Literature DB >> 30778499

[Temporal structure and dynamic neural mechanism in visual attention].

Jian-Rong Jia1,2,3,4, Fang Fang1,2,3,5, Huan Luo1,2,6.   

Abstract

Attention shapes what we see and what we act upon by allocating limited resources to certain parts of visual display in a selective and adaptive manner. While most previous studies in visual attention mainly focused on the attentional distribution over space or features, recent studies have revealed that temporal dynamics also plays a crucial function in visual attention. This paper reviews the representation, function and neural mechanism of temporal dynamics in visual attention from the following four aspects: (1) Tracking dynamic structure of external stimulus by attention; (2) Intrinsic dynamic characteristics of attention; (3) Time-based multiple object representation; (4) Relationship between visual dynamics and classical attentional phenomena. We propose that the dynamic structure and temporal organization are fundamental to visual attention, and the research on it might provide new solutions to many unresolved issues in visual attention research.

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Mesh:

Year:  2019        PMID: 30778499

Source DB:  PubMed          Journal:  Sheng Li Xue Bao        ISSN: 0371-0874


  1 in total

1.  Automatic Identification of Depression Using Facial Images with Deep Convolutional Neural Network.

Authors:  Xinru Kong; Yan Yao; Cuiying Wang; Yuangeng Wang; Jing Teng; Xianghua Qi
Journal:  Med Sci Monit       Date:  2022-07-10
  1 in total

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