Neural Decoding of Visual Information Across Different Neural Recording Modalities and Approaches

作     者：Yi-Jun Zhang Zhao-Fei Yu Jian.K.Liu Tie-Jun Huang Yi-Jun Zhang;Zhao-Fei Yu;Jian.K.Liu;Tie-Jun Huang

作者机构：Department of Computer Science and EngineeringShanghai Jiao Tong UniversityShanghai 200240China School of Computer SciencePeking UniversityBeijing 100190China Institute for Artificial IntelligencePeking UniversityBeijing 100190China School of ComputingUniversity of LeedsLeeds LS29JTUK Beijing Academy of Artificial IntelligenceBeijing 100190Chin 

出 版 物：《Machine Intelligence Research》 (机器智能研究（英文版）)

年 卷 期：2022年第19卷第5期

页      面：350-365页

核心收录：

学科分类：0831[工学-生物医学工程（可授工学、理学、医学学位）] 08[工学] 080203[工学-机械设计及理论] 0802[工学-机械工程] 0836[工学-生物工程] 

基　　金：supported by National Natural Science Foundation of China(Nos.62176003 and 62088102) the Royal Society Newton Advanced Fellowship of the UK(No.NAF-R1-191082) 

主　　题：Neural decoding machine learning deep learning visual decoding brain-inspired vision 

摘      要：Vision plays a peculiar role in *** 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 *** advances have led to the development of brain-inspired algorithms and models for machine *** of the key components of these methods is the utilization of the computational principles underlying biological ***,advanced experimental neuroscience techniques have generated different types of neural signals that carry essential visual ***,there is a high demand for mapping out functional models for reading out visual information from neural ***,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 resonance imaging recordings of brain signals.