SPEED, ACCURACY AND SERIAL ORDER Speed, Accuracy, and Serial Order in Sequence Production

The production of complex sequences like music or speech requires the rapid and temporally precise production of events (e.g., notes and chords), often at fast rates. Memory retrieval in these circumstances may rely on the simultaneous activation of both the current event and the surrounding context (Lashley, 1951). We describe an extension to a model of incremental retrieval in sequence production (Palmer & Pfordresher, 2003) that incorporates this logic to predict overall error rates and speed/accuracy trade-offs, as well as types of serial ordering errors. The model assumes that retrieval of the current event is influenced by activations of surrounding events. Activations of surrounding events increases over time, such that both the accessability of distant events and overall accuracy increases at slower production rates. The model's predictions were tested in an experiment in which pianists performed unfamiliar music at 8 different tempi. Model fits to speed/accuracy data and to serial ordering errors support model predictions. Parameter fits to individual data further suggest that working memory contributes to the retrieval of serial order and overall accuracy is influenced in addition by motor dexterity and domain-specific skill. Two topics that have dominated research in sequence production are the relationship between accuracy and speed (the speed/accuracy trade-off; Woodworth, 1899) and the way in which events are retrieved from memory in the correct order (the serial order problem; Lashley, 1951). 1 Whereas accuracy and the speed/accuracy trade-off concern the overall likelihood of production errors, p(err), the problem of serial order concerns the likelihood of a given type of error (x) when an error occurs, p(err x | err). Most research has focused exclusively on one of the two issues, despite the fact that both involve a common data source and probably reflect a common processing constraint (cf. MacKay, 1982; 1987). We describe a model in which timing functions as that common constraint (the range model, Palmer & Pfordresher, 2003). The core assumption of the range model is that performers use information about the surrounding context when retrieving events (in music, notes and chords) during sequence production. In other words, events are represented contextually via the pattern of activation strengths across the entire sequence. Activation strengths vary as a function of the serial proximity and similarity of surrounding events to the current event, with the most active surrounding events being those that are proximal and similar. Time constrains the accessibility of events across distances in …