计算机科学
统计学习
知识管理
心理学
数据科学
业务
数学教育
人工智能
作者
Luzi Xu,Chris Paffen,Stefan Van der Stigchel,Surya Gayet
标识
DOI:10.31219/osf.io/yb7cn
摘要
Statistical learning is a powerful mechanism that enables the rapid extraction of regularities from sensory inputs. Although numerous studies have established that statistical learning serves a wide range of cognitive functions, it remains unknown whether statistical learning impacts conscious access. To address this question, we applied multiple paradigms in a series of experiments (N = 153 adults): Two reaction-time-based breaking continuous flash suppression (b-CFS) experiments showed that probable objects break through suppression faster than improbable objects. A preregistered accuracy-based b-CFS experiment showed higher localization accuracy for suppressed probable (versus improbable) objects under identical presentation durations, thereby excluding the possibility of processing differences emerging after conscious access (e.g., criterion shifts). Consistent with these findings, a supplemental visual-masking experiment reaffirmed higher localization sensitivity to probable objects over improbable objects. Together, these findings demonstrate that statistical learning alters the competition for scarce conscious resources, thereby potentially contributing to established effects of statistical learning on higher-level cognitive processes that require consciousness.
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