Abstract

Some argue the common practice of inferring multiple processes or systems from a dissociation is flawed. One proposed solution is state-trace analysis, which involves plotting, across two or more conditions of interest, performance measured by either two dependent variables, or two conditions of the same dependent measure. The resulting analysis is considered to provide evidence that either a single process underlies performance or there is evidence for more than one process. This article reports simulations using the simple recurrent network in which changes to the learning rate produced state-trace plots with multiple functions. We also report simulations using a single-layer error-correcting network that generate plots with a single function. We argue that the presence of different functions on a state-trace plot does not necessarily support a dual-system account, at least as typically defined ; it can also indicate variation in a single parameter within theories generally considered to be single-system accounts.