Attention Improves Transfer of Motion Information between V1 and MT

被引:35
作者
Saproo, Sameer [1 ,2 ,3 ]
Serences, John T. [3 ,4 ]
机构
[1] NYU, Dept Psychol, New York, NY 10003 USA
[2] NYU, Ctr Neural Sci, New York, NY 10003 USA
[3] Univ Calif San Diego, Dept Psychol, San Diego, CA 92093 USA
[4] Univ Calif San Diego, Neurosci Grad Program, San Diego, CA 92093 USA
关键词
correlations; fMRI; gain; information theory; MT; HUMAN VISUAL-CORTEX; AREA MT; POPULATION CODES; STRIATE CORTEX; CORTICAL AREAS; CHANNEL NOISE; RESPONSES; NEURONS; BOLD; V4;
D O I
10.1523/JNEUROSCI.3484-13.2014
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
Selective attention modulates activity within individual visual areas; however, the role of attention in mediating the transfer of information between areas is not well understood. Here, we used fMRI to assess attention-related changes in coupled BOLD activation in two key areas of human visual cortex that are involved in motion processing: V1 and MT. To examine attention-related changes in cross-area coupling, multivoxel patterns in each visual area were decomposed to estimate the trial-by-trial response amplitude in a set of direction-selective "channels." In both V1 and MT, BOLD responses increase in direction-selective channels tuned to the attended direction of motion and decrease in channels tuned away from the attended direction. Furthermore, the modulation of cross-area correlations between similarly tuned populations is inversely related to the modulation of their mean responses, an observation that can be explained via a feedforward motion computation in MT and a modulation of local noise correlations in V1. More importantly, these modulations accompany an increase in the cross-area mutual information between direction-selective response patterns in V1 and MT, suggesting that attention improves the transfer of sensory information between cortical areas that cooperate to support perception. Finally, our model suggests that divisive normalization of neural activity in V1 before its integration by MT is critical to cross-area information coupling, both in terms of cross-area correlation as well as cross-area mutual information.
引用
收藏
页码:3586 / 3596
页数:11
相关论文
共 61 条
  • [11] Measuring and interpreting neuronal correlations
    Cohen, Marlene R.
    Kohn, Adam
    [J]. NATURE NEUROSCIENCE, 2011, 14 (07) : 811 - 819
  • [12] Using Neuronal Populations to Study the Mechanisms Underlying Spatial and Feature Attention
    Cohen, Marlene R.
    Maunsell, John H. R.
    [J]. NEURON, 2011, 70 (06) : 1192 - 1204
  • [13] Attention improves performance primarily by reducing interneuronal correlations
    Cohen, Marlene R.
    Maunsell, John H. R.
    [J]. NATURE NEUROSCIENCE, 2009, 12 (12) : 1594 - U148
  • [14] CHANNEL NOISE IN NERVE MEMBRANES AND LIPID BILAYERS
    CONTI, F
    WANKE, E
    [J]. QUARTERLY REVIEWS OF BIOPHYSICS, 1975, 8 (04) : 451 - 506
  • [15] Cover T.M., 2006, ELEMENTS INFORM THEO, V2nd ed
  • [16] Dale AM, 1999, HUM BRAIN MAPP, V8, P109, DOI 10.1002/(SICI)1097-0193(1999)8:2/3<109::AID-HBM7>3.0.CO
  • [17] 2-W
  • [18] Dynamic predictions: Oscillations and synchrony in top-down processing
    Engel, AK
    Fries, P
    Singer, W
    [J]. NATURE REVIEWS NEUROSCIENCE, 2001, 2 (10) : 704 - 716
  • [19] FMRI OF HUMAN VISUAL-CORTEX
    ENGEL, SA
    RUMELHART, DE
    WANDELL, BA
    LEE, AT
    GLOVER, GH
    CHICHILNISKY, EJ
    SHADLEN, MN
    [J]. NATURE, 1994, 369 (6481) : 525 - 525
  • [20] THE DESIGN AND USE OF STEERABLE FILTERS
    FREEMAN, WT
    ADELSON, EH
    [J]. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 1991, 13 (09) : 891 - 906