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Science China(Life Sciences) 2023年第5期66卷 893-1066页

作者： Aging Biomarker Consortium Hainan Bao Jiani Cao Mengting Chen Min Chen Wei Chen Xiao Chen Yanhao Chen Yu Chen Yutian Chen Zhiyang Chen Jagadish K Chhetri Yingjie Ding Junlin Feng Jun Guo Mengmeng Guo Chuting He Yujuan Jia Haiping Jiang Ying Jing Dingfeng Li Jiaming Li Jingyi Li Qinhao Liang Rui Liang Feng Liu Xiaoqian Liu Zuojun Liu Oscar Junhong Luo Jianwei Lv Jingyi Ma Kehang Mao Jiawei Nie Xinhua Qiao Xinpei Sun Xiaoqiang Tang Jianfang Wang Qiaoran Wang Siyuan Wang Xuan Wang Yaning Wang Yuhan Wang Rimo Wu Kai Xia Fu-Hui Xiao Lingyan Xu Yingying Xu Haoteng Yan Liang Yang Ruici Yang Yuanxin Yang Yilin Ying Le Zhang Weiwei Zhang Wenwan Zhang Xing Zhang Zhuo Zhang Min Zhou Rui Zhou Qingchen Zhu Zhengmao Zhu Feng Cao Zhongwei Cao Piu Chan Chang Chen Guobing Chen Hou-Zao Chen Jun Chen Weimin Ci Bi-Sen Ding Qiurong Ding Feng Gao Jing-Dong JHan Kai Huang Zhenyu Ju Qing-Peng Kong Ji Li Jian Li Xin Li Baohua Liu Feng Liu Lin Liu Qiang Liu Qiang Liu Xingguo Liu Yong Liu Xianghang Luo Shuai Ma Xinran Ma Zhiyong Mao Jing Nie Yaojin Peng Jing Qu Jie Ren Ruibao Ren Moshi Song Zhou Songyang Yi Eve Sun Yu Sun Mei Tian Shusen Wang Si Wang Xia Wang Xiaoning Wang Yan-Jiang Wang Yunfang Wang Catherine CL Wong Andy Peng Xiang Yichuan Xiao Zhengwei Xie Daichao Xu Jing Ye Rui Yue Cuntai Zhang Hongbo Zhang Liang Zhang Weiqi Zhang Yong Zhang Yun-Wu Zhang Zhuohua Zhang Tongbiao Zhao Yuzheng Zhao Dahai Zhu Weiguo Zou Gang Pei Guang-Hui Liu Aging Biomarker Consortium(ABC) Beijing 100101China CAS Key Laboratory of Genomic and Precision Medicine Beijing Institute of GenomicsChinese Academy of Sciences and China National Center for BioinformationBeijing 100101China State Key Laboratory of Stem Cell and Reproductive Biology Institute of ZoologyChinese Academy of SciencesBeijing 100101China Department of Dermatology Xiangya HospitalCentral South UniversityChangsha 410008China Hunan Key Laboratory of Aging Biology Xiangya HospitalCentral South UniversityChangsha 410008China National Clinical Research Center for Geriatric Disorders Xiangya HospitalCentral South UniversityChangsha 410008China Clinic Center of Human Gene Research Union HospitalTongji Medical CollegeHuazhong University of Science and TechnologyWuhan 430022China Hubei Clinical Research Center of Metabolic and Cardiovascular Disease Huazhong University of Science and TechnologyWuhan 430022China Hubei Key Laboratory of Metabolic Abnormalities and Vascular Aging Huazhong University of Science and TechnologyWuhan 430022China Stem Cell Translational Research Center Tongji HospitalTongji University School of MedicineShanghai 200065China Department of Nuclear Medicine Daping HospitalThird Military Medical UniversityChongqing 400042China CAS Key Laboratory of Nutrition Metabolism and Food SafetyShanghai Institute of Nutrition and HealthUniversity of Chinese Academy of SciencesChinese Academy of SciencesShanghai 200031China Shanghai Key Laboratory of Maternal Fetal Medicine Clinical and Translational Research Center of Shanghai First Maternity and Infant HospitalFrontier Science Center for Stem Cell ResearchShanghai Key Laboratory of Signaling and Disease ResearchSchool of Life Sciences and TechnologyTongji UniversityShanghai 200092China The Department of Endovascular Surgery The First Affiliated Hospital of Zhengzhou UniversityZhengzhou 450052China Key Laboratory of Regenerative Medicine of Ministry of Education Institute of Ageing and Regenerative MedicineJ

Aging biomarkers are a combination of biological parameters to(i)assess age-related changes,(ii)track the physiological aging process,and(iii)predict the transition into a pathological *** a broad spectrum of aging bi... 详细信息

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The Deep Learning model of Higher-Lower-Order Cognition, Memory, and Affection- More General Than KAN

arXiv

引用

arXiv 2022年

作者： Tao, Jun-Bo Sun, Bai-Qing Zhu, Wei-Dong Qu, Shi-You Li, Jia-Qiang Li, Guo-Qi Wang, Yan-Yan Chen, Ling-Kun Wu, Chong Xiong, Yu Zhou, Jiaxuan School of Management Harbin Institute of Technology Heilongjiang Harbin150001 China Department of Mechanical Engineering University of Maryland Baltimore County BaltimoreMD21250 United States Institute No.25 of the Second Academy China Aerospace Science and Industry Corporation Limited Beijing100048 China Institute of Automation Chinese Academy of Science Beijing100190 China University of Chinese Academy of Science Beijing100049 China Faculty of Humanities and Social Sciences Harbin Institute of Technology Heilongjiang Harbin150001 China College of Civil Science and Engineering Yangzhou University Yangzhou China Jiangsu 225127 China Department of Civil and Environmental Engineering University of California Los AngelesCA90095 United States School of Civil Engineering Southwest Jiaotong University Sichuan Chengdu610031 China Surrey Business School University of Surrey Surrey GuildfordGU2 7XH United Kingdom

Beyond the consideration of the basic connection, this research focuses on a new Neutral Network (NN) model, referred as PNN (Plasticity Neural Network) in which the current and memory effective range between synapses and neurons plastic changes with iterations, are both taken into account at the same time, specifically, the current and memory synaptic effective range weights. In addition, this mechanism of synaptic strength rebalance is consistent with the findings in the recent research on brain plasticity. Regarding the importance of this mechanism [14], our Neural Network is, it treats synapses as a group of intelligent agents to achieve synaptic strength rebalance. Dr. Luo’s team has mentioned that the competition regarding synapse formation for dendritic morphogenesis is important, also reflected PNN simulates synapse formation[15]. We try to examine the mechanism of failure in brain plasticity by model at the closure of critical period in details by contrasting with studies before[19]. The PNN model is not just modified on the architecture of NN based on current gradient informational synapse formation and brain plasticity, but also the memory negative and positive gradient informational synapse formation and memory brain plasticity at critical period. By simulations, the PNN gave the two cases with and without negative cortex memories persistence. And the paper proposed α7-nAChR-dependent astrocytic responsiveness is an integral part of the cellular substrate underlying memory persistence by impairing fear memory[20]. In addition, memory brain plasticity involves the plus or minus disturbance-astrocytes phagocytose synapses, through which the synaptic homeostasis is achieved[21]. The effect of astrocyte made local synaptic effective range remain in an appropriate length at critical period[21]. Both negative and positive memories can be reflected in brain cortex, and its simulations fits very well with experiments in the relationship of human intelligence and

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