Imitation of Multi-Component Movement Sequences

Yigal Agam
Volen Center for Complex Systems
Brandeis University

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.