Efficient visual exploration in infancy is essential for cognitive and language development. It allows infants to participate in social interactions by attending to faces and learning about objects of interest. Visual scanning of scenes depends on a number of factors, and early differences in efficiency are likely contributing to differences in learning and language development during subsequent years. Predicting language development in diverse samples is particularly challenging, as additional multiple sources of variability affect infant performance. In this study, we tested how the complexity of visual scanning in the presence or absence of a face at 6 to 7 months of age is related to language development at 2 years of age in a multiethnic and predominantly bilingual sample from diverse socioeconomic backgrounds. We used Recurrence Quantification Analysis to measure the temporal and spatial distribution of fixations recurring in the same area of a visual scene. We found that in the absence of a face the temporal distribution of re-fixations on selected objects of interest (but not all) significantly predicted both receptive and expressive language scores, explaining 16% to 20% of the variance. Also, lower rate of re-fixations recurring in the presence of a face predicted higher receptive language scores, suggesting larger vocabulary in infants that effectively disengage from faces. Altogether, our results suggest that dynamic measures, which quantify the complexity of visual scanning, can reliably and robustly predict language development in highly diverse samples. They suggest that selective attending to objects predicts language independently of attention to faces. As eye-tracking and language assessments were carried out in early intervention centres, our study demonstrates the utility of mobile eye-tracking setups for early detection of risk in attention and language development.

婴儿期进行有效的视觉探索对于认知和语言发展至关重要。它允许婴儿通过面对面孔并了解感兴趣的对象来参与社交互动。场景的视觉扫描取决于许多因素，效率的早期差异可能会导致随后几年学习和语言发展的差异。预测不同样本中语言的发展尤其具有挑战性，因为其他多种可变性来源会影响婴儿的表现。在这项研究中，我们测试了来自不同社会经济背景的多种族，主要是双语样本中在6至7个月大时有脸或无脸时视觉扫描的复杂性与2岁时语言发展之间的关系。我们使用递归量化分析来测量在视觉场景的同一区域中重复出现的注视的时间和空间分布。我们发现，在没有面孔的情况下，选定感兴趣对象（但不是全部）上的重新固定的时间分布可以显着预测接受性和表达性语言得分，解释了16％至20％的差异。同样，在面部存在的情况下，较低的重新固定率预示着较高的接受语言得分，这表明有效地与面部脱离接触的婴儿的词汇量较大。总而言之，我们的结果表明，量化视觉扫描复杂度的动态度量可以可靠，可靠地预测高度多样化的样本中的语言发展。他们建议选择性地注意对象可以独立于注意面部来预测语言。由于在早期干预中心进行了眼动追踪和语言评估，因此我们的研究证明了移动眼动追踪装置可用于早期发现注意力和语言发展中的风险。