Assessing Memory Representation

Assessment at the Intended Motor Control Level

Both sets of investigators evaluated memory representation below the level of response selection, in which the memory representation is purported to be selected in typical information processing motor control models (see Section 4.2.1). Chamberlin and Magill (1992b) assessed AE and VE, which are errors in performance evaluated at the level of motor execution (the final stage in the model of motor control). Error values in motor learning tasks describe the general pattern of performance over time (Schmidt & Lee, 2005; Schmidt & Wrisberg, 2004; Schmidt, 1988); however, AE and VE values are not sensitive at distinguishing memory representations at different hierarchical levels.

Crump and Logan (2010) employed response time as their dependent variable; however, reaction time was not differentiated from movement time. Thus, it is unknown if the response time reflected processing during response selection or at the response programming stage of motor control. Crump and Logan also placed emphasis on their ISKI assessments as an estimate of “sequential control during online response execution” (p. 663). Although measuring the

interkeystroke intervals between letters may be useful in understanding how the response programming and execution levels of motor control interact, it is not a direct assessment of the memory representation at the response selection stage. Thus, for both sets of investigators ascription of their results to either an instance or schema memory representation is invalid as an assessment evaluating memory selection was not implemented.

The assessments conducted by Chamberlin and Magill (1992b) and Crump and Logan (2010) are not unusual within the realm of motor control research (see Section 4.2.2). However, assessments of response selection could be implemented in future studies interested in evaluating motor memory representation. Event-related potentials (ERP) evaluate temporal processing characteristics of motor commands within an information processing control hierarchy, and results suggest early ERP components (e.g., N-40) may be involved in response selection (e.g., Carbonnell et al., 2013; Vidal, Burle, Grapperon, & Hasbroucq, 2011; Vidal, Grapperon, Bonnet, & Hasbroucq, 2003). Reaction times, when differentiated from movement times, may also provide an indirect evaluation of response selection during recognition tasks. Recognition tasks include identifying a single trained item (during an old-new judgment task) or several trained items amidst foils (during a forced choice recognition task), and retrieval characteristics associated with trained stimuli provide insight into memory retrieval (Hall, 1989; Radvansky, 2006). Evaluation of reaction times across untrained stimuli varying in similarity (characteristic of instance-based learning) and motor class (characteristic of rule-based learning) in a recognition task may also provide insight into the underlying memory representation being retrieved.

Assessment of Trained Stimuli versus Prior Knowledge

It is unclear in any of the experiments reviewed what effect prior knowledge may have had on the transfer tasks. This issue is not explicitly addressed by either set of investigators. However, the two-phase design of the experiments described suggests the training phase encoded specific memories for the training stimuli, and these memories (not prior stored memories) were to be compared to the untrained stimuli in the transfer phase of the experiment. Unfortunately, it is

the Chamberlin and Magill experiments may have been familiar to participants prior to the experiment. Familiar tactile and visual components of movement may activate previously learned knowledge, which may increase the accuracy and speed of motor responses (e.g., Magill, 1998; D. L. Wright, Shea, Li, & Whitacre, 1996; D. L. Wright & Shea, 1991). Thus, the uniform transfer results noted in Chamberlin and Magill’s study may have been the result of previously learned arm movements, and not based solely on movements trained during the experiment. If the trained arm movements were controlled for novelty (i.e., to differentiate them from previously learned arm movements) the results would be purer in their attribution of motor learning occurring during the experiment. This distinction becomes important if memory representations evolve as the result of experience and skill acquisition (e.g., J. R. Anderson et al., 2004; Logan, 1988; Tomporowski, 2003). This will be discussed further in the next section.

The results of Crump and Logan’s second experiment (Transfer Block Two) may have also been modulated by prior knowledge. The only difference between Experiment One and Two was the keyboard employed during data collection. The standard QWERTY keyboard in the second experiment may have provided participants with tactile cues to initiate well-learned typing sequences, increasing generalization between Transfer Blocks One and Two. Additionally, the effect of prior knowledge on the stimuli was uncontrolled. Crump and Logan only controlled for word frequency in their stimuli; however, the effects of high frequency bi- and trigram units may have increased typing speeds (D. R. Gentner, Larochelle, & Grudin, 1988). Complete control of prior knowledge within an experiment is impossible; however, experimental controls may be instituted to decrease the overall likelihood of prior knowledge impacting results. For example, reconstruction of the different stimuli sets with novel bi- or

trigram units may have decreased potential frequency effects, and yielded a better estimate of how trained stimuli compare to untrained stimuli in Crump and Logan’s experiments.

Effect of Training Amount

The amount of training required varied across experiments, with the participants in Chamberlin and Magill’s (1992b) study practicing twice as much as participants in Crump and Logan (2010) study. Additionally, the distribution of practice varied: multiple sessions (Chamberlin and Magill) versus a single session (Crump and Logan). It is unknown what, if any effect, these training amounts and practice schedules may have had on the trained memory representations. Skill acquisition theories vary in how memory representations evolve with experience. For example, some schema theories suggest memory representations are refined with practice (e.g., J. R. Anderson et al., 2004; Schmidt, 1975), whereas some instance-theories suggest different aggregation strategies are employed (computational versus automatic strategies; Logan, 1988).

A dual-representation model may be another potential explanation, in which an instance- representation may be encoded early in training, but evolves into a more rule-based representation as a skill becomes well-learned. Given the differences in motor tasks in the reviewed experiments, a dual-representation model is not an appropriate explanation for the varied learning theories attributed to each investigator’s results. However, it may provide a potential model to examine further in future studies. For example, evaluating recognition probes of trained and untrained stimuli at specific training intervals (e.g., 250, 500, 750, and 1000 trials) may provide insight into how the trained memory representation may be evolving with practice.

Chamberlin and Magill and Crump and Logan were not interested in the effects of training, and assumed the training phase of their experiment resulted in a well-learned baseline

variability noted with simple and complex motor tasks involving the limbs (as reviewed in: Magill, 2001; Schmidt & Lee, 2005), controlling for the effects of training in future studies should aid the interpretation of transfer effects. One way to control for training amount is to implement an accuracy criterion to determine the end of training versus relying on a set number of repetitions or trials. By instituting an accuracy criterion, individual variability in performance is controlled as all participants are anticipated to initiate the transfer phase of the experiment with the same “baseline” performance level based on the accuracy criterion.