synthetic aperture microscopy (ISAM) and computational adaptive optics (CAO) – two computational approaches for overcoming the depthof- field limitation and the effect of optical aberrations in optical coherence tomography (OCT). Traditionally requiring lengthy post processing, here we report implementations of ISAM and CAO on a single GPU for real-time in vivo imaging. Real-time, camera-limited ISAM processing enabled reliable acquisition of stable data for in vivo imaging, and CAO processing on the same GPU is shown to quickly correct static aberrations. These algorithmic advances hold the promise for high-resolution volumetric imaging in time-sensitive situations as well as enabling aberrationfree cellular-level volumetric tomography.
We present a set of analytical formula on describing the diffraction field of the three dimensional (3D) triangular-meshbased
model. The advantage of the proposed method is that it can avoid using the numerical algorithm -- Fast Fourier
Transform, which leads to a depth-of-field limitation by the Whittaker-Shannon sampling theorem. We employ the
proposed method to generate the hologram of 3D texture model derived from the real scene or 3D design software. In
order to further increase the computation speed, we have rendered a real scene by employing the GPU platform. Our
homemade GPU algorithm performs hundreds of times faster than those of CPU. As we developed a general phase
adjustment technique for polygon-based algorithm, the holographic reconstructed scenes possess high performance.
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