Luthra Sahil, You Heejo, Rueckl Jay G, Magnuson James S
Department of Psychological Sciences, University of Connecticut.
Connecticut Institute for the Brain and Cognitive Sciences.
Cogn Sci. 2020 Dec;44(12):e12917. doi: 10.1111/cogs.12917.
Visual word recognition is facilitated by the presence of orthographic neighbors that mismatch the target word by a single letter substitution. However, researchers typically do not consider where neighbors mismatch the target. In light of evidence that some letter positions are more informative than others, we investigate whether the influence of orthographic neighbors differs across letter positions. To do so, we quantify the number of enemies at each letter position (how many neighbors mismatch the target word at that position). Analyses of reaction time data from a visual word naming task indicate that the influence of enemies differs across letter positions, with the negative impacts of enemies being most pronounced at letter positions where readers have low prior uncertainty about which letters they will encounter (i.e., positions with low entropy). To understand the computational mechanisms that give rise to such positional entropy effects, we introduce a new computational model, VOISeR (Visual Orthographic Input Serial Reader), which receives orthographic inputs in parallel and produces an over-time sequence of phonemes as output. VOISeR produces a similar pattern of results as in the human data, suggesting that positional entropy effects may emerge even when letters are not sampled serially. Finally, we demonstrate that these effects also emerge in human subjects' data from a lexical decision task, illustrating the generalizability of positional entropy effects across visual word recognition paradigms. Taken together, such work suggests that research into orthographic neighbor effects in visual word recognition should also consider differences between letter positions.
视觉单词识别会因存在通过单个字母替换与目标单词不匹配的正字法邻词而得到促进。然而，研究人员通常不会考虑邻词与目标词在何处不匹配。鉴于有证据表明某些字母位置比其他位置更具信息性，我们研究正字法邻词的影响在不同字母位置上是否存在差异。为此，我们量化每个字母位置上的“敌词”数量（即有多少邻词在该位置与目标单词不匹配）。对一项视觉单词命名任务的反应时间数据的分析表明，“敌词”的影响在不同字母位置上存在差异，在读者对即将遇到的字母的先验不确定性较低的字母位置（即熵较低的位置），“敌词”的负面影响最为明显。为了理解产生这种位置熵效应的计算机制，我们引入了一种新的计算模型VOISeR（视觉正字法输入串行阅读器），该模型并行接收正字法输入，并输出随时间变化的音素序列。VOISeR产生的结果模式与人类数据中的结果相似，这表明即使字母不是串行采样的，位置熵效应也可能出现。最后，我们证明这些效应也出现在词汇判断任务的人类受试者数据中，说明了位置熵效应在视觉单词识别范式中的普遍性。综上所述，此类研究表明，对视觉单词识别中正字法邻词效应的研究也应考虑字母位置之间的差异。
