Buffer loading and chunking in sequential keypressing

Thirty-six participants practiced a task in which they continuously cycled through a fixed series of nine keypresses, each carried out by a single finger (cf. Keele & Summers, 1976). The results of the first experimental phase, the practice phase, support the notion that pauses between successive keypresses at fixed locations induces the development of integrated sequence representations (i.e., motor chunks) and reject the idea that a rhythm is learned. When different sequences were produced in the transfer phase, performance dropped considerably unless the sequence was relatively short and there was ample time for preparation. This demonstrates that motor chunks are content specific and that the absence of motor chunks shows when there is no time for advance loading of the motor buffer or the capacity of the motor buffer is insufficient to contain the entire keypressing sequence

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

Detecting short periods of elevated workload. A compari­son of nine workload assessment techniques

The present experiment tested the merits of 9 common workload assessment techniques with relatively short periods of workload in a car-driving task. Twelve participants drove an instrumented car and performed a visually loading task and a mentally loading task for 10, 30, and 60 s. The results show that 10-s periods of visual and mental workload can be measured successfully with subjective ratings and secondary task performance. With respect to longer loading periods (30 and 60 s), steering frequency was found to be sensitive to visual workload, and skin conductance response (SCR) was sensitive to mental workload. The results lead to preliminary guidelines that will help applied researchers to determine which techniques are best suited for assessing visual and mental workload

The effect of continuous, nonlinearly transformed visual feedback on rapid aiming movements

We investigated the ability to adjust to nonlinear transformations that allow people to control external systems like machines and tools. Earlier research (Verwey and Heuer 2007) showed that in the presence of just terminal feedback participants develop an internal model of such transformations that operates at a relatively early processing level (before or at amplitude specification). In this study, we investigated the level of operation of the internal model after practicing with continuous visual feedback. Participants executed rapid aiming movements, for which a nonlinear relationship existed between the target amplitude seen on the computer screen and the required movement amplitude of the hand on a digitizing tablet. Participants adjusted to the external transformation by developing an internal model. Despite continuous feedback, explicit awareness of the transformation did not develop and the internal model still operated at the same early processing level as with terminal feedback. Thus with rapid aiming movements, the type of feedback may not matter for the locus of operation of the internal model

Learning and Production of Movement Sequences: Behavioral, Neurophysiological, and Modeling Perspectives

A growing wave of behavioral studies, using a wide variety of paradigms that were introduced or greatly refined in recent years, has generated a new wealth of parametric observations about serial order behavior. What was a mere trickle of neurophysiological studies has grown to a more 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 summarize the major results from prominent sequence learning and performance tasks, namely immediate serial recall, typing, 2XN, discrete sequence production, and serial reaction time. These populate a continuum from higher to lower degrees of internal control of sequential organization. The main movement classes covered are speech and keypressing, both involving small amplitude movements that are very amenable to parametric study. A brief synopsis of classes of serial order models, vis-à-vis the detailing of major effects found in the behavioral data, leads to a focus on competitive queuing (CQ) models. Recently, the many behavioral predictive successes of CQ models have been joined by successful prediction of distinctively patterend electrophysiological recordings in prefrontal cortex, wherein 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-is then examined to highlight issues in ongoing attemptes to accomodate a broader range of behavioral and neurophysiological data within a CQ-consistent theory. Important contemporary issues such as the nature of working memory representations for sequential behavior, and the development and role of chunks in hierarchial control are prominent throughout.Defense Advanced Research Projects Agency/Office of Naval Research (N00014-95-1-0409); National Institute of Mental Health (R01 DC02852