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Neural Mechanism Underlying Task-Specific Enhancement of Motor Learning by Concurrent Transcranial Direct Current Stimulation

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Neuroscience Bulletin 2023年第1期39卷 69-82页

作者： Ying Wang Jixian Wang Qing-Fang Zhang Ke-Wei Xiao Liang Wang Qing-Ping Yu Qing Xie Mu-Ming Poo yunqing wen Institute of Neuroscience State Key Laboratory of NeuroscienceKey Laboratory of Primate NeurobiologyCenter for Excellence in Brain Science and Intelligence TechnologyChinese Academy of SciencesShanghai200031China University of Chinese Academy of Sciences Beijing100049China School of Life Science and Technology ShanghaiTech UniversityShanghai201210China Department of Rehabilitation Medicine Ruijin HospitalShanghai Jiao Tong University School of MedicineShanghai200025China Shanghai Center for Brain Science and Brain-Inspired Intelligence Technology Lingang LaboratoryShanghai201210China

The optimal protocol for neuromodulation by transcranial direct current stimulation(tDCS)remains *** the rotarod paradigm,we found that mouse motor learning was enhanced by anodal tDCS(3.2 mA/cm^(2))during but not before or after the performance of a ***-task experiments showed that motor learning enhancement was specific to the task accompanied by anodal *** using a mouse model of stroke induced by middle cerebral artery occlusion showed that concurrent anodal tDCS restored motor learning capability in a task-specific *** in vivo Ca^(2+)imaging further showed that anodal tDCS elevated and cathodal tDCS suppressed neuronal activity in the primary motor cortex(M1).Anodal tDCS specifically promoted the activity of task-related M1 neurons during task performance,suggesting that elevated Hebbian synaptic potentiation in task-activated circuits accounts for the motor learning ***,application of tDCS concurrent with the targeted behavioral dysfunction could be an effective approach to treating brain disorders.

关键词： Motor learning tDCS effect Neural mechanism of tDCS Neuronal excitability Stroke model mouse

A Virtual Reality Platform for Context-Dependent Cognitive Research in

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Neuroscience Bulletin 2023年第5期39卷 717-730页

作者： Xue-Tong Qu Jin-Ni Wu yunqing wen Long Che Shi-Lei Lv Li Liu Li-Jie Zhan Tian-Yi Liu Hua He Yu Liu Chun Xu Institute of Neuroscience State Key Laboratory of NeuroscienceCenter for Excellence in Brain Science and Intelligence TechnologyChinese Academy of SciencesShanghai 200031China University of the Chinese Academy of Sciences Beijing 100049China Shanghai Center for Brain Science and Brain-Inspired Intelligence Technology Shanghai 201210China Institute of Automation Chinese Academy of SciencesBeijing 100190China Department of Neurosurgery Third Affiliated Hospital of Navy Military Medical UniversityShanghai 200438China

Animal survival necessitates adaptive behav-iors in volatile environmental *** reality(VR)technology is instrumental to study the neural mechanisms underlying behaviors modulated by environmental con-text by simulating the real world with maximized control of contextual *** current VR tools for rodents have limited flexibility and performance(e.g.,frame rate)for context-dependent cognitive ***,we describe a high-performance VR platform with which to study con-textual behaviors immersed in editable virtual *** platform was assembled from modular hardware and custom-written software with flexibility and *** this platform,we trained mice to perform context-dependent cognitive tasks with rules ranging from discrim-ination to delayed-sample-to-match while recording from thousands of hippocampal place *** precise manipula-tions of context elements,we found that the context recogni-tion was intact with partial context elements,but impaired by exchanges of context ***,our work establishes a configurable VR platform with which to investigate context-dependent cognition with large-scale neural recording.

关键词： Virtual reality Spatial context Contextual behavior Hippocampus Place cell-Learning and memory Ca^(2+)imaging

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语义网虚拟本体构建

东南大学学报（自然科学版） 2015年第4期45卷 652-656页

作者：张祥李星温韵清沈凯郝敬坤东南大学计算机科学与工程学院南京211189 东南大学软件学院南京211189

针对缺乏良好组织的本体难以被重用的问题,提出了对本体中术语进行语义重组的方法.该方法首先从本体文档中抽取类之间的关系,建立类关系图,进而对不同类型的关系赋以权重.然后将多本体中语义高度相关的术语进行组合,对语义相关度低的术... 详细信息

针对缺乏良好组织的本体难以被重用的问题,提出了对本体中术语进行语义重组的方法.该方法首先从本体文档中抽取类之间的关系,建立类关系图,进而对不同类型的关系赋以权重.然后将多本体中语义高度相关的术语进行组合,对语义相关度低的术语进行分割.最后分别通过基于划分、基于层次化的聚类算法将类关系图重组为一组虚拟本体,实现了对本体的有效重用.以语义搜索引擎Falcons索引的本体作为数据集,对生成的虚拟本体进行了时间性能和聚类合理性评估,并对比了2种聚类方法在虚拟本体生成中的作用.实验证明该方法生成的虚拟本体具有较好的语义内聚性,达到了对本体中术语进行语义重组的目的.

关键词：本体虚拟本体语义网聚类

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Dynamical complexity of Anosov systems driven by a quasi-periodic force

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Science China Mathematics 2025年第1期 89-136页

作者： wen Huang Zeng Lian Kening Lu Department of Mathematics University of Science and Technology of China School of Mathematics Sichuan University

Consider C2Anosov systems on a compact manifold driven by a quasi-periodic *** study their dynamical complexity on various levels from the perspectives of both path-wise dynamics and stochastic *** that these systems are non-wandering（i.e.,every point in the phase space is nonwandering）,we prove a set of results:（1） the existence of abundance of random periodic points;（2） a random Liv?ic theorem;（3） a random Ma?é-Bousch-Conze-Guivarc'h lemma;（4） the existence of strong random ***,a concrete example constructed on a 2-dimensional torus is also given to uncover some interesting phenomena of the systems.

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Targeting TrkB–PSD-95 coupling to mitigate neurological disorders

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Neural Regeneration Research 2025年第3期20卷 715-724页

作者： Xin Yang Yu-wen Alvin Huang John Marshall Department of Molecular Biology Cell Biology and BiochemistryBrown UniversityProvidenceRIUSA Department of Neurology Warren Alpert Medical School of Brown UniversityProvidenceRIUSA Center for Translational Neuroscience Robert J.and Nancy D.Carney Institute for Brain Science and Brown Institute for Translational ScienceBrown UniversityProvidenceRIUSA

Tropomyosin receptor kinase B(TrkB)signaling plays a pivotal role in dendritic growth and dendritic spine formation to promote learning and *** activity-dependent release of brain-derived neurotrophic factor at synapses binds to pre-or postsynaptic TrkB resulting in the strengthening of synapses,reflected by long-term ***,the association of postsynaptic density protein-95 with TrkB enhances phospholipase Cγ-Ca^(2+)/calmodulin-dependent protein kinaseⅡand phosphatidylinositol 3-kinase-mechanistic target of rapamycin signaling required for long-term *** this review,we discuss TrkB-postsynaptic density protein-95 coupling as a promising strategy to magnify brain-derived neurotrophic factor signaling towards the development of novel therapeutics for specific neurological disorders.A reduction of TrkB signaling has been observed in neurodegenerative disorders,such as Alzheimer's disease and Huntington's disease,and enhancement of postsynaptic density protein-95 association with TrkB signaling could mitigate the observed deficiency of neuronal connectivity in schizophrenia and *** with brain-derived neurotrophic factor is problematic,due to poor pharmacokinetics,low brain penetration,and side effects resulting from activation of the p75 neurotrophin receptor or the truncated TrkB.T1 *** TrkB agonists and antibodies that activate TrkB are being intensively investigated,they cannot distinguish the multiple human TrkB splicing isoforms or cell type-specific *** TrkB–postsynaptic density protein-95 coupling provides an alternative approach to specifically boost TrkB signaling at localized synaptic sites versus global stimulation that risks many adverse side effects.

关键词： Angelman syndrome autism brain-derived neurotrophic factor depression neurodegenerative disorder neurodevelopmental disorder postsynaptic density protein-95 synaptic plasticity TrkB

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Wave effect of gravitational waves intersected with a microlens field Ⅱ:An adaptive hierarchical tree algorithm and population study

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Science China(Physics,Mechanics & Astronomy) 2025年第1期Mechanics & Astronomy) .卷 241-254页

作者： Xikai Shan Guoliang Li Xuechun Chen wen Zhao Bin Hu Shude Mao Department of Astronomy Tsinghua University Purple Mountain Observatory Chinese Academy of Sciences Institute for Frontier in Astronomy and Astrophysics Beijing Normal University School of Physics and Astronomy Beijing Normal University School of Astronomy and Space Science University of Science and Technology of China CAS Key Laboratory for Researches in Galaxies and Cosmology Department of Astronomy University of Science and Technology of ChinaChinese Academy of Sciences

The gravitational lensing wave effect generated by a microlensing field embedded in a lens galaxy is an inevitable phenomenon in strong lensed gravitational waves （SLGWs）.This effect presents both challenges and opportunities for the detection and application of ***,investigating this wave effect requires computing a complete diffraction integral over each microlens in the *** is extremely time-consuming due to the large number of microlenses （10～3-10～6）.Therefore,simply adding all the microlenses is ***,the complexity of the time delay surface makes the lens plane resolution a crucial factor in controlling numerical *** this paper,we propose a trapezoid approximation-based adaptive hierarchical tree algorithm to meet the challenges of calculation speed and *** find that this algorithm accelerates the calculation by four orders of magnitude compared to the simple adding method and is one order of magnitude faster than the fixed hierarchical tree algorithm proposed for electromagnetic *** importantly,our algorithm ensures controllable numerical errors,increasing confidence in the *** with our previous work （***.66,239511,2023）,this paper addresses all numerical issues,including integral convergence,precision,and computational time1).Finally,we conducted a population study on the microlensing wave effect of SLGWs using this algorithm and found that the microlensing wave effect cannot be ignored,especially for Type II SLGWs （from saddle position of the time delay surface） due to their intrinsic geometric structures and their typical intersection with a denser microlensing ***,more than 33%（11%） of SLGWs have a mismatch larger than 1%（3%） compared to the unlensed ***,we found that the mismatch between signal pairs in a doubly imaged GW is generally larger than 10-3,and 61%（25%） of signal pairs have a mismatch larger than 1%（3%）.Therefo

关键词： gravitational lensing diffractional integral algorithm gravitational wave

The detection, extraction and parameter estimation of extreme-mass-ratio inspirals with deep learning

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Science China(Physics,Mechanics & Astronomy) 2025年第1期Mechanics & Astronomy) .卷 86-96页

作者： Qianyun Yun wen-Biao Han Yi-Yang Guo He Wang Minghui Du Hangzhou Institute for Advanced Study University of Chinese Academy of Sciences Shanghai Astronomical Observatory Chinese Academy of Sciences School of Physics and Astronomy Shanghai Jiao Tong University School of Astronomy and Space Science University of Chinese Academy of Sciences Taiji Laboratory for Gravitational Wave Universe (Beijing/Hangzhou) University of Chinese Academy of Sciences Lanzhou Center for Theoretical Physics Key Laboratory of Theoretical Physics of Gansu Province Key Laboratory of Quantum Theory and Applications of MoE Lanzhou University Institute of Theoretical Physics & Research Center of Gravitation Lanzhou University International Centre for Theoretical Physics Asia-Pacific (ICTP-AP) University of Chinese Academy of Sciences (UCAS) Center for Gravitational Wave Experiment National Microgravity Laboratory Institute of Mechanics Chinese Academy of Sciences

One of the primary goals of space-borne gravitational wave detectors is to detect and analyze extreme-mass-ratio inspirals(EMRIs). This task is particularly challenging because EMRI signals are complex, lengthy, and faint. In this work, we introduce a2-layer convolutional neural network(CNN) approach to detect EMRI signals for space-borne detectors, achieving a true positive rate(TPR) of 96.9% at a 1% false positive rate(FPR) for signal-to-noise ratio(SNR) from 50 to 100. Especially, the key intrinsic parameters of EMRIs such as the mass, spin of the supermassive black hole(SMBH) and the initial eccentricity of the orbit can also be inferred directly by employing a neural network. The mass and spin of the SMBH can be determined at 99% and 92% respectively. This will greatly reduce the parameter spaces and computing cost for the following Bayesian parameter *** model also has a low dependency on the accuracy of the waveform model. This study underscores the potential of deep learning methods in EMRI data analysis, enabling the rapid detection of EMRI signals and efficient parameter estimation.

关键词： gravitational wave EMRIs deep-learing

An efficient quantum proactive incremental learning algorithm

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Science China(Physics,Mechanics & Astronomy) 2025年第1期Mechanics & Astronomy) .卷 49-57页

作者： Lingxiao Li Jing Li Yanqi Song Sujuan Qin Qiaoyan wen Fei Gao State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications School of Cyberspace Security Beijing University of Posts and Telecommunications

In scenarios where a large amount of data needs to be learned, incremental learning can make full use of old knowledge, significantly reduce the computational cost of the overall learning process, and maintain high performance. In this paper, taking the MaxCut problem as our example, we introduce the idea of incremental learning into quantum computing, and propose a Quantum Proactive Incremental Learning algorithm(QPIL). Instead of a one-off training of quantum circuit, QPIL contains a multi-phase training on gradually-increased subgraphs of all vertices, proactively reducing large-scale problems to smaller ones to solve in steps, providing an efficient solution for MaxCut. Specifically, some vertices and corresponding edges are randomly selected for training to obtain optimized parameters of the quantum circuit at first. Then, in each incremental phase, the remaining vertices and corresponding edges are gradually added and the parameters obtained from the previous phase are reused in the parameter initialization of the current phase. We perform experiments on 120 different small-scale graphs, and it shows that QPIL performs superior to prevalent quantum and classical baselines in terms of approximation ratio(AR), time cost, anti-forgetting, and solving stability. In particular, QPIL's AR surpasses 20% of mainstream quantum baselines, and the time cost is less than 1/5 of them. The idea of QPIL is expected to inspire efficient and high-quality solutions in large-scale Max Cut and other combinatorial optimization problems.

关键词： variational quantum algorithm incremental learning multi-phase training MaxCut quantum computing

Engineered Cancer Nanovaccines:A New Frontier in Cancer Therapy

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Nano-Micro Letters 2025年第2期17卷 134-168页

作者： Yijie Wang Congrui Liu Chao Fang Qiuxia Peng wen Qin Xuebing Yan Kun Zhang Central Laboratory and Department of Medical Ultrasound Sichuan Academy of Medical SciencesSichuan Provincial People’s HospitalSchool of MedicineUniversity of Electronic Science and Technology of ChinaNo.32West Second SectionFirst Ring RoadChengdu 610072People’s Republic of China Department of Stomatology and Central Laboratory School of MedicineShanghai Tenth People’s HospitalTongji UniversityNO.301 Yan‑Chang‑Zhong RoadShanghai 200072People’s Republic of China Jiangsu Provincial Innovation and Practice Base for Postdoctors Suining People’s HospitalAffiliated Hospital of Xuzhou Medical UniversityNo.2Bayi West RoadSuiningXu Zhou 221000Jiangsu ProvincePeople’s Republic of China

Vaccinations are essential for preventing and treating disease,especially cancer nanovaccines,which have gained considerable interest recently for their strong anti-tumor immune *** can prompt the immune system to generate antibodies and activate various immune cells,leading to a response against tumor tissues and reducing the negative effects and recurrence risks of traditional chemotherapy and *** enhance the flexibility and targeting of vaccines,nanovaccines utilize nanotechnology to encapsulate or carry antigens at the nanoscale level,enabling more controlled and precise drug delivery to enhance immune *** nanovaccines function by encapsulating tumor-specific antigens or tumor-associated antigens within *** small size of these nanomaterials allows for precise targeting of T cells,dendritic cells,or cancer cells,thereby eliciting a more potent anti-tumor *** this paper,we focus on the classification of carriers for cancer nanovaccines,the roles of different target cells,and clinically tested cancer nanovaccines,discussing strategies for effectively inducing cytotoxic T lymphocytes responses and optimizing antigen presentation,while also looking ahead to the translational challenges of moving from animal experiments to clinical trials.

关键词： Cancer nanovaccines Immunotherapy Nanobiotechnology Immune targets Signaling pathway

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