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Intercellular communication mediated by a large number of neuromodulators diversifies physiological actions, yet neuromodulation remains poorly understood despite the recent upsurge of genetically encoded transmitter sensors. Here, we report the development of a versatile genetically encoded sensor-based image analysis program (GESIAP) that utilizes MATLAB-based algorithms to achieve high-throughput, high-resolution processing of sensor-based functional imaging data. GESIAP enables delineation of fundamental properties (e.g., transmitter spatial diffusion extent, quantal size, quantal content, release probability, pool size, and refilling rate at single release sites) of transmission mediated by various transmitters (i.e., monoamines, acetylcholine, neuropeptides, and glutamate) at various cell types (i.e., neurons, astrocytes, and other non-neuronal cells) of various animal species (i.e., mouse, rat, and human). Our analysis appraises a dozen of newly developed transmitter sensors, validates a conserved model of restricted non-volume neuromodulatory synaptic transmission, and accentuates a broad spectrum of presynaptic release properties that variegate neuromodulation.

The amygdala, one of the most studied brain structures, integrates brain-wide heterogeneous inputs and governs multidimensional outputs to control diverse behaviors central to survival, yet how amygdalar input-output neuronal circuits are organized remains unclear. Using a simplified cell-type- and projection-specific retrograde transsynaptic tracing technique, we scrutinized brain-wide afferent inputs of four major output neuronal groups in the amygdalar basolateral complex (BLA) that project to the bed nucleus of the stria terminals (BNST), ventral hippocampus (vHPC), medial prefrontal cortex (mPFC) and nucleus accumbens (NAc), respectively. Brain-wide input-output quantitative analysis unveils that BLA efferent neurons receive a diverse array of afferents with varied input weights and predominant contextual representation. Notably, the afferents received by BNST-, vHPC-, mPFC- and NAc-projecting BLA neurons exhibit virtually identical origins and input weights. These results indicate that the organization of amygdalar BLA input-output neuronal circuits follows the input-dependent and output-independent principles, ideal for integrating brain-wide diverse afferent stimuli to control parallel efferent actions. The data provide the objective basis for improving the virtual reality exposure therapy for anxiety disorders and validate the simplified cell-type- and projection-specific retrograde transsynaptic tracing method.

Optical clearing is a versatile approach to improve imaging quality and depth of optical microscopy by reducing scattered light. However, conventional optical clearing methods are restricted in the efficiency-first applications due to unsatisfied time consumption, irreversible tissue deformation, and fluorescence quenching. Here, we developed an ultrafast optical clearing method (FOCM) with simple protocols and common reagents to overcome these limitations. The results show that FOCM can rapidly clarify 300-µm-thick brain slices within 2 min. Besides, the tissue linear expansion can be well controlled by only a 2.12% increase, meanwhile the fluorescence signals of GFP can be preserved up to 86% even after 11 d. By using FOCM, we successfully built the detailed 3D nerve cells model and showed the connection between neuron, astrocyte, and blood vessel. When applied to 3D imaging analysis, we found that the foot shock and morphine stimulation induced distinct c-fos pattern in the paraventricular nucleus of the hypothalamus (PVH). Therefore, FOCM has the potential to be a widely used sample mounting media for biological optical imaging.

Non-invasive, real-time imaging and deep focus into tissue are in high demand in biomedical research. However, the aberration that is introduced by the refractive index inhomogeneity of biological tissue hinders the way forward. A rapid focusing with sensor-less aberration corrections, based on machine learning, is demonstrated in this paper. The proposed method applies the Convolutional Neural Network (CNN), which can rapidly calculate the low-order aberrations from the point spread function images with Zernike modes after training. The results show that approximately 90 percent correction accuracy can be achieved. The average mean square error of each Zernike coefficient in 200 repetitions is 0.06. Furthermore, the aberration induced by 1-mm-thick phantom samples and 300-µm-thick mouse brain slices can be efficiently compensated through loading a compensation phase on an adaptive element placed at the back-pupil plane. The phase reconstruction requires less than 0.2 s. Therefore, this method offers great potential for in vivo real-time imaging in biological science.

The combination of light sheet fluorescence microscopy (LSFM) and the optical clearing method can achieve fast three-dimensional high-resolution imaging. However, there is an essential contradiction between the field of view (FoV) and spatial resolution. Also, aberration and scattering still exist after tissue clearing, which seriously limits the imaging depth of LSFM. Here we propose a Schwartz modulation method and implement it in LSFM based on a quasi-Bessel beam to enlarge the imaging FoV without sacrificing its spatial resolution. The simulation results show that the FoV of the LSFM is enlarged by a factor of 1.73 compared to the Bessel beam. The capability of extremely fast decay along the optical axis makes Schwartz modulation more tolerant for scattering, indicating potential applications for deep tissue imaging. Also, the capability of sidelobe suppression effectively decreases unnecessary fluorescence excitation and photobleaching.

Two-photon microscopy (2PM) is one of the most widely used tools for in vivo deep tissue imaging. However, the spatial resolution and penetration depth are still limited due to the strong scattering background. Here we demonstrate a two-photon focal modulation microscopy. By utilizing the modulation and demodulation techniques, background rejection capability is enhanced, thus spatial resolution and imaging penetration depth are improved. Compared with 2PM, the transverse resolution is increased by 70%, while the axial resolution is increased to 2-fold. Furthermore, when applied in conventional 2PM mode, it can achieve inertial-free scanning in either transverse or axial direction with in principle unlimited scanning speed. Finally, we applied 2PFMM in thick scattering samples to further examine the imaging performance. The results show that the signal-to-background ratio of 2PFMM can be improved up to five times of 2PM at the depth of 500 μm. Fluorescent imaging in the mouse brain tissue. 3D Thy1-GFP hippocampal neurons imaged by (A) 2PM compared with (B) 2PFMM; (C-H) xy maximum-intensity projection imaged by 2PM compared with 2PFMM. Scale bar 50 μm.