Simplifying the detection of optical distortions by machine learning

Adaptive optics has been widely used in biological science to recover high-resolution optical image deep into the tissue,where optical distortion detection with high speed and accuracy is strongly required.Here,we introduce convolutional neural networks,one of the most popular machine learning models,into Shack-Hartmann wavefront sensor(SHWS)to simplify optical distortion detection processes.Without image segmentation or centroid positioning algorithm,the trained network could estimate up to 36th Zernike mode coefficients directly from a full SHWS image within 1.227ms on a personal computer,and achieves prediction accuracy up to 97.4%.The simulation results show that the average root mean squared error in phase residuals of our method is 75.64%lower than that with the modal-based SHWS method.With the high detection accuracy and simplified detection processes,this work has the potential to be applied in wavefront sensor-based adaptive optics for in vivo deep tissue imaging.

旬宜地区延长组长7致密油特征与富集主控因素

利用岩心、测录井、分析化验及试油试采等资料,从岩石学特征、储集性能、流体性质、砂岩分布特征等入手,分析工区内致密油地质特征与富集主控因素。认为工区内延长组长7油层组浊积砂岩发育,属致密储层,储集空间以小孔隙为主;原油性质好,为低密度、低黏度、低凝固点的轻质原油,具有低含硫、可流动性强等特点。同时,长7烃源岩分布广,厚度大,有机质丰度高,类型好,Ro平均为0.78%,已进入成熟阶段,为致密油形成提供了丰富的物质基础;长71和长72亚油层砂岩厚度大、分布广,是致密油富集的关键;断层的发育对致密油富集起破坏作用,良好的保存条件是该区致密油聚集成藏的必要条件。

玉米苞叶正己烷萃取物化学成分研究

利用硅胶柱色谱(CC)和薄层色谱(TLC)对玉米苞叶正己烷提取物的化学成分进行分离和纯化,结果得到3个单体化合物(1,2和3)。经1H NMR,13C NMR,COSY,HMQC,HMBC波谱分析,鉴定化合物1为2-环己醇-13-甲基-24烷酸,化合物2为麦角甾醇,化合物3为β-谷甾醇。初步确定化合物1为新化合物,化合物2和3为首次从该植物中分离得到。

Multidither coherent optical adaptive technique for deep tissue two-photon microscopy

Two-photon microscopy normally suffers from the scattering of the tissue in biological imaging.Multidither coberent optical adaptive technique(COAT)can correct the scattered wavefront in parallel.However,the determination of the corrective phases may not be completely accurate using conventional method,which undermines the performance of this technique.In this paper,we theoretically demonstrate a method that can obtain more accurate corrective phases by determining the phase values from the square root of the fuorescence signal.A numnerical simulation model is established to study the performance of adaptive optics in two-photon micros-copy by combining scalar diffraction theory with vector diffraction theory.The results show that the distortion of the wavefront can be corrected more thoroughly with our method in two-photon imaging.In our simulation,with the scattering from a 450-mn-thick mouse brain tissue,excitation focal spots with higher peak-to background ratio(PBR)and images with higher contrast can be obtained.Hence,further enhancement of the multidither COAT correction performance in two-photon imaging can be expected.

Super-resolution microscopy and its applications in neuroscience

Optical microscopy promises researchers to soe most tiny substances directly.However,the resolution of conventional microscopy is resticted by the diffraction limit.This makes it a challenge to observe subcellular processes happened in nanoscale.The development of super-resolution microscopy provides a solution to this challenge.Here,we briefly review several commonly used super-resolution techniques,explicating their basic principles and applications in biological science,especially in neuroscience.In addition,characteristics and limitations of each techrique are compared to provide a guidance for biologists to choose the most suitable tool.

Deep learning based wavefront sensor for complex wavefront detection in adaptive optical microscopes

The Shack-Hartmann wavefront sensor(SHWS)is an essential tool for wavefront sensing in adaptive optical microscopes.However,the distorted spots induced by the complex wavefront challenge its detection performance.Here,we propose a deep learning based wavefront detection method which combines point spread function image based Zernike coefficient estimation and wavefront stitching.Rather than using the centroid displacements of each micro-lens,this method first estimates the Zernike coefficients of local wavefront distribution over each micro-lens and then stitches the local wavefronts for reconstruction.The proposed method can offer low root mean square wavefront errors and high accuracy for complex wavefront detection,and has potential to be applied in adaptive optical microscopes.

Optical Brain Imaging： A Powerful Tool for Neuroscience

As the control center of organisms, the brain remains little understood due to its complexity. Taking advantage of imaging methods, scientists have found an accessible approach to unraveling the mystery of neuroscience. Among these methods, optical imaging techniques are widely used due to their high molecular specificity and single-molecule sensitivity. Here, we overview several optical imaging techniques in neuroscience of recent years, including brain clearing, the micro-optical sectioning tomography system, and deep tissue imaging.

Contextual Fear Learning and Extinction in the Primary Visual Cortex of Mice

Fear memory contextualization is critical for selecting adaptive behavior to survive.Contextual fear conditioning(CFC)is a classical model for elucidating related underlying neuronal circuits.The primary visual cortex(V1)is the primary cortical region for contextual visual inputs,but its role in CFC is poorly understood.Here,our experiments demonstrated that bilateral inactivation of V1 in mice impaired CFC retrieval,and both CFC learning and extinction increased the turnover rate of axonal boutons in V1.The frequency of neuronal Ca^(2+)activity decreased after CFC learning,while CFC extinction reversed the decrease and raised it to the naïve level.Contrary to control mice,the frequency of neuronal Ca^(2+)activity increased after CFC learning in microglia-depleted mice and was maintained after CFC extinction,indicating that microglial depletion alters CFC learning and the frequency response pattern of extinction-induced Ca^(2+)activity.These findings reveal a critical role of microglia in neocortical information processing in V1,and suggest potential approaches for cellular-based manipulation of acquired fear memory.

Deep tissue super-resolution imaging with adaptive optical two-photon multifocal structured illumination microscopy

Visualization of axons and dendritic spines is crucial in neuroscience research.However,traditional microscopy is limited by diffraction-limited resolution and shallow imaging depth,making it difficult to study neuronal dynamics.Two-photon multifocal structured illumination microscopy(2P-MSIM)provides super-resolution imaging along with a reasonably good penetration,but it is vulnerable to optical aberrations in deep tissues.Herein we present a novel non-inertial scanning 2P-MSIM system incorporated with adaptive optics(AO)which allows for super-resolution imaging with effective aberration correction.Our strategy is designed to correct both laser and fluorescence paths simultaneously using a spatial light modulator and a deformable mirror respectively,providing better results than the individual path corrections.The successful implementation of adaptive optical two-photon multifocal structured illumination microscopy(AO 2P-MSIM)has allowed for the super-resolution imaging of neuronal structures in a mouse brain slice at great depths and dynamic morphological characteristics of zebrafish motoneurons in vivo.