FAILED
首站-论文投稿智能助手
典型文献
Neural Decoding of Visual Information Across Different Neural Recording Modalities and Approaches
文献摘要:
Vision plays a peculiar role in intelligence.Visual information,forming a large part of the sensory information,is fed into the human brain to formulate various types of cognition and behaviours that make humans become intelligent agents.Recent advances have led to the development of brain-inspired algorithms and models for machine vision.One of the key components of these methods is the utilization of the computational principles underlying biological neurons.Additionally,advanced experimental neuroscience tech-niques have generated different types of neural signals that carry essential visual information.Thus,there is a high demand for mapping out functional models for reading out visual information from neural signals.Here,we briefly review recent progress on this issue with a focus on how machine learning techniques can help in the development of models for contending various types of neural signals,from fine-scale neural spikes and single-cell calcium imaging to coarse-scale electroencephalography(EEG)and functional magnetic reson-ance imaging recordings of brain signals.
文献关键词:
作者姓名:
Yi-Jun Zhang;Zhao-Fei Yu;Jian.K.Liu;Tie-Jun Huang
作者机构:
Department of Computer Science and Engineering,Shanghai Jiao Tong University,Shanghai 200240,China;School of Computer Science,Peking University,Beijing 100190,China;Institute for Artificial Intelligence,Peking University,Beijing 100190,China;School of Computing,University of Leeds,Leeds LS2 9JT,UK;Beijing Academy of Artificial Intelligence,Beijing 100190,China
引用格式:
[1]Yi-Jun Zhang;Zhao-Fei Yu;Jian.K.Liu;Tie-Jun Huang-.Neural Decoding of Visual Information Across Different Neural Recording Modalities and Approaches)[J].机器智能研究(英文),2022(05):350-365
A类:
Modalities,contending,reson
B类:
Neural,Decoding,Visual,Information,Across,Different,Recording,Approaches,Vision,plays,peculiar,role,intelligence,information,forming,large,part,sensory,fed,into,brain,formulate,various,types,cognition,behaviours,that,make,humans,become,intelligent,agents,Recent,advances,have,led,development,inspired,algorithms,models,machine,vision,One,key,components,these,methods,utilization,computational,principles,underlying,biological,neurons,Additionally,advanced,experimental,neuroscience,generated,different,neural,signals,carry,essential,visual,Thus,there,high,demand,mapping,out,functional,reading,from,Here,we,briefly,review,recent,progress,this,issue,focus,how,learning,techniques,can,help,fine,scale,spikes,single,cell,calcium,imaging,coarse,electroencephalography,EEG,magnetic,recordings
AB值:
0.657038
相似文献
Mako:A Graph-based Pattern Growth Approach to Detect Complex Structural Variants
Jiadong Lin;Xiaofei Yang;Walter Kosters;Tun Xu;Yanyan Jia;Songbo Wang;Qihui Zhu;Mallory Ryan;Li Guo;Chengsheng Zhang;The Human Genome Structural Variation Consortium;Charles Lee;Scott E.Devine;Evan E.Eichler;Kai Ye-School of Automation Science and Engineering,Faculty of Electronic and Information Engineering,Xi'an Jiaotong University,Xi'an 710049,China;MOE Key Lab for Intelligent Networks&Networks Security,Faculty of Electronic and Information Engineering,Xi'an Jiaotong University,Xi'an 710049,China;Genome Institute,the First Affiliated Hospital of Xi'an Jiaotong University,Xi'an 710061,China;Leiden Institute of Advanced Computer Science,Faculty of Science,Leiden University,Leiden 2311EZ,Netherland;School of Computer Science and Technology,Faculty of Electronic and Information Engineering,Xi'an Jiaotong University,Xi'an 710049,China;The Jackson Laboratory for Genomic Medicine,Farmington,CT 06032,USA;Precision Medicine Center,the First Affiliated Hospital of Xi'an Jiaotong University,Xi'an 710061,China;Institute for Genome Sciences,University of Maryland School of Medicine,Baltimore,MD 21201,USA;Department of Genome Sciences,University of Washington School of Medicine,Seattle,WA 98119,USA;Howard Hughes Medical Institute,University of Washington,Seattle,WA 98195,USA;The School of Life Science and Technology,Xi'an Jiaotong University,Xi'an 710049,China
Annotating TSSs in Multiple Cell Types Based on DNA Sequence and RNA-seq Data via DeeReCT-TSS
Juexiao Zhou;Bin Zhang;Haoyang Li;Longxi Zhou;Zhongxiao Li;Yongkang Long;Wenkai Han;Mengran Wang;Huanhuan Cui;Jingjing Li;Wei Chen;Xin Gao-Computer Science Program,Computer,Electrical and Mathematical Sciences and Engineering Division,King Abdullah University of Science and Technology,Thuwal 23955-6900,Saudi Arabia;Computational Bioscience Research Center,King Abdullah University of Science and Technology,Thuwal 23955-6900,Saudi Arabia;Department of Biology,School of Life Sciences,Southern University of Science and Technology,Shenzhen 518055,China;Shenzhen Key Laboratory of Gene Regulation and Systems Biology,School of Life Sciences,Southern University of Science and Technology,Shenzhen 518055,China;Academy for Advanced Interdisciplinary Studies,Southern University of Science and Technology,Shenzhen 518055,China
机标中图分类号,由域田数据科技根据网络公开资料自动分析生成,仅供学习研究参考。