KDI: Statistical Learning and Its Constraints

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Both humans and non-human primates show remarkable learning abilities. However, these abilities are often limited to certain domains, developmental periods, or behavioral contexts. For example, nearly all humans acquire one or more complex linguistic systems-that is, languages -- but not all humans acquire complex musical systems. Similarly, non-human primates are exceptionally adept at learning to forage for and categorize different types of food, but are severely limited in acquiring complex communication systems. Also, both humans and non-human primates appear to learn best in several domains during early periods of development. Thus, learning is nearly always characterized by specializations, rather than by general-purpose mechanisms. Understanding the constraints on learning will contribute to basic research, by accounting for domain- and species-specializations, and to applied research, by refining our understanding of which domains, ages, and contexts are optimal for humanlearners.The goal of the present research project is to explore the ability of human adults, children, infants, and non-human primates (Tamarins) to learn rapid sequential events. A prime example of a rapid sequential event is language, in which sounds are combined to form words, and words are combined to form sentences. Recent findings have demonstrated that human adults and infants can rapidly extract and remember very detailed 'statistics' of linguistic input, such as the frequency and probability that one syllable will follow another. In our proposed research, we will employ miniature artificial 'languages' which simulate some of the structural properties of natural languages, but which can be built with equivalent structures across different domains (speech sequences, tone sequences, visual sequences, motor sequences). At issue is the facility humans and non-human primates show for the extraction of statistical structure from these different learning materials. Are they equally sensitive to the distributions of elements and higher order structure in the materials? Do learning abilities differ across learners of different ages and species, and across different structures and domains?In addition to behavioral experiments with humans and non-human primates, a series of computational studies will allow us to investigate the formal properties of learning mechanisms, in order to ask what architectural and neural differences might underlie such differences in learning abilities. What kinds of computational architectures can learn the types of regularities and patterns that human infants learn? Is the inability of adults or non-human primates to learn some types of complex sequential events due to the absence of a learning device specialized for that domain, or could small differences in computation and/or memory lead to large differences in learning outcome?