Computational approaches to neural reward and development

Despite much progress in brain and cognitive sciences, attempts to connect brain function to cognition are hampered by the large explanatory gap betwe en psychology and neurobiology. In recent years, a neurocomputational persp ective has emerged as the most promising approach to integrating brain and mind. According to this perspective, the brain is a special sort of compute r,a system of many parallel neural networks whose operation underlies cogni tion. In this paper, we present this neurocomputational perspective and exa mine the ways in which this new approach to explaining our mental skills di ffers from earlier ones. In particular, we examine its emerging insights in to two domains. First, we explore the neurocomputational approach to decisi on-making, the adaptive guidance of behavior in the satisfaction of life ma intenance goals. Decisionmaking is central to all mobile creatures in an un certain environment, and this approach reveals a surprising conservation of decisionmaking strategies across many species. We then examine the neuroco mputational approach's new insights into characterizing cognitive developme nt. In particular, this approach offers the new framework of self-organizat ion to characterize the complex interaction between neural developmental pr ograms and the environment, a framework that has important implications for understanding early intervention. (C) 1999 Wiley-Liss, Inc.