Shari Liu - US grants

How is the human brain organized to learn and reason about the world during development? Although young infants show behavioral signs of surprise (e.g. longer looking) at unexpected stimuli (e.g. upon hearing a completely new word, seeing an object float in midair, or seeing a person perform an inefficient action) (Gergely & Csibra, 2003; Saffran, Aslin, & Newport, 1996; Spelke, Breinlinger, Macomber, & Jacobson, 1992; Spelke & Kinzler, 2007), the neural systems that support their expectation and surprise are not accessible through measurements of behavior. In this proposal, we use an infant-friendly, non-invasive neuroimaging technique, functional near-infrared spectroscopy (fNIRS), to investigate the neural systems that allow infants and adults to form expectations and detect violations of those expectations across different situations. We test the hypotheses that sensory cortex encode task- and modality specific information during learning, that lateral prefrontal cortex (LPFC) detects subsequent violations of those expectations, and that LPFC drives attention towards the surprising stimulus. If so, we should find differentiated sensory activity during learning across tasks, but overlapping LPFC activity during surprise in those tasks, which should in turn predict behavior. Aim 1 tests these predictions using learning tasks, wherein people form new expectations in the lab (e.g. about which word, 'doti' or 'lado', is more likely to come from a newly learned artificial language) (Marcus, 1999; Saffran et al., 1996). Aim 2 investigates the same predictions in tasks requiring prior expectations about objects (that they're solid), people (that they behave rationally), and probability (that randomly drawn samples tend to be representative of the population) (Gergely & Csibra, 2003; Spelke et al., 1992; Spelke & Kinzler, 2007; Xu & Garcia, 2008). Aim 3 compares the neural systems that allow people to learn new expectations (Aim 1) and reason using prior expectations (Aim 2). Across all aims, we will test infants and adults in multiple tasks (e.g. one task involving people, another involving objects), compare neural activity during learning and surprise in those tasks, and use this neural activity to predict behavior. The proposed research takes an innovative, cross-disciplinary approach to push the frontiers of our theories of how the brain is organized to enable such rapid and rich learning across development. Its findings will reveal (1) which regions of the brain are implicated in forming expectations and having those expectations violated, (2) whether those cortical regions support a general, broad process of belief formation or task- and modality-specific learning, and (3) how they modulate behavior in infants and adults. Thus, this work has the potential to transform our understanding of how infants learn and reason in and out of the lab. To know how to nurture learning and reasoning, during both typical and atypical development, we need a causal theoretical understanding of how learning and reasoning work in the mind and brain. This work takes strides towards this goal by providing benchmarks and measures for designing and evaluating targeted educational and parenting interventions.