心理学
模式(遗传算法)
认知心理学
刺激(心理学)
情绪性
识别记忆
认知
计算机科学
社会心理学
神经科学
机器学习
作者
Yueyue Xiao,Aiqing Nie
标识
DOI:10.3390/jintelligence11070130
摘要
Previous studies have confirmed that different degrees of expectation, including the bipolarity of the expected and unexpected, as well as an intermediate level (no expectation), can affect memory. However, only a few investigations have manipulated expectation through experimentally established schema, with no consideration of how expectation impacts both item and source memory. Furthermore, stimulus emotionality may also impact memory. Therefore, we conducted a study to investigate the effects of three levels of expectation on item and source memory while considering the impact of stimulus emotionality. The experiment began with a phase dedicated to learning the rules. In the subsequent study phase, negative and neutral words were manipulated as expected, no expectation, and unexpected, based on these rules. This was followed by tasks focused on item and source memory. The study found that there was a "U-shape" relationship between expectation and item memory. Additionally, the study revealed the distinct impacts of expectation on item and source memory. When it came to item memory, both expected and unexpected words were better remembered than those with no expectations. In source memory, expected words showed memory inferiority for expectation-irrelevant source information, but an advantage for expectation-relevant source information. Stimulus emotionality modulated the effect of expectation on both item and source memory. Our findings provide behavioral evidence for the schema-linked interactions between medial prefrontal and medial temporal regions (SLIMM) theory, which proposes that congruent and incongruent events enhance memory through different brain regions. The different patterns between item and source memory also support dual-process models. Moreover, we speculate that processing events with varying levels of emotionality may undermine the impact of expectation, as implied by other neural investigations.
科研通智能强力驱动
Strongly Powered by AbleSci AI