We present a neural network model that shows how the prefrontal cortex, interacting with the basal ganglia, can maintain a sequence of phonological information in activation-based working memory (i.e., the phonological loop). The primary function of this phono(cid:173) logical loop may be to transiently encode arbitrary bindings of information necessary for tasks - the combinatorial expressive power of language enables very flexible binding of essentially ar(cid:173) bitrary pieces of information. Our model takes advantage of the closed-class nature of phonemes, which allows different neural rep(cid:173) resentations of all possible phonemes at each sequential position to be encoded. To make this work, we suggest that the basal ganglia provide a region-specific update signal that allocates phonemes to the appropriate sequential coding slot. To demonstrate that flexi(cid:173) ble, arbitrary binding of novel sequences can be supported by this mechanism, we show that the model can generalize to novel se(cid:173) quences after moderate amounts of training.