Centre for Brain and Cognitive Development, Birkbeck University of London, UK.
Dev Sci. 2013 Sep;16(5):760-71. doi: 10.1111/desc.12064. Epub 2013 May 28.
Young infants have demonstrated a remarkable sensitivity to probabilistic relations among visual features (Fiser & Aslin, 2002; Kirkham et al., 2002). Previous research has raised important questions regarding the usefulness of statistical learning in an environment filled with variability and noise, such as an infant's natural world. In an eye-tracking experiment, 8-month-old infants viewed sequences of spatio-temporal events with three different transitional probabilities (1.0-Deterministic, 0.75-High probability, and 0.5-Low probability). Across two between-subjects conditions, the sequences were presented with or without competing visual distracters. Results show that as transitional probability decreased, infants distributed less attention to the predictable locations and their anticipations were less often correct. With no distraction, infants had faster saccadic latencies to the high probability events; however, with distracters present in the stimulus environment, infants' eye movements shifted to favour the deterministic relations. These findings suggest that infants integrate multiple sources of variability to guide visual attention and facilitate the detection and learning of statistically reliable events.
婴儿在感知视觉特征之间的概率关系方面表现出非凡的敏感性（Fiser 和 Aslin，2002；Kirkham 等人，2002）。先前的研究提出了一些重要的问题，即统计学习在充满变异性和噪声的环境（如婴儿的自然世界）中的有用性。在一项眼动实验中，8 个月大的婴儿观看了具有三种不同转换概率（1.0-确定性、0.75-高概率和 0.5-低概率）的时空事件序列。在两个被试间条件下，序列要么呈现要么不呈现竞争的视觉干扰物。结果表明，随着转换概率的降低，婴儿对可预测位置的注意力分配减少，他们的预期也不太准确。在没有干扰的情况下，婴儿对高概率事件的眼跳潜伏期更快；然而，当刺激环境中存在干扰物时，婴儿的眼球运动就会转移到有利于确定性关系的方向。这些发现表明，婴儿整合了多种来源的变异性，以指导视觉注意力，并促进对统计上可靠事件的检测和学习。
