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Stimulation and imaging of neural cells via photonic nanojets

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Photonics Research 2024年第8期12卷 1604-1609页

作者： HENG LI XIXI CHEN TIANLI WU ZHIYONG GONG JINGHUI GUO XIAOSONG BAI JIAWEI LI YAO ZHANG YUCHAO LI BAOJUN LI Guangdong Provincial Key Laboratory of Nanophotonic Manipulation Institute of NanophotonicsCollege of Physics&Optoelectronic EngineeringJinan UniversityGuangzhou 511443China School of Medicine The Chinese University of Hong KongShenzhen 518172China InnerMedical Co. Ltd.Shenzhen 518055China

Various neuromodulation techniques have been developed to modulate the peak activity of neurons,thereby regulating brain function and alleviating neurological ***,neuronal stimulation and imaging have significantly contributed to the understanding and treatment of these ***,we propose utilizing photonic nanojets for optical stimulation and imaging of neural *** application of resin microspheres as microlenses enhances fluorescence imaging of neural lysosomes,mitochondria,and actin filaments by generating photonic ***,optical tweezers can precisely manipulate the microlenses to locate specific targets within the cell for real-time stimulation and *** focusing capabilities of these microlenses enable subcellular-level spatial precision in stimulation,allowing highly accurate targeting of neural cells while minimizing off-target ***,fluorescent signals during neural cell stimulation can be detected in real-time using these *** proposed method facilitates investigation into intercellular signal transmission among neural cells,providing new insights into the underlying mechanisms of neuronal cell activities at a subcellular level.

关键词： stimulation neural utilizing

Structure-Preserving Recurrent neural Networks for a Class of Birkhoffian Systems

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Journal of Systems Science & Complexity 2024年第2期37卷 441-462页

作者： XIAO Shanshan CHEN Mengyi ZHANG Ruili TANG Yifa LSEC ICMSECAcademy of Mathematics and Systems ScienceChinese Academy of SciencesBeijing 100190China School of Mathematical Sciences University of Chinese Academy of SciencesBeijing 100049China School of Mathematics and Statistics Beijing Jiaotong UniversityBeijing 100044China

In this paper,the authors propose a neural network architecture designed specifically for a class of Birkhoffian systems—The Newtonian *** proposed model utilizes recurrent neural networks(RNNs)and is based on a mathematical framework that ensures the preservation of the Birkhoffian *** authors demonstrate the effectiveness of the proposed model on a variety of problems for which preserving the Birkhoffian structure is important,including the linear damped oscillator,the Van der Pol equation,and a high-dimensional *** with the unstructured baseline models,the Newtonian neural network(NNN)is more data efficient,and exhibits superior generalization ability.

关键词： Birkhoffian system k(z,t)-symplectic neural networks recurrent neural network

Through-polymer,via technology-enabled,flexible,lightweight,and integrated devices for implantable neural probes

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Microsystems & Nanoengineering 2024年第2期10卷 279-291页

作者： Cunkai Zhou Ye Tian Gen Li Yifei Ye Lusha Gao Jiazhi Li Ziwei Liu Haoyang Su Yunxiao Lu Meng Li Zhitao Zhou Xiaoling Wei Lunming Qin Tiger H.Tao Liuyang Sun College of Electronics and Information Engineering Shanghai University of Electric PowerShanghaiChina 2020 X-Lab Shanghai Institute of Microsystem and Information TechnologyChinese Academy of SciencesShanghaiChina School of Graduate Study University of Chinese Academy of SciencesBeijingChina State Key Laboratory of Transducer Technology Shanghai Institute of Microsystem and Information TechnologyChinese Academy of SciencesShanghaiChina Center of Materials Science and Optoelectronics Engineering University of Chinese Academy of SciencesBeijingChina School of Physical Science and Technology ShanghaiTech UniversityShanghaiChina Center for Excellence in Brain Science and Intelligence Technology Chinese Academy of SciencesShanghaiChina Neuroxess Co. Ltd.(Jiangxi)NanchangJiangxiChina Guangdong Institute of Intelligence Science and Technology HengqinZhuhaiGuangdongChina Tianqiao and Chrissy Chen Institute for Translational Research ShanghaiChina

In implantable electrophysiological recording systems,the headstage typically comprises neural probes that interface with brain tissue and integrated circuit chips for signal *** advancements in MEMS and CMOS technology have significantly improved these components,their interconnection still relies on conventional printed circuit boards and sophisticated *** conventional approach adds considerable weight and volume to the package,especially for high channel count *** address this issue,we developed a through-polymer via(TPV)method inspired by the through-silicon via(TSV)technique in advanced three-dimensional *** innovation enables the vertical integration of flexible probes,amplifier chips,and PCBs,realizing a flexible,lightweight,and integrated device(FLID).The total weight of the FLIDis only 25%that of its conventional counterparts relying on adapters,which significantly increased the activity levels of animals wearing the FLIDs to nearly match the levels of control animals without ***,by incorporating a platinum-iridium alloy as the top layer material for electrical contact,the FLID realizes exceptional electrical performance,enabling in vivo measurements of both local field potentials and individual neuron action *** findings showcase the potential of FLIDs in scaling up implantable neural recording systems and mark a significant advancement in the field of neurotechnology.

关键词： alloy neural recording

Screening COVID-19 from chest X-ray images by an optical diffractive neural network with the optimized F number

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Photonics Research 2024年第7期12卷 1410-1426页

作者： JIALONG WANG SHOUYU CHAI WENTING GU BOYI LI XUE JIANG YUNXIANG ZHANG HONGEN LIAO XIN LIU DEAN TA Academy for Engineering and Technology Fudan UniversityShanghai 200433China Center for Biomedical Engineering Fudan UniversityShanghai 200433China Department of Chemistry Fudan UniversityShanghai 200433China Department of Biomedical Engineering School of MedicineTsinghua UniversityBeijing 100084China

The COVID-19 pandemic continues to significantly impact people's lives worldwide, emphasizing the critical need for effective detection methods. Many existing deep learning-based approaches for COVID-19 detection offer high accuracy but demand substantial computing resources, time, and energy. In this study, we introduce an optical diffractive neural network(ODNN-COVID), which is characterized by low power consumption, efficient parallelization, and fast computing speed for COVID-19 detection. In addition, we explore how the physical parameters of ODNN-COVID affect its diagnostic performance. We identify the F number as a key parameter for evaluating the overall detection capabilities. Through an assessment of the connectivity of the diffractive network, we established an optimized range of F number, offering guidance for constructing optical diffractive neural networks. In the numerical simulations, a three-layer system achieves an impressive overall accuracy of 92.64% and 88.89% in binary-and threeclassification diagnostic tasks. For a single-layer system, the simulation accuracy of 84.17% and the experimental accuracy of 80.83% can be obtained with the same configuration for the binary-classification task, and the simulation accuracy is 80.19% and the experimental accuracy is 74.44% for the three-classification task. Both simulations and experiments validate that the proposed optical diffractive neural network serves as a passive optical processor for effective COVID-19 diagnosis, featuring low power consumption, high parallelization, and fast computing capabilities. Furthermore, ODNN-COVID exhibits versatility, making it adaptable to various image analysis and object classification tasks related to medical fields owing to its general architecture.

关键词： neural network offering

Implantable probe with integrated reference electrode for in situ neural signal and calcium ion monitoring

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Bio-Design and Manufacturing 2024年第4期7卷 591-595页

作者： Junyu Xiao Mengfei Xu Longchun Wang Bin Yang Jingquan Liu National Key Laboratory of Advanced Micro and Nano Manufacture Technology Shanghai Jiao Tong UniversityShanghai 200240China Department of Micro/Nano Electronics Shanghai Jiao Tong UniversityShanghai 200240China

Monitoring the electrophysiology activity of neurons and blood calcium signals can enable a better understanding of disease-related neural system ***,currently,in situ calcium ion monitoring tools are scarce and exhibit low integration and limited *** this letter,we propose an implantable probe with an integrated in situ Ag/AgCl reference electrode(ISA/ARE)that can monitor action potential(AP)and Ca^(2+) concentrations.

关键词： neural electrode enable

The neural Mechanism of Knowledge Assembly in the Human Brain Inspires Artificial Intelligence Algorithm

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Neuroscience Bulletin 2024年第2期40卷 280-282页

作者： Xiang Ji Wentao Jiang Xiaoru Zhang Ming Song Shan Yu Tianzi Jiang University of the Chinese Academy of Sciences Beijing 100049China Brainnetome Center Institute of AutomationThe Chinese Academy of SciencesBeijing 100190China Laboratory of Brain Atlas and Brain-inspired Intelligence Institute of AutomationThe Chinese Academy of SciencesBeijing 100190China CAS Center for Excellence in Brain Science and Intelligence Technology The Chinese Academy of SciencesBeijing 100190China Research Center for Augmented Intelligence Zhejiang LabHangzhou 311100China

When new information enters the brain,a human's prior knowledge of the world can change rapidly through a process referred to as"knowledge assembly".Recently,Nelli et *** the neural correlates of knowledge assembly in the human brain using functional ***,inspired by the neural mechanism,the authors developed an artificial neural network algorithm to permit rapid knowledge assembly,improving the flexibility of the system[1].Once again,this research demonstrates that studying how the brain works can lead to better computational algorithms.

关键词： neural knowledge artificial

Degradation-adaptive neural network for jointly single image dehazing and desnowing

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Frontiers of Computer Science 2024年第2期18卷 247-249页

作者： Erkang CHEN Sixiang CHEN Tian YE Yun LIU School of Ocean Information Engineering Jimei UniversityXiamen 361021 China College of Artificial Intelligence Southwest UniversityChongqing 400715 China

1 Introduction In harsh winter scenes,the captured images often suffer from hazeand snowdegradationssimultaneously,which significantly affect the performance of high-level computer vision ***,most existing dehazing methods[1-4]and desnowing methods[5-7]are specialized to address only one type of weather-related degradation,and they struggle to effectively handle multiple types of degradations.

关键词： neural handle computer

Artificial intelligence meets body sense: task-driven neural networks reveal computational principles of the proprioceptive pathway

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Signal Transduction and Targeted Therapy 2024年第8期9卷 3147-3149页

作者： Leonard E.van Dyck Frank Bremmer Katharina Dobs Department of Psychology Justus Liebig University GiessenGiessenGermany Max Planck Institute for Human Cognitive and Brain Sciences LeipzigGermany Center for Mind Brain and BehaviorUniversities of MarburgGiessenand DarmstadtMarburgGermany Department of Neurophysics Philipps-Universitat MarburgMarburgGermany

In a recent study published in Cell,Marin Vargas and Bisi et al.1 present an innovative approach to unravel the computational principles underlying proprioceptive processing in non-human *** findings showcase the utility of task-driven modeling in advancing neuroscience and offer translational potential by providing seminal insights into the goals and mechanisms by which the brain encodes body position and movements.

关键词： networks neural principles

Epigenetic memory of drug exposure history controls neural stem cell quiescence in the adult brain

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neural Regeneration Research 2024年第4期19卷 711-712页

作者： Masakazu Iwamoto Taito Matsuda Department of Stem Cell Biology and Medicine Graduate School of Medical SciencesKyushu UniversityFukuokaJapan

neural stem cells(NSCs)are the source of all neurons and glial cells(astrocytes and oligodendrocytes)in the central nervous *** adult mammalian brain retains NSCs in the subgranular zone of the dentate gyrus in the hippocampus and ventricular subventricular zone lining the lateral ventricle(Olpe and Jessberger,2022).Adult NSCs in rodents are preserved throughout life and continuously produce new neurons that integrate into the pre-existing neuronal network.

关键词： neural integrate continuously