The facilitating effect of Chinese character linguistic knowledge on working memory updating.

Information representations in working memory (WM) decay rapidly over time. Although phonological rehearsal partially compensates for this decay of memory traces, the extent to which WM updating benefits from linguistic knowledge and whether this benefit is independent of phonological rehearsal strategies remains unclear. This study addressed this question using two progressive experiments. Experiment 1 employed a verbal N-back task (1-back and 2-back) to compare WM updating performance between real and pseudo-characters. Results showed that real characters elicited significantly shorter reaction times than pseudo-characters in the 2-back task, with no difference observed in the low-load 1-back task. This indicates that task load modulates the facilitating effect of linguistic knowledge. Experiment 2 disrupted phonological rehearsal ability through forced numerical repetition, after which the performance between stimulus types was compared. Results showed that real characters demonstrated higher accuracy than pseudo-characters in 1-back and 2-back tasks, confirming the memory stability advantage of linguistic knowledge. Additionally, real characters exhibited shorter reaction times than pseudo-characters in the 2-back task. The facilitating effect of Chinese language knowledge on WM updating is not entirely dependent on phonological rehearsal strategy. This finding reveals that knowledge representations (particularly semantic knowledge) serve as key modulators of WM updating, offering new insights and empirical support for refining WM theories. Public significance statement. This study explored how linguistic knowledge affected working memory (WM) updating during Chinese-character processing. This indicates that familiar characters boost memory performance under a high cognitive load, even when phonological rehearsals are disrupted. This finding reveals that knowledge representations are key modulators of WM updating, offering new insights and empirical support for refining WM theories.