Constraints on Visual Statistical Learning in Infancy

描述（由申请人提供）：视觉统计学习是识别视觉特征之间概率共现模式的过程，这对于我们感知世界是可预测和稳定的能力至关重要。拟议的实验将首次全面检查婴儿对视觉序列和布局中复杂统计模式的检测，描述 2 至 14 个月婴儿对概率信息的计算。这是感知和认知发展的形成时期，其特征是环境结构的感知和学习的快速发展变化。特别是，实验将检验如何 结构变异性、认知负荷和记忆限制影响学习，情境线索如何影响学习 促进或阻碍这种学习，以及这种学习的成果是否可以推广到不同的环境。此外，实验还将通过检查空间信息对视觉统计学习的具体贡献来提供领域特异性的关键测试。拟议研究的短期目标是了解感知和认知技能的发展如何促进早期发展，以识别统计定义的模式。长期目标是阐明认知发展理论，通过计算观察概率为归纳学习奠定核心作用。这项研究的结果可能对了解可能面临缺铁性贫血和自闭症谱系障碍等发育障碍风险的儿童的发育产生影响，这两种疾病都被认为是内隐学习缺陷。这样一个 了解可能会导致比目前可用的评估工具更适合早期诊断和治疗。

DESCRIPTION (provided by applicant): Visual statistical learning is the process of identifying patterns of probabilistic co-occurrence among visual features, essential to our ability to perceivethe world as predictable and stable. The proposed experiments will provide the first comprehensive examination of infants' detection of complex statistical patterns in visual sequences and layouts b describing computation of probabilistic information by infants from 2 to 14 months. This is a formaive time in perceptual and cognitive development characterized by rapid developmental change in perception and learning of environmental structure. In particular, the experiments will examine how structural variability, cognitive load, and memory limitations affect learning, how contextual cues facilitate or impede this learning, and whether the products of such learning can be generalized toa different setting. In addition, the experiments will provide critical tests of domain-specificity b examining the specific contributions of spatial information to visual statistical learning. The shot-term objectives of the proposed research are to learn how developing perceptual and cognitive skills intract in early development to identify statistically defined patterns. The long-term goals are to clarifytheories of cognitive development that posit a central role for inductive learning by computing probabilitie of observations. The results of this research may have implications for understanding development in children who may be at risk for developmental disorders such as iron-deficiency anemia and autism spectrum disorders, both of which have been characterized as deficits in implicit learning. Such an understanding may lead to assessment tools more closely tailored to early diagnosis and treatment than are presently available.