Baker Chris I, Olson Carl R, Behrmann Marlene
Center for the Neural Basis of Cognition, Mellon Institute, USA.
Psychol Sci. 2004 Jul;15(7):460-6. doi: 10.1111/j.0956-7976.2004.00702.x.
Statistical learning has been widely proposed as a mechanism by which observers learn to decompose complex sensory scenes. To determine how robust statistical learning is, we investigated the impact of attention and perceptual grouping on statistical learning of visual shapes. Observers were presented with stimuli containing two shapes that were either connected by a bar or unconnected. When observers were required to attend to both locations at which shapes were presented, the degree of statistical learning was unaffected by whether the shapes were connected or not. However, when observers were required to attend to just one of the shapes' locations, statistical learning was observed only when the shapes were connected. These results demonstrate that visual statistical learning is not just a passive process. It can be modulated by both attention and connectedness, and in natural scenes these factors may constrain the role of stimulus statistics in learning.
统计学习作为一种机制被广泛提出,通过该机制观察者学会分解复杂的感官场景。为了确定统计学习的稳健程度,我们研究了注意力和知觉分组对视觉形状统计学习的影响。向观察者呈现包含两个形状的刺激,这两个形状要么由一条线连接,要么不相连。当要求观察者关注形状呈现的两个位置时,统计学习的程度不受形状是否相连的影响。然而,当要求观察者只关注形状的一个位置时,只有当形状相连时才会观察到统计学习。这些结果表明,视觉统计学习不仅仅是一个被动过程。它可以受到注意力和连通性的调节,并且在自然场景中,这些因素可能会限制刺激统计在学习中的作用。