How are movement sequences represented in the brain? Saul Sternberg did some careful psychophysics experiments that revealed some odd properties of the production of sequences. He had people recite sequences of digits, and he found that the more digits subjects had to produce, (a) the longer the delay was from the ‘go’ signal to when the subject started speaking, and (b) the longer the duration was in the speaking of each digit. You can see this in Figure 1 on page 125 of Sternberg’s famous chapter about the experiments (only read pages 124,125, and the top of 126 of this article):
Sternberg, S., Monsell, S., Knoll, R. L., & Wright, C. E. (1978). The latency and duration of rapid movement sequences: Comparisons of speech and typewriting. In G. E. Stelmach (Ed.), Information processing in motor control and learning (pp. 117-152). New York, NY: Academic Press. (link to pdf of this article)
These results of Sternberg’s experiments can be accounted for by models of sequence production where the actions of a sequence are stored as a spatial pattern (like words on a page), which are then read out, one by one, as a sequence of actions. There are neural models for generating sequences this way, and I will present the first three pages of an article that describes a basic one (only read the first three pages of this article):
Bullock, D. (2004). Adaptive neural models of queuing and timing in fluent action. Trends in Cognitive Sciences, 8(9), 426-433. (link to pdf of this article)
In biological cognition, specialized representations and associated control processes solve the temporal problems inherent in skilled action. Recent data and neural circuit models highlight three distinct levels of temporal structure: sequence preparation, velocity scaling, and state-sensitive timing. Short sequences of actions are prepared collectively in prefrontal cortex, then queued for performance by a cyclic competitive process that operates on a parallel analog representation. Successful acts like ball-catching depend on coordinated scaling of effector velocities, and velocity scaling, mediated by the basal ganglia, may be coupled to perceived time-to-contact. Making acts accurate at high speeds requires state-sensitive and precisely timed activations of muscle forces in patterns that accelerate and decelerate the effectors. The cerebellum may provide a maximally efficient representational basis for learning to generate such timed activation patterns.
Such models have been around for a long time, but, in the main article I’ll be presenting, the authors claim to have evidence that this kind of parallel-to-serial readout process is actually going on in the brain:
Averbeck, B. B., Chafee, M. V., Crowe, D. A., & Georgopoulos, A. P. (2002). Parallel processing of serial movements in prefrontal cortex. Proceedings of the National Academy of Sciences of the United States of America, 99(20), 13172-13177. (link to pdf of this article)
A key idea in Lashley's formulation of the problem of serial order in behavior is the postulated neural representation of all serial elements before the action begins. We studied this question by recording the activity of individual neurons simultaneously in small ensembles in prefrontal cortex while monkeys copied geometrical shapes shown on a screen. Monkeys drew the shapes as sequences of movement segments, and these segments were associated with distinct patterns of neuronal ensemble activity. Here we show that these patterns were present during the time preceding the actual drawing. The rank of the strength of representation of a segment in the neuronal population during this time, as assessed by discriminant analysis, predicted the serial position of the segment in the motor sequence. An analysis of errors in copying and their neural correlates supplied additional evidence for this code and provided a neural basis for Lashley's hypothesis that errors in motor sequences would be most likely to occur when executing elements that had prior representations of nearly equal strength.