Spatio-temporal templates of transient attention revealed by classification images

被引:17
作者
Megna, Nicola [2 ,3 ]
Rocchi, Francesca [4 ]
Baldassi, Stefano [1 ]
机构
[1] Univ Florence, Dept Psychol, I-50135 Florence, Italy
[2] Univ Florence, Dept Phys & Astron, I-50019 Florence, Italy
[3] Natl Opt Inst, I-50125 Florence, Italy
[4] Univ Nottingham, Sch Psychol, Visual Neurosci Grp, Nottingham NG7 2RD, England
关键词
Classification images; Attention; Parvocellular system; Magnocellular system; SPATIAL ATTENTION; COVERT ATTENTION; PERCEIVED DURATION; STRIATE CORTEX; PERFORMANCE; IMPAIRS; MECHANISM; CHANNELS; FEATURES; IMPROVES;
D O I
10.1016/j.visres.2011.11.012
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
Visual attention is captured by transient signals in the periphery of the visual field, allowing enhanced perceptual representations in spatial tasks. However, it has been reported that the same cues impair performance in temporal tasks (e.g.. Yeshurun, 2004; Yeshurun & Levy, 2003). This findings suggest that transient attention enhances the activity of slow, high-resolution channels, like parvocellular neurons, and/or shuts off faster channels better sensitive to low spatial frequencies, such as the ones of the magnocellular system. To test this idea, we have measured the spatio-temporal perceptive fields for transiently cued signals at various eccentricities using the classification images (CI) technique. At near eccentricities transient attention caused the perceptual templates to be sharper in space and characterized by much stronger high spatial frequency components. At the same time, they show a consistently larger temporal integration window. These effects of attention on perceptual filters are strongly reduced at far eccentricities and disappear when using longer target-cue lags. These data provide evidence in support of the parvocellular model of transient, exogenous attention, showing that in the presence of a well timed spatial cue observers rely on noisy evidence lasting longer and with finer spatial configurations. (C) 2011 Elsevier Ltd. All rights reserved.
引用
收藏
页码:39 / 48
页数:10
相关论文
共 50 条
[41]   Spatio-temporal epidemic forecasting using mobility data with LSTM networks and attention mechanism [J].
Jiao, Shihu ;
Wang, Yu ;
Ye, Xiucai ;
Nagahara, Larry ;
Sakurai, Tetsuya .
SCIENTIFIC REPORTS, 2025, 15 (01)
[42]   An End to End Framework With Adaptive Spatio-Temporal Attention Module for Human Action Recognition [J].
Liu, Shaocan ;
Ma, Xin ;
Wu, Hanbo ;
Li, Yibin .
IEEE ACCESS, 2020, 8 :47220-47231
[43]   PASTFNet: a paralleled attention spatio-temporal fusion network for micro-expression recognition [J].
Haichen Tian ;
Weijun Gong ;
Wei Li ;
Yurong Qian .
Medical & Biological Engineering & Computing, 2024, 62 :1911-1924
[44]   Spatio-temporal attention on manifold space for 3D human action recognition [J].
Ding, Chongyang ;
Liu, Kai ;
Cheng, Fei ;
Belyaev, Evgeny .
APPLIED INTELLIGENCE, 2021, 51 (01) :560-570
[45]   Spatio-temporal attention on manifold space for 3D human action recognition [J].
Chongyang Ding ;
Kai Liu ;
Fei Cheng ;
Evgeny Belyaev .
Applied Intelligence, 2021, 51 :560-570
[46]   A spatio-temporal model for violence detection based on spatial and temporal attention modules and 2D CNNs [J].
Mahmoodi, Javad ;
Nezamabadi-pour, Hossein .
PATTERN ANALYSIS AND APPLICATIONS, 2024, 27 (02)
[47]   Dynamics of Spatio-Temporal Binding in Rats [J].
Malet-Karas, Aurore ;
Noulhiane, Marion ;
Doyere, Valerie .
TIMING & TIME PERCEPTION, 2019, 7 (01) :27-47
[48]   The spatio-temporal profile of multisensory integration [J].
Starke, Johanna ;
Ball, Felix ;
Heinze, Hans-Jochen ;
Noesselt, Toemme .
EUROPEAN JOURNAL OF NEUROSCIENCE, 2020, 51 (05) :1210-1223
[49]   Spatio-Temporal Perturbations for Video Attribution [J].
Li, Zhenqiang ;
Wang, Weimin ;
Li, Zuoyue ;
Huang, Yifei ;
Sato, Yoichi .
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY, 2022, 32 (04) :2043-2056