Departmental Colloquium: Richard Aslin (Haskins Lab): Learning and attention in infants: The importance of prediction in development
"Learning and attention in infants: The importance of prediction in development"
I will review three lines of research from my lab that have implications for the normative course of development and for the diagnosis of deficits or delays in development among special populations. (1) Statistical learning is a rapid form of implicitly extracting information from the environment. It has been shown to be robustly present in infants, children, and adults. Children with Specific Language Impairment and adults with Autism Spectrum Disorder show different patterns of statistical learning. It may, therefore, serve as both a diagnostic tool and as a potential mechanism that underlies some developmental disorders. (2) The allocation of attention to gather information via statistical learning is controlled by both low-level stimulus salience and by predictive mechanisms. Infants allocate their attention to visual and auditory events so that they ignore both overly simple and overly complex information, while focusing mostly on information of medium complexity. Deviations from this normative pattern of allocating attention may contribute to some developmental disorders. (3) The infant brain must make predictions about upcoming stimuli. We have shown using a brain imaging technique called functional near-infrared spectroscopy (fNIRS) that an auditory cue can predict a visual stimulus, and even in the absence of the visual stimulus this prediction will elicit a brain response in the visual cortex. A follow-up study of prematurely born infants revealed that this brain signature of prediction is absent, despite these at-risk infants (tested at their corrected age) showing predictions at the behavioral level.