Analogical transfer in problem solving is a fundamental aspect of human intelligence that involves exploiting knowledge about the solution for one problem to solve another. In order to provide a quantifiable measure of analogical transfer in sequence learning (ATSL), we developed a novel extension of the serial reaction time (SRT) paradigm. To quantify the underlying representational and computational requirements for ATSL we extended a neurobiologically based model of primate prefrontal cortex (PFC) and basal ganglia function in visuomotor sequence learning* to address analogical transfer. We compared the behavior of this model with preliminary data from normal subjects and patients with frontostriatal dysfunction [idiopathic dopa-sensitive Parkinson\’s disease (PD)] in the ATSL paradigm. \