A paper by Assistant Professor Masataka Nakayama and colleagues, entitled “Verbal Working Memory, Long-Term Knowledge, and Statistical Learning,” has been published in the online version of Current Directions in Psychological Science.

A paper by Assistant Professor Masataka Nakayama and colleagues, entitled “Verbal Working Memory, Long-Term Knowledge, and Statistical Learning,” has been published in the online version of Current Directions in Psychological Science.

The mental function of temporarily storing information is called working memory, and it plays a central role in various cognitive functions. In particular, many studies have shown that verbal working memory plays an important role in language operation and acquisition.

In this paper, Assistant Professor Masataka Nakayama, Professor Satoru Saito (Graduate School of Education, Kyoto University) and Specially Appointed Assistant Professor Yuki Tanida (United Graduate School of Child Development, Osaka University, as of the writing of this paper) reviewed findings of verbal working memory, long-term knowledge and statistical learning, and showed the following things:    

There are three types of linguistic long-term knowledge: (1) element-to-element association knowledge, (2) position–element knowledge, and (3) whole-sequence knowledge (e.g., word-form). This paper discussed how statistical learning is involved in each type. They showed the possibility that the first two would be a basis for fluent and efficient language usage, and the third would be a basis for vocabulary learning.

The publication criteria for Current Directions in Psychological Science includes that an article should introduce the latest findings to researchers outside the field and be useful as a material for psychology classes in English-speaking countries. Namely, authors are expected to contribute broadly to academic communication.

Saito, S., Nakayama, M., & Tanida, Y. (2020). Verbal Working Memory, Long-Term Knowledge, and Statistical Learning. Current Directions in Psychological Science, https://doi.org/10.1177/0963721420920383

2020/08/05