Cognitive architectures such as ACT-R and EPIC are being applied to human factors research problems with increasing frequency. However, it is unclear whether such systems can model continuous motor tasks that were once staples in the field but have since been largely displaced by more cognitively-oriented problems. Recent research on a challenging continuous motor control task has revealed interesting patterns in skill acquisition that appear compatible with the learning mechanisms present in ACT-R. However, what was not clear was whether ACT-R could model expert performance in a high-frequency motor control task. Unmodified, ACT-R could not. However, by making some small changes in ACT-R's motor system and capitalizing on ACT-R's ability to imagine visual objects, ACT-R was able to achieve expert-level performance in this task. Whether ACT-R will be able to mirror the skill acquisition data is still an open question. Copyright 2010 by Human Factors and Ergonomics Society, Inc. All rights reserved.