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
  • [21] RPformer: A Robust Parallel Transformer for Visual Tracking in Complex Scenes
    Gu, Fengwei
    Lu, Jun
    Cai, Chengtao
    IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, 2022, 71
  • [22] Adaptive cascaded and parallel feature fusion for visual object tracking
    Wang, Jun
    Li, Sixuan
    Li, Kunlun
    Zhu, Qizhen
    VISUAL COMPUTER, 2024, 40 (03): : 2119 - 2138
  • [23] On robots and flies:: Modeling the visual orientation behavior of flies
    Huber, SA
    Franz, MO
    Bülthoff, HH
    ROBOTICS AND AUTONOMOUS SYSTEMS, 1999, 29 (04) : 227 - 242
  • [24] Higher-Order Thalamic Circuits Channel Parallel Streams of Visual Information in Mice
    Bennett, Corbett
    Gale, Samuel D.
    Garrett, Marina E.
    Newton, Melissa L.
    Callaway, Edward M.
    Murphy, Gabe J.
    Olsen, Shawn R.
    NEURON, 2019, 102 (02) : 477 - +
  • [25] Robust Visual Tracking via Parallel Kernel Sparse Representation and NormalHedge
    Kuang, Jinjun
    Cheng, Cheng
    PROCEEDINGS OF THE 2ND INTERNATIONAL SYMPOSIUM ON COMPUTER, COMMUNICATION, CONTROL AND AUTOMATION, 2013, 68 : 89 - 93
  • [26] PARALLEL OCULAR AND MANUAL TRACKING RESPONSES TO A CONTINUOUSLY MOVING VISUAL TARGET
    MATHER, JA
    PUTCHAT, C
    JOURNAL OF MOTOR BEHAVIOR, 1983, 15 (01) : 29 - 38
  • [27] Visual tracking achieved by adaptive sampling from hierarchical and parallel predictions
    Shibata, Tomohiro
    Bando, Takashi
    Ishii, Shin
    NEURAL INFORMATION PROCESSING, PART I, 2008, 4984 : 604 - +
  • [28] Query-Based Object Visual Tracking with Parallel Sequence Generation
    Liu, Chang
    Zhang, Bin
    Bo, Chunjuan
    Wang, Dong
    SENSORS, 2024, 24 (15)
  • [29] VISUAL ECOLOGY OF BITING FLIES
    ALLAN, SA
    DAY, JF
    EDMAN, JD
    ANNUAL REVIEW OF ENTOMOLOGY, 1987, 32 : 297 - 316
  • [30] Human figure in the visual arts
    Nakamachi, K
    ANTHROPOLOGICAL SCIENCE, 2000, 108 (01) : 67 - 67