心理与行为研究 ›› 2011, Vol. 9 ›› Issue (1): 45-52.

• 论文 • 上一篇    下一篇

The Emergence of Adaptive Eye-Movement Control in Reading: Theory and Data

Erik D. Reichle1,Yanping Liu1,Patryk A. Laurent2   

  1. 1 University of Pittsburgh;
    2 The Johns Hopkins University
  • 收稿日期:2010-11-27 出版日期:2011-03-20 发布日期:2011-03-20

The Emergence of Adaptive Eye-Movement Control in Reading: Theory and Data

Erik D. Reichle1,Yanping Liu1,Patryk A. Laurent2   

  1. 1 University of Pittsburgh;
    2 The Johns Hopkins University
  • Received:2010-11-27 Online:2011-03-20 Published:2011-03-20
  • Supported by:
    Erik Reichle, University of Pittsburgh, 635 LRDC, 3939 O'Hara St; , Pittsburgh, PA, 15260; or via e-mail to: reichle@pitt; edu; The work described in this article was supported by an NIH R01 grant(HD053639) that was awarded to the first author and an award from the Chinese Scholarship Council to the second author

摘要: Computational models of eye-movement control during reading provide precise quantitative descriptions of the perceptual, cognitive, and motoric processing that guide readers′ eyes, but are based on numerous equivocal a priori theoretical assumptions. This article describes an alternative approach to understanding eye-movement control: Using reinforcement learning to examine how complex eye-movement behaviors emerge from the requirement to identify words rapidly in the context of known psychological and physiological constraints(e.g., limited visual acuity). An example simulation is reported, as are key results from an fMRI experiment that demonstrates that structures implicated in reinforcement learning support the learning of eye-movement behavior in humans.

Abstract: Computational models of eye-movement control during reading provide precise quantitative descriptions of the perceptual, cognitive, and motoric processing that guide readers′ eyes, but are based on numerous equivocal a priori theoretical assumptions. This article describes an alternative approach to understanding eye-movement control: Using reinforcement learning to examine how complex eye-movement behaviors emerge from the requirement to identify words rapidly in the context of known psychological and physiological constraints(e.g., limited visual acuity). An example simulation is reported, as are key results from an fMRI experiment that demonstrates that structures implicated in reinforcement learning support the learning of eye-movement behavior in humans.