Context-enabled learning in the human visual system

被引:134
|
作者
Adini, Y [1 ]
Sagi, D [1 ]
Tsodyks, M [1 ]
机构
[1] Weizmann Inst Sci, Dept Neurobiol, IL-76100 Rehovot, Israel
基金
美国国家科学基金会;
关键词
D O I
10.1038/415790a
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Training was found to improve the performance of humans on a variety of visual perceptual tasks(1,2). However, the ability to detect small changes in the contrast of simple visual stimuli could not be improved by repetition(3). Here we show that the performance of this basic task could be modified after the discrimination of the stimulus contrast was practised in the presence of similar laterally placed stimuli, suggesting a change in the local neuronal circuit involved in the task. On the basis of a combination of hebbian and anti-hebbian synaptic learning rules compatible with our results, we propose a mechanism of plasticity in the visual cortex that is enabled by a change in the context.
引用
收藏
页码:790 / 793
页数:4
相关论文
共 50 条
  • [21] Visual Context Learning with Big Data Analytics
    Chandrashekar, Mayanka
    Lee, Yugyung
    2016 IEEE 16TH INTERNATIONAL CONFERENCE ON DATA MINING WORKSHOPS (ICDMW), 2016, : 600 - 607
  • [22] Unsupervised Learning of Spoken Language with Visual Context
    Harwath, David
    Torralba, Antonio
    Glass, James R.
    ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 29 (NIPS 2016), 2016, 29
  • [23] Unsupervised Visual Representation Learning by Context Prediction
    Doersch, Carl
    Gupta, Abhinav
    Efros, Alexei A.
    2015 IEEE INTERNATIONAL CONFERENCE ON COMPUTER VISION (ICCV), 2015, : 1422 - 1430
  • [24] Model Selection for Unsupervised Learning of Visual Context
    Tao Xiang
    Shaogang Gong
    International Journal of Computer Vision, 2006, 69 : 181 - 201
  • [25] Learning Visual Context for Group Activity Recognition
    Yuan, Hangjie
    Ni, Dong
    THIRTY-FIFTH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE, THIRTY-THIRD CONFERENCE ON INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE AND THE ELEVENTH SYMPOSIUM ON EDUCATIONAL ADVANCES IN ARTIFICIAL INTELLIGENCE, 2021, 35 : 3261 - 3269
  • [26] Weighted Part Context Learning for Visual Tracking
    Zhu, Guibo
    Wang, Jinqiao
    Zhao, Chaoyang
    Lu, Hanqing
    IEEE TRANSACTIONS ON IMAGE PROCESSING, 2015, 24 (12) : 5140 - 5151
  • [27] Model selection for unsupervised learning of visual context
    Xiang, Tao
    Gong, Shaogang
    INTERNATIONAL JOURNAL OF COMPUTER VISION, 2006, 69 (02) : 181 - 201
  • [28] Putting Things into Context: Generative AI-Enabled Context Personalization for Vocabulary Learning Improves Learning Motivation
    Leong, Joanne
    Pataranutaporn, Pat
    Danry, Valdemar
    Perteneder, Florian
    Mao, Yaoli
    Maes, Pattie
    PROCEEDINGS OF THE 2024 CHI CONFERENCE ON HUMAN FACTORS IN COMPUTING SYTEMS, CHI 2024, 2024,
  • [29] Top - down strategy affects learning of visual context in visual search
    Endo, N.
    PERCEPTION, 2008, 37 : 8 - 8
  • [30] DiSCo-SLAM: Distributed Scan Context-Enabled Multi-Robot LiDAR SLAM With Two-Stage Global-Local Graph Optimization
    Huang, Yewei
    Shan, Tixiao
    Chen, Fanfei
    Englot, Brendan
    IEEE ROBOTICS AND AUTOMATION LETTERS, 2022, 7 (02) : 1150 - 1157