Comprehensive exploration of visual working memory mechanisms using large-scale behavioral experiment

Abstract

Abstract Two decades of research on visual working memory have produced substantial yet fragmented knowledge. This study aims to integrate these findings into a cohesive framework. Drawing on a large-scale behavioral experiment involving 40 million responses to 10,000 color patterns, a quasi-comprehensive exploration model of visual working memory, termed QCE-VWM, is developed. Despite its significantly reduced complexity (57 parameters versus 30,796), QCE-VWM outperforms neural networks in data fitting. The model provides an integrative framework for understanding human visual working memory, incorporating a dozen mechanisms—some directly adopted from previous studies, some modified, and others newly identified. This work underscores the value of large-scale behavioral experiments in advancing comprehensive models of cognitive mechanisms.