A neurocomputational approach to decision making and aging

Abstract

The adaptive toolbox approach to human rationality analyzes environments and proposes detailed cognitive mechanisms that exploit the structures identified. This paper argues that the posited mechanisms are suitable for implementation as connectionist networks and that this allows (1) integrating behavioral, biological, and information processing levels, an attractive feature of any approach in cognitive science; and (2) addressing developmental issues. These claims are supported by reporting implementations of decision strategies using simple recurrent networks and showing how age differences related to attenuation in cholaminergic modulation can be modeled by lowering the G parameter in these networks. This approach is shown to be productive by deriving empirically testable predictions of age differences in decision making tasks. © Springer-Verlag Berlin Heidelberg 2005.