*Three new technologies for the study of child cognition: Examples from language* 

Many long-standing questions in the study of child language and cognition remain elusive because of low signal-to-noise ratios and/or limited ecological validity of traditional empirical methods. Recent technological developments have augmented our toolkit with several measures that promise to enhance our empirical grasp. This talk seeks to inform the audience of the strengths and weaknesses of a selection novel methodologies (in terms of populations, topics, and designs). To be most informative, I center on a single topic: language acquisition in early childhood. This allows me to showcase three such methods, which stand to contribute unique insight into aspects ranging from a description of the spoken input and output, to the neural correlates of language processing. I introduce the method and illustrate its use with recent work from my own as well as other labs.
The first method, LENA, consists of daylong recordings analyzed with largely unsupervised algorithms to provide a unique view of the child's verbal interactions with those around him/her. This is one of a series of emergent methods that try to capture children's behaviors in a naturalistic environment in all their richness, another example being that of head-mounted cameras. The second method involves electronic devices with a touch-screen. As children age, such an active and interactive method is more likely to uniquely engage their attention. Moreover, such a method could eventually allow precise language perception measurements outside the lab. Finally, fNIRS is an inexpensive neuroimaging technique, reputed to combine accurate localization of activations and a considerable resistance to movement artifacts. While the technique itself is far from new, its application to the description of brain networks involved in language perception and production, and cognition in general, remains relatively novel.