Ansteeg Lukas, Leoné Frank, Dijkstra Ton
Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, Nijmegen, Netherlands.
Front Psychol. 2022 Aug 11;13:945094. doi: 10.3389/fpsyg.2022.945094. eCollection 2022.
Collecting human similarity judgments is instrumental to measuring and modeling neurocognitive representations (e.g., through representational similarity analysis) and has been made more efficient by the multi-arrangement task. While this task has been tested for collecting semantic similarity judgments, it is unclear whether it also lends itself to phonological and orthographic similarity judgments of words. We have extended the task to include these lexical modalities and compared the results between modalities and against computational models. We find that similarity judgments can be collected for all three modalities, although word forms were considered more difficult to sort and resulted in less consistent inter- and intra-rater agreement than semantics. For all three modalities we can construct stable group-level representational similarity matrices. However, these do not capture significant idiosyncratic similarity information unique to each participant. We discuss the potential underlying causes for differences between modalities and their effect on the application of the multi-arrangement task.
收集人类相似度判断对于测量和建模神经认知表征(例如,通过表征相似性分析)至关重要,并且多排列任务使其效率更高。虽然该任务已被用于收集语义相似度判断,但尚不清楚它是否也适用于单词的语音和正字法相似度判断。我们扩展了该任务以包括这些词汇模态,并比较了不同模态之间以及与计算模型的结果。我们发现可以针对所有三种模态收集相似度判断,尽管单词形式被认为更难排序,并且与语义相比,评分者之间和评分者内部的一致性较低。对于所有三种模态,我们都可以构建稳定的组级表征相似性矩阵。然而,这些矩阵并未捕获每个参与者独特的显著特质相似性信息。我们讨论了不同模态之间差异的潜在根本原因及其对多排列任务应用的影响。