The mechanism of involuntary visual spatial attention revealed by a new linear computation model

被引:2
|
作者
Qiu, Lijun
Yao, Dezhong [1 ]
Fu, Shimin
Chen, Lin
机构
[1] Univ Elect Sci & Technol China, Sch Life Sci & Technol, Ctr Neuroinformat, Chengdu, Peoples R China
[2] Chinese Acad Sci, Biophys Res Inst, Beijing Cognit Lab, Beijing, Peoples R China
基金
中国国家自然科学基金;
关键词
computation; involuntary attention; ERP; peripheral cue;
D O I
10.1007/s10548-006-0003-0
中图分类号
R74 [神经病学与精神病学];
学科分类号
摘要
EEG reveals brain electrical activities with high temporal resolution. Yet, multiple implicit variables may be involved in limited event related potential (ERP) measures. Special computation techniques are needed to recover these parameters. In the study of involuntary visual spatial attention, we may obtain the ERP in valid cued (V), invalid cued (1) and neutral cued (N) conditions. Usually, the effect of involuntary attention is computed by the subtraction model with the assumption that V/I and N are independent. Yet, they should be related. Treating V/I as a function of N, a linear model V(I) = W + GN is assumed, where W and G are implicit in the ERP measures. G is the gain control on the neutral function. Provided G and W are constant over a local brain region, we may use the Total Least Square (TLS) algorithm to compute their values. The values of W and G computed from an involuntary attention experiment data show that multiple implicit variables are involved in obtained ERPs. Here G acts as a "top-down" sensory modulator on the neutral ERPs and W is related to possible newly involved neural activities. The parameters derived from the new linear model also suggest that there are different mechanisms involved in involuntary attention and voluntary allocation of attention.
引用
收藏
页码:249 / 256
页数:8
相关论文
共 50 条
  • [1] The Mechanism of Involuntary Visual Spatial Attention Revealed by a New Linear Computation Model
    Lijun Qiu
    Dezhong Yao
    Shimin Fu
    Lin Chen
    Brain Topography, 2006, 18 : 249 - 256
  • [2] Distributed model of spatial visual attention
    Vitay, J
    Rougier, NP
    Alexandre, F
    BIOMIMETIC NEURAL LEARNING FOR INTELLIGENT ROBOTS: INTELLIGENT SYSTEMS, COGNITIVE ROBOTICS, AND NEUROSCIENCE, 2005, 3575 : 54 - 72
  • [3] TOWARDS A MODEL OF VISUAL SPATIAL ATTENTION
    BELOPOLSKY, VI
    INTERNATIONAL JOURNAL OF PSYCHOPHYSIOLOGY, 1989, 7 (2-4) : 139 - 140
  • [4] Involuntary capture of visual-spatial attention occurs for intersections, both real and "imagined"
    Burnham, Bryan R.
    Neely, James H.
    PSYCHONOMIC BULLETIN & REVIEW, 2007, 14 (04) : 735 - 741
  • [5] Involuntary capture of visual-spatial attention occurs for intersections, both real and “imagined”
    Bryan R. Burnham
    James H. Neely
    Psychonomic Bulletin & Review, 2007, 14 : 735 - 741
  • [6] Pedestrian object detection with fusion of visual attention mechanism and semantic computation
    Xiao, Feng
    Liu, Baotong
    Li, Runa
    MULTIMEDIA TOOLS AND APPLICATIONS, 2020, 79 (21-22) : 14593 - 14607
  • [7] Pedestrian object detection with fusion of visual attention mechanism and semantic computation
    Feng Xiao
    Baotong Liu
    Runa Li
    Multimedia Tools and Applications, 2020, 79 : 14593 - 14607
  • [8] The role of different cues in the brain mechanism on visual spatial attention
    SONG Weiqun
    State Key Laboratory of Cognitive Neuroscience and Learning
    School of Psychology
    Key Laboratory of Mental Health
    Department of Neurology
    Institute of Linguistics
    ProgressinNaturalScience, 2006, (10) : 1045 - 1050
  • [9] The role of different cues in the brain mechanism on visual spatial attention
    Song Weiqun
    Luo Yuejia
    Chi Song
    Ji Xunming
    Ling Feng
    Zhao Lun
    Wang Maobin
    Shi Jiannong
    PROGRESS IN NATURAL SCIENCE-MATERIALS INTERNATIONAL, 2006, 16 (10) : 1045 - 1050
  • [10] Retinotopic organization of early visual spatial attention effects as revealed by PET and ERPs
    Woldorff, MG
    Fox, PT
    Matzke, M
    Lancaster, JL
    Veeraswamy, S
    Zamarripa, F
    Seabolt, M
    Glass, T
    Gao, JH
    Martin, CC
    Jerabek, P
    HUMAN BRAIN MAPPING, 1997, 5 (04) : 280 - 286