Working Memory Training Transfer-CaiLab-202309
Whether and how the effect of working memory (WM) training can transfer to untrained tasks has been under intensive debate. Few studies have clarified training transfer boundaries or distinguished sources of training improvements. In our study, we trained participants with a delayed estimation task for locations and systemically tested its transfer boundaries with three types of untrained WM tasks: tasks with the same paradigm and changed stimuli (i.e., delayed estimation tasks for colors and letters), tasks with changed paradigms with the same stimuli (i.e., complex span and n-back tasks for locations), and tasks with combined changes in paradigms and stimuli (e.g., a complex span task for colors). We found decreased recall errors in both the trained task and the delayed estimation task for colors. In particular, among the participants with larger training improvements, we observed transfers in both the color delayed estimation task and the location complex span task but not in the color complex span task or others. These results indicated that training could transfer to tasks with either stimuli or paradigm changes, but there was an extra transfer boundary for tasks with combined changes. Furthermore, we adapted model fittings to estimate WM quantity and quality separately in delayed estimation tasks for locations (trained) and colors (untrained). Our results revealed that both increased WM quantity and quality contributed to the recall improvement in the trained task, and individuals with lower baseline gained larger training benefits. For the untrained task, we found that the recall improvement was underlain by increased quality and an optimized quality-quantity trade-off strategy. Additionally, participants’ baseline performance positively predicted the transfer benefit. Our findings suggested that training improved the stimulus-specific WM resource and optimized the paradigm-specific WM strategy. These results extended our understanding of WM training transfers and shed light on future studies.
Humanities and Social Science Fund of Ministry of Education of China
Open Research Fund of the State Key Laboratory of Cognitive Neuroscience and Learning
Research of Basic Discipline for the 2.0 Base of Top-notch Students Training Program
National Natural Science Foundation of China