期刊文献+

高速LED背光速视器揭示拓扑性质的快速加工 被引量:1

High Speed LED Backlight Tachistoscope Reveals Fast Processing of Topological Invariants
下载PDF
导出
摘要 灵长类视觉系统能够非常有效地从环境中提取稳定的不变性特征,而不受各种变换与干扰的影响.这种不变性知觉的时间与动态过程为视觉理论提供了重要的约束.我们开发了一种高速发光二极管(LED)背光速视器,能够短暂呈现1 ms的视觉刺激,并以亚毫秒级精度调整刺激呈现时间.这使得我们可以通过控制视觉输入的可获取时间,估计感觉线索积累的心理物理曲线,从而研究在图形结构优势效应任务中,拓扑、射影、仿射和欧氏不变性的相对加工速度.实验结果表明拓扑不变性所需要的呈现时间最短,这与大范围首先理论的预测相一致. Primate visual system is extremely efficient in extracting stable invariants from environment, despite various transformation and degradation. The timing and dynamics of invariants perception provide important constraints for theories of vision. We developed a high speed LED backlight tachistoscope capable to deliver visual stimuli with 1 ms exposure and adjust the duration in submillisecond precision, which enabled us to investigate the relative speed of processing topological, projective, affine, and Euclidean invariants in configural superiority effect paradigm by manipulating the access time to visual input and estimating the psychometric function for sensory evidence accumulation. The results suggest that topological invariant requires shortest exposure time, consistent with the prediction of global-first theory.
出处 《生物化学与生物物理进展》 SCIE CAS CSCD 北大核心 2016年第2期157-166,共10页 Progress In Biochemistry and Biophysics
基金 国家重点基础研究发展计划(973)(2012CB825500,2015CB351701) 国家自然科学基金(91132302) 中国科学院基金(XDB02010001,XDB02050001)资助项目
关键词 图形结构优势效应 拓扑不变性 时间过程 心理物理曲线 速视器 configural superiority effect topological invariant timing psychometric function tachistoscope
  • 相关文献

参考文献30

  • 1Cox D D. Do we understand high-level vision?. Ctuzcnt opinion in neurobiology, Elsevier Ltd, 2014, 25C: 187-193.
  • 2Rajalingham R, Schmidt K, DiCarlo J J. Comparison of object recognition behavior in human and monkey. Journal of Ncuroscience, 2015, 35(35): 12127-12136.
  • 3DiCarlo J J, Cox D D. Untangling invariant object recognition. Trends in Cognitive Sciences, 2007, 11(8): 333-341.
  • 4DiCarlo J J, Zoccolan D, Rust N C. How does the brain solve visual object recognition?. Neuron, Elsevier Inc., 2012, 73(3): 415-434.
  • 5Kravitz D J, Saleem K S, Baker C I, et al. The vgntral visual pathway: an expanded neural framework for the processing of object quality. Trends in Cognitive Sciences, Elsevier Ltd, 2013, 17(I): 26-49.
  • 6Serrc T, Oliva A, Poggio T A. A feedforward architecture accounts for rapid categorization. Proc Nat Acad Sci USA, 2007, 104(15): 6424-6429.
  • 7Krizhevsky A, Sutskever I, Hinton G E. ImageNet Classification with Deep Convolutional Neural Networks. NIPS, 2012:1-9.
  • 8Yamins D L K, Hong H, Cadieu C F, et al. Performance-optimized hierarchical models predict neural responses in higher visual cortex. Proe Nat Acad Sci USA, 2014, 111(23): 8619-8624.
  • 9Hoehstein S, Ahissar M. View from the top: hierarchies and reverse hierarchies in the visual system. Neuron, 2002, 36(5): 791-804.
  • 10Chen L. The topological approach to perceptual organization. Vis. Cogn., HOVE: PSYCHOLOGY PRESS, 2005, 12(4): 553-637.

同被引文献2

引证文献1

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部