Elsevier

Human Movement Science

Volume 23, Issue 5, November 2004, Pages 699-746
Human Movement Science

Learning and production of movement sequences: Behavioral, neurophysiological, and modeling perspectives

https://doi.org/10.1016/j.humov.2004.10.008Get rights and content

Abstract

A wave of recent behavioral studies has generated a new wealth of parametric observations about serial order behavior. What was a trickle of neurophysiological studies has grown to a steady stream of probes of neural sites and mechanisms underlying sequential behavior. Moreover, simulation models of serial behavior generation have begun to open a channel to link cellular dynamics with cognitive and behavioral dynamics. Here we review major results from prominent sequence learning and performance tasks, namely immediate serial recall, typing, 2 × N, discrete sequence production, and serial reaction time. These tasks populate a continuum from higher to lower degrees of internal control of sequential organization and probe important contemporary issues such as the nature of working-memory representations for sequential behavior, and the development and role of chunks in hierarchical control. The main movement classes reviewed are speech and keypressing, both involving small amplitude movements amenable to parametric study. A synopsis of serial order models, vis-à-vis major empirical findings leads to a focus on competitive queuing (CQ) models. Recently, the many behavioral predictive successes of CQ models have been complemented by successful prediction of distinctively patterned electrophysiological recordings. In lateral prefrontal cortex, parallel activation dynamics of multiple neural ensembles strikingly matches the parallel dynamics predicted by CQ theory. An extended CQ simulation model – the N-STREAMS neural network model – exemplifies ongoing attempts to accommodate a broad range of both behavioral and neurobiological data within a CQ-consistent theory.

Section snippets

Introduction: A brief history of serial order

Thinking about movement sequences has a long history in behavioral science. Pavlov and other early observers (for a review, see e.g., Adams, 1984) noted that sequences may arise if feedback caused by generating one response triggers the next one. This mechanism has been called stimulus–response reflex chaining or simply response chaining (Bain, 1868, James, 1890). That movement sequences can be performed in the absence of sensory feedback argues against the sufficiency of response chaining.

Sequence learning and performance research: Major active paradigms

We now review major data constraints pertinent to delineating mechanisms responsible for proficient representation and execution of movement sequences, especially short sequences that are known before movement is initiated. Most conceptual models have been developed in the context of a particular task. There are distinct schemes (conceptual models) for handwriting, typing, speech production, and musical performance. These schemes have a mutual resemblance but are often too sketchy to allow

A contemporary (partial) synthesis: The N-STREAMS model

As the foregoing attests, learning and production of serial movements have received much attention from psychological and neuroscience experimentalists as well as modelers. Numerous models have attempted to address relatively specific parts of the data presented above or have explored a single learning mechanism as a basis for serial learning. Very few models have addressed data and neuroanatomical constraints simultaneously. Given the complexity of the picture painted by the data above, it is

Conclusions

The present discussion of research paradigms, tasks and models of skilled sequential motor behavior indicates that people have the capacity to control short sequences as chunks whose elements can be treated collectively, e.g., activated in parallel, during cognitive operations. Such collective treatment may be a necessary condition for hierarchical control, which is further suggested by many of the data and models reviewed. In such hierarchical control, short segments can be processed

Acknowledgments

BJR was supported in part by DARPA/ONR N00014-95-1-0409. DB was supported in part by NIH R01 DC02852. BBA was supported by United States Public Health Service grant NS17413. MPAP gratefully acknowledges the support of the UK Biotechnology and Biosciences Research Council via Grant 310/S15906.

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