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Imitating Unfamiliar Sequences of Connected Linear Motions

¹Volen Center for Complex Systems, Brandeis University, Waltham; and ²Cognitive and Neural Systems, Boston University, Boston, Massachusetts

Submitted 8 April 2005; accepted in final form 9 July 2005

A fundamental challenge in neuroscience is to understand the mechanisms by which multicomponent actions are represented and sequenced for production. We addressed this challenge with a movement-imitation task in which subjects viewed the quasi-random, two-dimensional movements of a disc and then used a stylus to reproduce the remembered trajectory. The stimulus disc moved along straight segments, which differed sufficiently from one another that it was possible to trace individual segments' fate in the resulting movement imitation. A biologically based segmentation algorithm decomposed each imitation into segments whose directions could be compared with those of homologous segments in the model. As the number of linked segments in a stimulus model grew from three to seven, imitation became less accurate, with segments more likely to be deleted, particularly from a model's final stages. When fidelity of imitation was assessed segment by segment, the resulting serial position curves showed a strong primacy effect and a moderate recency effect. Analysis of pairwise transposition errors revealed a striking preponderance of exchanges between adjacent segments that, along with the serial position effects, supports a competitive queuing model of sequencing. In analogy to results with verbal serial recall, repetition of one directed segment in the model reduced imitation quality. Results with longer stimulus models suggest that the segment-by-segment imitation generator may be supplemented in the final stages of imitation by an error-signal driven overlay that produces a late-course, real-time correction. Results are related to neural mechanisms that are known to support sequential motor behavior and working memory.