工作记忆
心理学
感知
认知心理学
认知
任务(项目管理)
相似性(几何)
代表(政治)
特征(语言学)
视觉感受
视觉掩蔽
视觉记忆
短时记忆
匹配(统计)
标志性记忆
心理表征
识别记忆
视觉处理
注意眨眼
视觉搜索
内存错误
感觉记忆
编码(内存)
感觉系统
情景记忆
视觉短时记忆
备忘录
作者
Hongqiao Shi,Qiqi Zhang,Jianguo Zhou,Yue Ding,Yonghui Wang,Ya Li
摘要
Higher level cognition depends on visual working memory (VWM), the ability of the brain to maintain and manipulate internal representations of images that are no longer present. A key question is whether VWM representations are maintained in a sensorylike or an abstract, nonsensory format. While progress has been made in understanding memory-relevant features, the nature of memory-irrelevant features remains less clear. Here, we used a dual-task paradigm to investigate how and when memory-irrelevant features interact with concurrent visual information. Across three experiments, participants performed either a visual search task (Experiment 1) or a perceptual discrimination task (Experiments 2 and 3) involving memory-irrelevant features, while concurrently maintaining another feature for later retrieval. Experiment 1 showed that VWM biases attention toward stimuli matching the memory-irrelevant features, with the magnitude of this bias decreasing monotonically as feature similarity decreased, a pattern consistent with the psychophysical similarity structure in perception. Experiment 2 revealed that memory-irrelevant features bias ongoing perception, as reflected in shifted discrimination thresholds. Experiment 3 further demonstrated that such VWM-biased perceptual effects occur only at short delays and diminish at longer delays. Together, these results provide converging behavioral evidence that the representation of memory-irrelevant features in VWM involves a sensorylike format, whose transient influence on perception reflects the time-limited nature of sensory representations. Overall, these findings advance our understanding of the representational nature of VWM content and shed light on the dynamic interplay between memory and perception in higher level cognition. (PsycInfo Database Record (c) 2026 APA, all rights reserved).
科研通智能强力驱动
Strongly Powered by AbleSci AI