Developing expertise in any field usually requires acquisition of a wide range of skills. Most current studies on perceptual learning have focused on a single task and concluded that learning is quite specific to the trained task, and the ubiquitous individual differences reflect random fluctuations across subjects. Whether there exists a general learning ability that determines individual learning performance across multiple tasks remains largely unknown. In a large-scale perceptual learning study with a wide range of training tasks, we found that initial performance, task, and individual differences all contributed significantly to the learning rates across the tasks. Most importantly, we were able to extract both a task-specific but subject-invariant component of learning, that accounted for 38.6% of the variance, and a subject-specific but task-invariant perceptual learning ability, that accounted for 36.8% of the variance. The existence of a general perceptual learning ability across multiple tasks suggests that individual differences in perceptual learning are not “noise”; rather, they reflect the variability of learning ability across individuals. These results could have important implications for selecting potential trainees in occupations that require perceptual expertise and designing better training protocols to improve the efficiency of clinical rehabilitation.

发展任何领域的专业知识通常需要掌握广泛的技能。目前大多数关于感知学习的研究都集中在单一任务上，并得出结论：学习对于训练任务来说是非常特定的，普遍存在的个体差异反映了受试者之间的随机波动。是否存在决定个人在多个任务中的学习表现的一般学习能力仍然很大程度上未知。在一项涉及广泛训练任务的大规模感知学习研究中，我们发现初始表现、任务和个体差异都对任务的学习率有显着影响。最重要的是，我们能够提取特定于任务但与主题无关的学习成分（占方差的 38.6%）和特定于主题但与任务不变的感知学习能力（占方差的 36.8%）。方差。跨多个任务的普遍感知学习能力的存在表明，感知学习中的个体差异并不是“噪音”；而是“噪音”。相反，它们反映了个体学习能力的差异。这些结果可能对选择需要感知专业知识的职业的潜在学员以及设计更好的培训方案以提高临床康复的效率具有重要意义。