Figure Tracking by Flies Is Supported by Parallel Visual Streams

被引:52
|
作者
Aptekar, Jacob W. [1 ]
Shoemaker, Patrick A. [2 ]
Fryel, Mark A. [1 ]
机构
[1] Univ Calif Los Angeles, Howard Hughes Med Inst, Dept Integrat Biol & Physiol, Los Angeles, CA 90095 USA
[2] Tanner Res, Monrovia, CA 91016 USA
基金
美国国家科学基金会; 美国国家卫生研究院;
关键词
ORIENTATION BEHAVIOR; 2ND-ORDER MOTION; ILLUSORY MOTION; DROSOPHILA; FLY; RESPONSES; SYSTEM; DISCRIMINATION; PERCEPTION; MOVEMENT;
D O I
10.1016/j.cub.2012.01.044
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
Visual figures may be distinguished based on elementary motion or higher-order non-Fourier features, and flies track both [1]. The canonical elementary motion detector, a compact computation for Fourier motion direction and amplitude, can also encode higher-order signals provided elaborate preprocessing [2-4]. However, the way in which a fly tracks a moving figure containing both elementary and higher-order signals has not been investigated. Using a novel white noise approach, we demonstrate that (1) the composite response to an object containing both elementary motion (EM) and uncorrelated higher-order figure motion (FM) reflects the linear superposition of each component; (2) the EM-driven component is velocity-dependent, whereas the FM component is driven by retinal position; (3) retinotopic variation in EM and FM responses are different from one another; (4) the FM subsystem superimposes saccadic turns upon smooth pursuit; and (5) the two systems in combination are necessary and sufficient to predict the full range of figure tracking behaviors, including those that generate no EM cues at all [1]. This analysis requires an extension of the model that fly motion vision is based on simple elementary motion detectors [5] and provides a novel method to characterize the subsystems responsible for the pursuit of visual figures.
引用
收藏
页码:482 / 487
页数:6
相关论文
共 50 条
  • [1] PARALLEL ATTENTIVE VISUAL TRACKING
    ROBERTS, JM
    CHARNLEY, D
    ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, 1994, 7 (02) : 205 - 215
  • [2] Parallel processing streams in human visual cortex
    Merigan, W
    Freeman, A
    Meyers, SP
    NEUROREPORT, 1997, 8 (18) : 3985 - 3991
  • [3] Parallel Tracker for Visual Object Tracking
    Liang, Xiangluan
    Lai, Ru
    Bi, Luzheng
    PROCEEDINGS OF THE 30TH CHINESE CONTROL AND DECISION CONFERENCE (2018 CCDC), 2018, : 5676 - 5681
  • [4] PARALLEL FUNCTIONAL STREAMS IN THE PRIMATE VISUAL-SYSTEM
    MOVSHON, JA
    INTERNATIONAL JOURNAL OF PRIMATOLOGY, 1987, 8 (05) : 444 - 444
  • [5] Parallel Dual Networks for Visual Object Tracking
    Tian Li
    Peihan Wu
    Feifei Ding
    Wenyuan Yang
    Applied Intelligence, 2020, 50 : 4631 - 4646
  • [6] Parallel Dual Networks for Visual Object Tracking
    Li, Tian
    Wu, Peihan
    Ding, Feifei
    Yang, Wenyuan
    APPLIED INTELLIGENCE, 2020, 50 (12) : 4631 - 4646
  • [7] Tracking control of a UAV with a parallel visual processor
    Greatwood, Colin
    Bose, Laurie
    Richardson, Thomas
    Mayol-Cuevas, Walterio
    Chen, Jianing
    Carey, Stephen J.
    Dudek, Piotr
    2017 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS), 2017, : 4248 - 4254
  • [8] Figure/ground modeling combined with the context matching for visual object tracking
    Bordbar, Saghar
    Agahi, Hamed
    Mahmoodzadeh, Azar
    INTELLIGENT DECISION TECHNOLOGIES-NETHERLANDS, 2019, 13 (03): : 355 - 366
  • [9] Visual Servo Aircraft Control for Tracking Parallel Curves
    Serra, Pedro
    Cunha, Rita
    Silvestre, Carlos
    Hamel, Tarek
    2012 IEEE 51ST ANNUAL CONFERENCE ON DECISION AND CONTROL (CDC), 2012, : 1148 - 1153
  • [10] Parallel visual motion processing streams for manipulable objects and human movements
    Beauchamp, MS
    Lee, KE
    Haxby, JV
    Martin, A
    NEURON, 2002, 34 (01) : 149 - 159