SL-CN: Development of Neural Body Maps

University Of Washington, Seattle WA

Investigators

Abstract

A great deal of research with adults has documented the presence of body maps in the human brain. These neural maps have an organized spatial layout. Neighboring parts of the body are connected in an orderly fashion to areas of the brain that process touch and movement. Body maps are important for many aspect of everyday life including the sense of one's own body and controlling our movements. Body maps also likely play an important role in learning from others, through allowing us to register similarities between ourselves and other people. Despite the importance of body maps, very little is currently understood about how they develop in the early months and years of life. The research supported by this award would provide significant new information on the development of body maps and their relation to early learning. The award supports a collaborative, cross-disciplinary network of investigators who will combine expertise in developmental psychology and infant learning, brain science, cognitive science, computer modelling, and robotics. The proposed network will also support the development and training of junior investigators through specific activities designed to expose them to the benefits of an interdisciplinary approach. Advances in methods for safely measuring the brain activity of human infants are allowing new questions to be asked concerning the role of body maps in early learning. The proposed research involves using magnetoencephalography (MEG) to non-invasively measure responses of the infant brain to tactile stimulation of different parts of the body (e.g., hands vs. feet), and to relate these responses to aspects of infant learning. Another set of studies involving electroencephalography (EEG) will examine how body maps facilitate early imitation and learning from others. Insights from these studies will inform (and be informed by) a further strain of research using computer modelling that takes bodily factors into account in designing robotic systems that can learn from people. The research questions will also provide insight into the control of brain-computer interfaces that can assist disabled individuals in learning to control artificial limbs and other external devices.