Experience and the Development of Perceptual-Motor Systems
Richard N. Aslin
One of the classic questions in development is the nature-nurture debate that has occupied philosophers, psychologists, and biologists for several centuries. Although no-one believes that development is controlled entirely by the genes or by the environment, there are various gradations of influence that particular researchers assign to each end of this continuum. Two modern issues in this debate are how one would determine the relative importance of genetic and environmental influences in development, and when different influences predominate during development. By manipulating the type and timing of experiential inputs during development (either experimentally or by studying unusual circumstances that occur outside strict experimental control), one can better define the constraints that operate in controlling the course of development.
I am generally interested in the processes and mechanisms that lead to development of sensory, perceptual, motor, and cognitive abilities in human infants. One of the overriding themes of my research is the role experience plays in development. In some domains, such as auditory sensitivity and motion perception, experience seems to play a rather minor role unless there is complete deprivation of experience during early postnatal life. In other domains, such as oculomotor control and speech perception, experience plays a more important role by enabling the infant to acquire specific abilities necessary for particular skills or languages.
My most recent work has been directed to the rapid learning of sequences of events. This statistical learning enables adults, children, and infants to group sounds based solely on the distributional information (conditional probabilities) contained within the sound stream. It also enables adults (and perhaps infants, as we will see in future work) to segment and group visual features in scenes and visuo-motor responses during a sequential reaction time task. Finally, with Marc Hauser at Harvard, we have shown that the statistical learning of speech streams operates in tamarin monkeys. All of these examples of unsupervised statistical learning illustrate that it is likely to play and important role in many domains, with more specialized (and highly constrained) forms of learning building on these domain- and species-general mechanisms.