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

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 x 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-a-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.     

Concatenating familiar movement sequences: the versatile cognitive processor

Earlier studies demonstrated that practicing a series of key presses in a fixed order yields memory representations (i.e., motor chunks) that can be selected and used for sequence execution as if familiar key pressing sequences are single responses. In order to examine whether these motor chunks are robust in different situations and whether preparation for one sequence may overlap with execution of another one, two experiments were carried out in which participants executed two highly practiced keying sequences in rapid succession in response to two simultaneously presented stimuli. The results confirmed robustness of motor chunks, even when the sequences included only two elements, and showed that preparation (and in particular, selection) of a forthcoming sequence may occur during execution of the earlier sequence. Sequences including only two keys appeared to be slowed more by concurrent preparation than longer sequences. Together these results suggest that the execution of familiar keying sequences is predominantly carried out by a dedicated motor processor, and that the cognitive processor can be allocated to preparing a forthcoming sequence (e.g., during execution of an earlier sequence) or, some times, to selecting individual sequence elements in parallel to the motor processor.     

Motor skill learning in the middle-aged: limited development of motor chunks and explicit sequence knowledge

The present study examined whether middle-aged participants, like young adults, learn movement patterns by preparing and executing integrated sequence representations (i.e., motor chunks) that eliminate the need for external guidance of individual movements. Twenty-four middle-aged participants (aged 55–62) practiced two fixed key press sequences, one including three and one including six key presses in the discrete sequence production task. Their performance was compared with that of 24 young adults (aged 18–28). In the middle-aged participants motor chunks as well as explicit sequence knowledge appeared to be less developed than in the young adults. This held especially with respect to the unstructured 6-key sequences in which most middle-aged did not develop independence of the key-specific stimuli and learning seems to have been based on associative learning. These results are in line with the notion that sequence learning involves several mechanisms and that aging affects the relative contribution of these mechanisms.     

Learning a keying sequence you never executed: Evidence for independent associative and motor chunk learning

A substantial amount of research has addressed how people learn and control movement sequences. Recent results suggested that practice with discrete key pressing sequences results in two types of sequence learning: associative learning and motor chunk development (Verwey & Abrahamse, 2012). In the present study, we addressed whether in keying sequences of limited length associative learning develops also when the use of the chunking mode is prevented by introducing during practice random deviants. In line with the notion of two different learning mechanisms, the present results indicate that associative sequence learning develops when motor chunks cannot be developed during practice. This confirms the notion that motor chunks do not rely on these associations. In addition, experience with a particular execution mode during the practice phase seems to benefit subsequent use of that mode with unfamiliar and random sequences. Also, participants with substantial video-gaming experience were faster in executing discrete keying sequences in the chunking mode. These last two results may point to the development of a general ability to produce movement sequences in the chunking mode.     

Representations underlying skill in the discrete sequence production task: effect of hand used and hand position

Various studies suggest that movement sequences are initially learned predominantly in effector-independent spatial coordinates and only after extended practice in effector-dependent coordinates. The present study examined this notion for the discrete sequence production (DSP) task by manipulating the hand used and the position of the hand relative to the body. During sequence learning in Experiment 1, in which sequences were executed by reacting to key-specific cues, hand position appeared important for execution with the practiced but not with the unpracticed hand. In Experiment 2 entire sequences were executed by reacting to one cue. This produced similar results as in Experiment 1. These experiments support the notion that robustness of sequencing skill is based on several codes, one being a representation that is both effector and position dependent.     

Nonlinear visuomotor transformations: locus and modularity

Participants in two experiments moved a mouse-like device to the right to move a cursor on a computer screen to a target position. The cursor was invisible during motion but reappeared at the end of each movement. The relationship between the amplitudes of the cursor movement and the mouse movement was exponential in Experiment 1 and logarithmic in Experiment 2 for two groups of participants, while it was linear for the control groups in both experiments. The results of both experiments indicate that participants adjusted well to the external transformation by developing an internal model that approximated the inverse of the external transformation. We introduce a method to determine the locus of the internal model. It indicates that the internal model works at a processing level that either preceded specification of movement amplitude, or had become part of movement amplitude specification. Limited awareness of the nonlinear mouse-cursor relationship and the fact that a working-memory task had little effect on performance suggest that the internal model is modular and not dependent on high-level cognitive processes.     

Processing modes and parallel processors in producing familiar keying sequences

Recent theorizing indicates that the acquisition of movement sequence skill involves the development of several independent sequence representations at the same time. To examine this for the discrete sequence production task, participants in Experiment 1 produced a highly practiced sequence of six key presses in two conditions that allowed little preparation so that interkey intervals were slowed. Analyses of the distributions of moderately slowed interkey intervals indicated that this slowing was caused by the occasional use of two slower processing modes, that probably rely on independent sequence representations, and by reduced parallel processing in the fastest processing mode. Experiment 2 addressed the role of intention for the fast production of familiar keying sequences. It showed that the participants, who were not aware they were executing familiar sequences in a somewhat different task, had no benefits of prior practice. This suggests that the mechanisms underlying sequencing skills are not automatically activated by mere execution of familiar sequences, and that some form of top-down, intentional control remains necessary.     

A clinical comparative study evaluating the effect of epilepsy versus ADHD on timed cognitive tasks in children.

Both children with epilepsy and children with ADHD may be characterized by slowing on reaction-time measurement. This is of particular interest, as neuropsychological assessment is often requested in the differential diagnosis between children with short non-convulsive epileptic seizures and children with ADHD. In this study we attempt to identify patterns of impairment on timed tasks that are specific for epilepsy, relative to ADHD. This study was an open, controlled parallel-group clinical investigation which included two groups of patients: 60 children with ADHD and 60 children with epilepsy. These children were compared with a control group (n=30) on two types of timed cognitive tasks: tasks with low information load (simple reaction-time measurement) and tasks with high information load (multiple decision reaction-time measurement). The simple reaction-time measurements show significant differences between ADHD and controls (all except for visual RT non-dominant hand) and between epilepsy and controls (only one test). No significant differences were found between epilepsy and ADHD. The two tests with high information load show significant slowing compared with the controls for epilepsy on the Binary Choice Reaction-Time Test and for ADHD on the Visual Searching Test. On both tests also the differences between epilepsy and ADHD are significant. The two tests in combination have a relatively satisfactory potential to classify the children with ADHD (75% correct classification) and the children with epilepsy (55% correct classification). We may conclude that complex reaction-time tests (i.e., timed tasks with high information load) have potential for assessing the differential impact of ADHD and epilepsy on attentional function. These tasks specifically reveal general slowing for children with epilepsy and slowing as an effect of failures of inhibitory self control on unstructured tasks for ADHD.     

Redundant sensory information does not enhance sequence learning in the serial reaction time task

In daily life we encounter multiple sources of sensory information at any given moment. Unknown is whether such sensory redundancy in some way affects implicit learning of a sequence of events. In the current paper we explored this issue in a serial reaction time task. Our results indicate that redundant sensory information does not enhance sequence learning when all sensory information is presented at the same location (responding to the position and/or color of the stimuli; Experiment 1), even when the distinct sensory sources provide more or less similar baseline response latencies (responding to the shape and/or color of the stimuli; Experiment 2). These findings support the claim that sequence learning does not (necessarily) benefit from sensory redundancy. Moreover, transfer was observed between various sets of stimuli, indicating that learning was predominantly response-based.     

A Clinical Comparative Study Evaluating the Effect of Epilepsy Versus Adhd on Timed Cognitive Tasks in Children

Both children with epilepsy and children with ADHD may be characterized by slowing on reaction-time measurement. This is of particular interest, as neuropsychological assessment is often requested in the differential diagnosis between children with short non-convulsive epileptic seizures and children with ADHD. In this study we attempt to identify patterns of impairment on timed tasks that are specific for epilepsy, relative to ADHD. This study was an open, controlled parallel-group clinical investigation which included two groups of patients: 60 children with ADHD and 60 children with epilepsy. These children were compared with a control group (n =30) on two types of timed cognitive tasks: tasks with low information load (simple reaction-time measurement) and tasks with high information load (multiple decision reaction-time measurement). The simple reaction-time measurements show significant differences between ADHD and controls (all except for visual RT non-dominant hand) and between epilepsy and controls (only one test). No significant differences were found between epilepsy and ADHD. The two tests with high information load show significant slowing compared with the controls for epilepsy on the Binary Choice Reaction-Time Test and for ADHD on the Visual Searching Test. On both tests also the differences between epilepsy and ADHD are significant. The two tests in combination have a relatively satisfactory potential to classify the children with ADHD (75% correct classification) and the children with epilepsy (55% correct classification). We may conclude that complex reaction-time tests (i.e., timed tasks with high information load) have potential for assessing the differential impact of ADHD and epilepsy on attentional function. These tasks specifically reveal general slowing for children with epilepsy and slowing as an effect of failures of inhibitory self control on unstructured tasks for ADHD.