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LATER模型可预测阅读过程中的扫视潜伏期分布。

LATER predicts saccade latency distributions in reading.

作者信息

Carpenter R H S, McDonald Scott A

机构信息

The Physiological Laboratory, University of Cambridge, Downing Street, Cambridge, CB2 3EG, UK.

出版信息

Exp Brain Res. 2007 Feb;177(2):176-83. doi: 10.1007/s00221-006-0666-5. Epub 2006 Sep 15.

DOI:10.1007/s00221-006-0666-5
PMID:16977449
Abstract

When saccades are evoked by suddenly presented visual stimuli, the stochastic distribution of their reaction times is typically recinormal, in conformity with the LATER model of decision-making, sometimes with an additional sub-population of early responses. In the real world, saccades are more often spontaneous responses to static features of the visual world; nevertheless, the time between the end of one saccade and the start of the next may be regarded as a reaction time to the new image that is presented to the retina. The distribution of these times is qualitatively similar to that of evoked saccades, but typically with a longer median and more of the early responses. Here, we analyse the statistical distributions of fixation times from a large database of spontaneous saccades made while reading and show that the distributions are altered in characteristic ways by particular features of the current fixation: likely familiarity of the currently fixated word, and its proximity to the preceding fixation. These alterations are of the kind predicted by LATER: familiarity appears to influence the mean rate at which the decision signal approaches completion, whereas proximity to the previous fixation, presumably because it provides partial prior information about the upcoming word, appears to increase prior probability. We conclude that spontaneous saccades may be successfully described by the same decision-making model that can be used for evoked ones.

摘要

当通过突然呈现的视觉刺激诱发眼跳时,其反应时间的随机分布通常呈重正态分布,符合决策的LATER模型,有时还会有一个额外的早期反应亚群体。在现实世界中,眼跳更多是对视觉世界静态特征的自发反应;然而,一次眼跳结束到下一次眼跳开始之间的时间可被视为对呈现给视网膜的新图像的反应时间。这些时间的分布在性质上与诱发眼跳的分布相似,但通常中位数更长且早期反应更多。在此,我们分析了一个阅读时自发眼跳的大型数据库中注视时间的统计分布,并表明这些分布会因当前注视的特定特征而以特征性方式改变:当前注视单词的可能熟悉程度及其与前一次注视的接近程度。这些改变是LATER模型所预测的那种:熟悉程度似乎会影响决策信号接近完成的平均速率,而与前一次注视的接近程度,大概是因为它提供了关于即将出现单词的部分先验信息,似乎会增加先验概率。我们得出结论,自发眼跳可以用与诱发眼跳相同的决策模型成功描述。

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