EAGER: COLLABORATIVE RESEARCH: Developmental mechanisms of perception and language in the infant brain

了解婴儿对他们在世界上遇到的物体和单词的理解一直是发育科学的一个重要目标，但该领域对婴儿如何执行这两项任务的了解相对较少。有几种神经成像方法被用来确定成年人的大脑是如何识别熟悉的物体和单词的，但这些方法中的大多数都不适合用于婴儿。这个研究项目的目标是部署两种适用于婴儿的神经成像方法，作为一种新的方式来深入了解3到12个月大的婴儿的基本大脑机制，使其能够识别物体和理解单词。其中一项技术是脑电图（EEG），它通过头皮上的传感器测量大脑产生的电活动。另一种是功能性近红外光谱（fNIRS），它将近红外光照射颅骨，并测量大脑每个部位对其的吸收情况，以此作为大脑该部位活跃程度的指标。在婴儿观看和听刺激时记录这两项测量将为婴儿大脑如何处理这些信息提供重要的见解。脑电图已用于婴儿多年，而功能近红外光谱（fNIRS）是一种相对较新的非侵入性神经成像技术，非常适合用于婴儿。与fMRI一样，fNIRS提供了大脑局部区域代谢活动的特征，但更适合婴儿，因为它通过一个紧密的帽子将光传递到头皮上。在这个项目中，EEG和fNIRS将用于测量婴儿在观看各种类别的物体（如车辆或家具）或听他们知道或不知道的单词（或无意义的单词）时大脑中的电和代谢活动。关键的分析工具是一套来自计算机科学领域的机器学习算法，它采用脑电图或近红外光谱信号来确定这些信号的哪些组成部分最能预测婴儿所看到或听到的内容。拟议的研究结果将定位于大脑中视觉物体和口语编码发生的地方，以及刺激发生后的处理时间。由于方法上的挑战，这些是对象和语言处理的基本方面，无法在人类婴儿中进行研究。建立分析这两种方法产生的数据的协议将有助于为未来的婴儿大脑研究提供分析技术。确定婴儿大脑中这些加工机制的规范特性，将为未来研究发育中的大脑如何受到早期经验变化、损伤后补偿和各种遗传异常的影响奠定基础。

Understanding what infants understand about objects and words that they encounter in the world has been an important goal in developmental science, but the field understands relatively little about how infants perform either of these two tasks. Several neuroimaging methods have been used to determine how adult brains recognize familiar objects and words, but most of these methods are not suitable for use with infants. The goal of this research project is to deploy two neuroimaging methods that are amenable for use with infants, as a novel way to gain insights into the fundamental brain mechanisms that enable object recognition and word understanding in 3- to 12-month-old infants. One technique, electroencephalography (EEG) involves measuring electrical activity generated by the brain from sensors on the scalp. The other, functional near-infrared spectroscopy (fNIRS), shines near-infrared light through the skull and measures how it is absorbed by the brain at each location as an index of how active that part of the brain is. Recording both these measures while infants watch and listen to stimuli will provide important insights into how the infant brain processes this information.EEG has been in use with infants for many years, whereas functional near-infrared spectroscopy (fNIRS) is a relatively newer non-invasive neuroimaging technique ideally suited for use with infants. fNIRS, like fMRI, provides a signature of metabolic activity in localized regions of the brain but is more suitable for infants because it delivers light to the scalp via a tight-fitting cap. In this project, EEG and fNIRS will be used to measure electrical and metabolic activity in the brain as infants watch objects of various categories such as vehicles or furniture, or listen to words that they know or do not know (or nonsense words). The key analysis tool is a suite of machine-learning algorithms from the field of computer science that take the EEG or fNIRS signals to determine which components of these signals best predict, on a trial by trial basis, what the infant was seeing or hearing.The outcome of the proposed research will localize in the brain where encoding of visual objects and spoken words takes place and over what time period after stimulus onset that processing occurs. These are fundamental aspects of object and language processing have eluded study in the human infant because of methodological challenges. Establishing protocols for analyzing data generated by these two methods will contribute to analytic techniques available for future infant brain research. Identifying normative properties of these processing mechanisms in the infant brain will set the stage for future research investigating how the developing brain is affected by variations in early experience, by compensation after injury, and by a variety of genetic anomalies.