Advertisement

Abstract

Background and Purpose: Random practice of motor tasks has been shown to enhance motor learning. The purpose of this study was to investigate the effects of task practice order (random, blocked) on motor learning in adults with Parkinson disease (PD).

Subjects: Twenty adults with mild PD and 20 age-matched adults (controls) participated in the study.

Methods: Participants in both groups (PD and control) practiced 3 movement tasks with either a blocked or a random practice order. This 2 participant group × 2 practice order design resulted in 4 experimental groups. The Trail Making Test was administered to all participants to determine task-switching capability. Motor performance on the arm movement tasks was quantified on the basis of the root-mean-square error difference between the goal movement task and each participant's response.

Results: The task-switching capability of the control group was superior to that of the PD group. For acquisition, in general, participants in the control group performed with significantly less error than participants in the PD group. For retention, participants in the control group who practiced with a random order performed more accurately than participants in the control group who practiced with a blocked order. However, for the PD group, the findings were reversed; participants who practiced with a blocked order performed more accurately than participants who practiced with a random order. These findings resulted in a group × practice order interaction.

Discussion and Conclusion: These pilot study data suggest that, contrary to the findings for age-matched control learners, for learners with mild PD, a blocked practice order may be better than a random practice order for motor learning.

The capability to acquire motor skills requires both cognitive (eg, strategy formation and task elaboration) and motor processes.16 The cognitive demands for motor learning refer to the mental processes involved in decision making, which include anticipation, planning, regulation, and interpretation of motor performance.4 An understanding of these cognitive processes can inform the translation of motor learning principles into rehabilitative protocols, especially for populations with accompanying cognitive deficits. Likewise, the recently proposed challenge point framework7 (CPF) suggested that effective motor learning evolves from an interaction of task and learner characteristics that, together with a specific practice condition, creates a level of functional task difficulty that determines how much information will be available for motor learning.

The CPF emerged from a long-held view that motor learning is a problem-solving process and that the information available during and after each attempt to solve the problem is encoded and forms the basis for learning. The CPF predicts that the skill level of learners affects how learners respond to certain motor practice conditions. For example, a practice condition that typically enhances motor learning for adults without disabilities through greater information processing might degrade motor learning for adults who have information-processing deficits, such as adults with Parkinson disease (PD).

Effects of Parkinson Disease on Motor Learning Capability

Parkinson disease is a progressive degenerative neurologic disorder that is associated with malfunctioning of the basal ganglia and that affects more than 1.5 million Americans.8 The cardinal deficits of PD, such as tremor, limb rigidity, bradykinesia, delayed movement initiation, and hypometric movement, provide evidence of the important role that the basal ganglia play in motor behavior.913 With their elaborate and widespread feedback circuits, the basal ganglia are thought to influence specific cognitive processes as well.1418 For example, people with PD demonstrate difficulty performing 2 or more different tasks that are presented in a nonrepetitive fashion (hereafter referred to as “task switching”).14,1922 An important requirement for successful task switching is the capability to represent a task internally and to update task set information (ie, assign the appropriate rules that govern mapping between stimuli and responses).23 For instance, people with PD have more difficulty learning sequential tasks that require a switch from one sequence element to the next. They often exhibit prolonged movement duration for each element of a sequence compared with that for isolated elements.13,2426 The prolongation of movement duration during element switching suggests that people with PD have deficits in updating appropriate task set information. In summary, although the motor symptoms of PD are the most obvious symptoms, a comprehensive assessment usually includes a combination of instruments sensitive to motor and cognitive deficits.3,2729

One of the goals of rehabilitation is to maximize and prolong the benefits reaped during therapy. To achieve this goal, scientifically informed and evidenced-based therapy is important. The degree to which PD-related cognitive and motor deficits affect motor learning capability is not well understood. In this pilot project, we focused on the effects of a specific practice condition, task practice order, on motor learning in people with mild PD.

Effects of Task Practice Order on Motor Skill Learning

The order in which motor tasks are practiced (eg, blocked and random) has been shown to influence a learner's retention of those tasks (ie, the definition of motor learning). The phenomenon that random-order practice (eg, C-A-B, A-B-C, B-C-A, with each letter representing a different task) generally benefits motor learning more than blocked-order practice (eg, A-A-A, B-B-B, C-C-C), even when the numbers of tasks and trials are controlled, is known as the contextual interference effect.30,31 One interpretation of the contextual interference effect is that random-order practice requires more cognitive processing during the acquisition phase than blocked- or repetitive-order practice.3037 This added cognitive load is more challenging, as predicted by the CPF, and thus is thought to provide a long-term benefit for learning.6,36,38 The CPF also predicts that random-order practice might not benefit motor learning for people whose memory and cognitive flexibility in switching between tasks are impaired.

Performance Change May Not Reflect Learning

In a classic study of the contextual interference effect, Shea and Morgan31 demonstrated that participants performed with more errors during acquisition under a random-order practice condition than under a blocked-order practice condition. However, immediate and delayed tests of retention were performed much better by those who had practiced under the random-order practice condition. These findings highlight the well-known learning-performance distinction and emphasize that not all immediate changes during the acquisition phase can be assumed to reflect relatively permanent changes in behavior, defined as learning. The learning-performance distinction is analogous to what one might see in the clinic when a patient is able to perform a motor task very well, but that performance does not persist after the patient goes home. Furthermore, a patient may not be able to generalize or transfer the clinic performance to functional daily activities in the home. Consequently, performance during the acquisition phase may not be an effective representation of motor learning; motor learning is best assessed by performance during retention (relatively permanent change in behavior) tests.

This study was designed to test the CPF by manipulating both the challenge level of the practice condition (ie, blocked-order practice is considered to be less challenging than random-order practice) and the relative skill level of the learner (ie, people who have mild PD and who exhibit measurable motor and cognitive deficits can be considered to be less skilled than age-matched people without disabilities [controls]) in the process of learning 3 motor tasks. We hypothesized that motor learning in people with a task-switching deficit, as is characteristic of PD, would not benefit as much, if at all, from a random-order practice condition compared with that of age-matched control subjects. Our long-term goal is to identify an optimal task practice order for people with mild PD. This pilot project is the first step along that research continuum, with the primary aim being to provide pilot data for determining the effects of blocked-order practice and random-order practice on motor learning in people with mild PD.

Method

Participants

Twenty participants with mild PD (age [X̄±SE]=65.0±12 years) (Tab. 1) and 20 age-matched but not sex-matched control participants (age=63.1±11 years) were enrolled in the study. All participants gave written informed consent. Participants with PD were recruited from the Movement Disorders Clinic at the University of Southern California Healthcare Consultation Center and the Parkinson Support Group in the Los Angeles, Sherman Oaks, and Long Beach areas. Participants with PD were recruited first and were assigned randomly to 1 of 2 practice conditions by choosing 1 of a set of predefined cards from an envelope containing 10 cards marked with R (random) and 10 cards marked with B (blocked). The control group was a sample of convenience from spouses, family members, and the adjacent community. We attempted to match age and sex between the control and PD groups as closely as possible. However, we did not attempt to match these characteristics between the practice condition groups (eg, blocked versus random for participants with PD). Participants were excluded if they had any acute medical problems, motor fluctuations, uncorrected vision loss, history of admission to a psychiatric hospital within the preceding 3 years, or a score of less than 28 on the Mini-Mental State Examination (MMSE).39 The motor subscale of the Unified Parkinson Disease Rating Scale (UPDRS) was used to assess the motor capability of the participants. Participants with PD were recruited if they were within 3 years of the diagnosis of PD (diagnosis confirmed by a board-certified neurologist), were optimally medicated, and had only mild illness, classified with the modified Hoehn-Yahr scale40 as stage I or II.

Table 1.

Baseline Characteristics of Participants With Parkinson Disease (PD) and Age-Matched Control Participantsa

Instrumentation and Tasks

All participants used their dominant arm to practice the movement task. The movement task was to grasp the handle of a lever and move it horizontally over a table at the correct speed and distance to replicate a goal movement task, which was displayed on the computer screen before each trial. Three versions of the movement task were used, each with a different variation of a discrete arm movement composed of 2 extension-flexion reversal actions (Fig. 1A). A lightweight lever affixed to a frictionless vertical axle was attached to a table and positioned parallel to the floor. A handle at the end of the lever was adjusted to accommodate the participant's forearm. A linear potentiometer was attached to the transducer at the base of the vertical axle. Signals from the transducer were converted to a digital signal by the analog-to-digital board of a Compaq 466v computer* and sampled at 1,000 Hz. The Template software program41 was applied to manipulate the movement task, the interval duration, and data storage from each trial for off-line analyses. Figure 1B shows a schematic of the event timing for each trial, including the goal movement task, go signal, and postresponse feedback presentation.

Figure 1.

(A) Representation of the 3 target movement tasks. (B) Timeline of each event of a single trial in milliseconds. FB=feedback. (C) Example of the feedback display. The participant's response is superimposed on the target task. The root-mean-square error (RMSE) is displayed along with the trajectories after each trial for feedback.

During the acquisition phase, participants were presented with feedback after each movement trial. The feedback included an overall error score (ie, the root-mean-square error [RMSE], representing the difference between the goal movement task and each participant's response) and a graphic representation of the participant's response superimposed on the goal movement task (Fig. 1C). All participants received written instructions and additional verbal information about the total number of trials that they would practice and approximately how long it would take to finish the experiment.

Experimental Design and Procedure

A 2 participant group (control, PD) × 2 practice order (blocked, random) between-factor design was implemented. This overall design resulted in 4 experimental groups: PD-blocked practice (PDB), PD-random practice (PDR), control-blocked practice (CB), and control-random practice (CR). Testing took place over 2 consecutive days; the acquisition phase took place on day 1, and the retention phase took place on day 2. The 3 movement tasks were practiced in either a blocked order or a random order for a total of 135 trials. During blocked practice, each task was practiced for 45 trials, and the three 45-trial sets were counterbalanced across participants. During random practice, the 3 movement tasks were randomized within each 45-trial set; the randomization scheme was the same for both random-practice groups.

Motor learning was assessed with retention tests on day 2. There were 2 no-feedback 15-trial retention tests, 1 with blocked-order task presentation and the other with random-order task presentation. This retention design was used to ensure that the condition of the retention test would not bias the outcome by not favoring either practice order. Retention test order was counterbalanced across participants. Another measure of motor learning is the amount of “forgetting,” which is indicated by the difference between performance in the last block of the acquisition phase and performance in the retention phase. Therefore, a group analysis was performed for forgetting, which was defined as the difference between performance in block 9 and performance in each retention test (ie, blocked retention test and random retention test).

Task-Switching Capability Test

The Trail Making Test was used to assess task-switching capability.42 The Trail Making Test, a reliable and valid measure of distributed attention,43,44 has been used by other researchers4449 to assess task-switching capability in people with PD. The test has 2 distinct parts. In part A, the participant is instructed to draw by connecting numbers from 1 to 25 randomly spread across a sheet of paper. The objective is to connect the numbers in order, beginning with 1 and ending with 25, as quickly and as accurately as possible while being timed by the investigator. Part B is more complex in that it requires the participant to connect numbers and letters in an alternating pattern (eg, 1-A-2-B-3-C) while being timed. The performance times between part A and part B were compared between groups to test for differences in the cognitive capacity for task switching. The Trail Making Test was chosen to measure how participants would perform when they were required to switch from one task to another, either infrequently (as in blocked-order practice) or frequently (as in random-order practice).

Data Analysis

Motor skill learning was evaluated with a global performance accuracy measure (RMSE) (Fig. 1C) calculated separately for 2 experimental phases: acquisition and delayed retention phases. The RMSE is the average difference between the goal movement task and the participant's response calculated over the participant's total movement time.6,50,51 Individual RMSE data were grouped into 15-trial blocks for the acquisition phase (blocks 1–9) and 15-trial blocks for the retention phase (blocked retention test and random retention test).

Full-model analysis including all 4 experimental groups was conducted separately for the acquisition and retention phases. For the acquisition data, the mean RMSE was analyzed with a 2 group (PD, control) × 2 practice order (blocked, random) × 9 block (15 trials per block) analysis of variance (ANOVA) for repeated measures on the acquisition block. Separate analyses were performed for the retention blocks with a 2 group (PD, control) × 2 practice order (blocked, random) ANOVA on the 15-trial block mean RMSE.

Because this pilot project was not powered adequately for the full model, we conducted within-group (PD and control) analyses with the same design and separately for the acquisition and retention phases. The latter are considered to be exploratory analyses useful for informing the next study in this series. Post hoc analyses of main effects and interactions were carried out with pair-wise comparisons, corrected with the Bonferroni method to control for an inflated type I error. Independent 2-sample t tests were conducted to compare group means for demographic characteristics, baseline RMSE (acquisition block 1), total RMSE change score for the acquisition phase (ie, block 1 − block 9), and Trail Making Test difference score (ie, part B − part A). Effect size (ES) was used to estimate the magnitude of between-group differences and can be meaningful in pilot studies when sample sizes are small. The ES was reported according to established criteria as small (<0.41), medium (0.41–0.70), or large (>0.70).52 For all statistical tests, the significance level was set at P<.05. SPSS version 13.0 statistical software was used for all statistical analyses.

Results

Baseline Demographics, Memory, and Task-Switching Capability

Within (blocked, random) and between (PD, control) participant group mean comparisons for age, sex, memory, Trail Making Test scores, Hoehn-Yahr stages, and UPDRS motor subscale scores are summarized in Table 1. Within-group comparisons showed that there were no significant differences in age, sex, and MMSE scores between blocked practice and random practice for the PD and control groups. The baseline Hoehn-Yahr stages, UPDRS motor subscale scores, and Trail Making Test scores were not significantly different between the PDB and PDR groups. There were no significant differences between the control and PD groups for age, sex, and MMSE scores. The average difference in performance times between part A and part B of the Trail Making Test was significantly higher for participants with mild PD than for age-matched control participants (P=.05) (Tab. 1). The individual demographic information for participants with PD is summarized in Table 2.

Table 2.

Demographic Information for Participants With Parkinson Disease (PD)a

The motor performance results are presented first for the full model including all 4 experimental groups, separately for the acquisition and retention phases; retention phase results are reported separately for the blocked and random retention tests. Within-group analyses are presented next with the same reporting structure.

Full Model: Group, Practice Order, and Interaction

Acquisition phase.

Figure 2A shows the group means for both the acquisition and the retention trial blocks for the control groups (CB and CR) and the PD groups (PDB and PDR). Each group showed improvement in performance accuracy, resulting in a block main effect for the RMSE (P<.001). These findings indicated that each group benefited from task practice. Throughout the acquisition phase, there were marked differences between the control groups and the PD groups. Participants with PD performed with greater error than control participants, resulting in a group main effect (P=.04). This difference was not attributable to differences in baseline performance (block 1, P=.483). A post hoc analysis revealed that there was no significant group × block interaction (P=.13).

Figure 2.

Block means for root-mean-square error (RMSE). (A) All 4 groups: control-blocked (CB), control-random (CR), Parkinson disease (PD)-blocked (PDB), and PD-random (PDR). (B) Control (CON) groups. (C) PD groups. Blocks 1–9 represent the acquisition phase; blocks BR (blocked retention test) and RR (random retention test) represent the day 2 retention tests. Error bars=SEMs. For group comparisons, P<.05.

There was a tendency for participants who practiced under the random-order condition to be less accurate than those who practiced under the blocked-order condition; indeed, there was a significant practice order × block interaction (P=.049). In general, participants in blocked-order practice groups showed greater accuracy across the acquisition phase than participants in random-order practice groups.

There was no group × practice order interaction (P=.13); however, to confirm the greater importance of practice order than of group (PD versus control), we conducted a post hoc analysis to compare change scores across the acquisition blocks (ie, difference between block 1 RMSE and block 9 RMSE) for each group (Fig. 3). There was a significant main effect for practice order (P=.019) but not for group, suggesting that participants with PD responded to blocked and random practice orders in a fashion similar to that of control participants.

Figure 3.

Magnitude of change in root-mean-square error (RMSE) across acquisition phase (blocks 1–9) for control (CON) groups (A) and Parkinson disease (PD) groups (B): control-blocked (CB), control-random (CR), PD-blocked (PDB), and PD-random (PDR). Change score=RMSE for block 1 − RMSE for block 9. Error bars=SEMs.

Retention phase.

Participants with PD were less accurate (Fig. 2A) than control participants in the blocked retention test. However, the group main effect did not reach significance (P=.158). Consistent with previous literature,3037 control participants who practiced under the random-order condition demonstrated better retention performance (mean RMSE=17.5) (Fig. 2B) than those who practiced under the blocked-order condition (mean RMSE=21.6). The ES (0.94) was large, but the within-group t test comparison was not significant (P=.08). The results of interest are shown in Figure 4A; all 4 practice groups are shown for comparison. Participants in the 2 blocked-order practice groups (PDB and CB) performed with similar accuracies. However, the retention performance of participants in the PDR group was significantly less accurate than that of participants in the CR group. The ANOVA revealed a significant group × practice order interaction effect (P=.045). Post hoc testing revealed that the locus of the interaction was between CR and PDR (P=.032) and not between CB and PDB (P=.662).

Figure 4.

Group mean root-mean-square error (RMSE) for delayed retention phase by group: control-blocked (CB), control-random (CR), Parkinson disease (PD)-blocked (PDB), and PD-random (PDR). (A) Blocked retention test. (B) Random retention test. *For group comparisons, P<.05.

Similar to the results obtained for the blocked retention test, participants with PD were less accurate (Fig. 2A) than control participants in the random retention test. However, the main effect for group was not significant (P=.08). For practice order, control participants who practiced under the random-order condition demonstrated better performance (Fig. 2B) than those who practiced under the blocked-order condition. The ES (.54) was medium, but the within-group t test comparison was not significant (P=.24). The full-model comparison of retention test results is shown in Figure 4B for all 4 practice groups. Participants in the 2 blocked-order practice groups (PDB and CB) performed with similar accuracies. The retention performance of participants in the PDR group was significantly less accurate than that of participants in the CR group. However, the ANOVA did not yield a significant group × practice order interaction effect (P=.217). Post hoc testing revealed no significant difference between the CR and PDR groups (P=.08, ES=.83) or between the CB and PDB groups (P=.662). However, the large ES for the difference between the CR and PDR groups suggested that with a larger sample, this difference would be detected. Therefore, both random and blocked retention test findings provide support for the notion that random-order practice is not beneficial for motor skill retention in people with PD.

Changes between end of acquisition and retention (forgetting).

The task practice order affected forgetting differentially for the PD and control groups. Random practice reduced forgetting for control participants (for the difference between the CB and CR groups, P=.003) (Fig. 2B) but not for participants with PD (for the difference between the PDB and PDR groups, P=.913) (Fig. 2C). These findings suggested that participants with PD did not benefit from random practice to the same extent as age-matched control subjects.

Within-Group Model Comparisons: Control Groups

Acquisition phase.

Figure 2B shows the group means for both the acquisition and the retention trial blocks for the 2 control groups (CB and CR). Practice under the blocked-order condition resulted in better acquisition performance than practice under the random-order condition; the performance of participants in the CB group appeared to improve relatively more than that of participants in the CR group in the acquisition phase (P=.096). Despite the lack of a significant difference between the CB and CR groups in the magnitude of improvement (Fig. 3A), the large ES (0.84) suggested that the between-group difference would be detected with a larger sample.

Retention phase.

Control participants who practiced under the random-order condition appeared to demonstrate better retention performance than those who practiced under the blocked-order condition (P=.08, ES=0.94) (Fig. 2B). Although the difference was not statistically significant, the large ES suggested that a larger sample would be needed to detect this group difference. There was no significant difference in retention performance between the 2 control groups (P=.24, ES=0.54).

Changes between end of acquisition and retention (forgetting).

The older adults who practiced under the random-order condition demonstrated less forgetting than those who practiced under the blocked-order condition (for the difference between block 9 performance and blocked retention test performance, P=.003; for the difference between block 9 performance and random retention test performance, P=.075, ES=0.94) (Fig. 2B).

Within-Group Model Comparisons: PD Groups

Acquisition phase.

The performance of participants in the PDR group was consistently less accurate than that of participants in the PDB group (Fig. 2C). Visual inspection suggested that participants in the PDR group showed less improvement than participants in the PDB group (ES=0.8) (Fig. 3B), but the difference was not significant (P=.09).

Retention phase.

Participants with PD did not benefit from random-order practice (Fig. 2C). Participants with PD who practiced under a random-order condition did not perform better than those who practiced under a blocked-order condition in the blocked retention test (P=.212, ES=0.62). Similar to the results obtained in the blocked retention test, the results of the random retention test suggest that participants with PD who practiced under the random-order condition did not perform better than those who practiced under the blocked-order condition (P=.49).

Changes between end of acquisition and retention (forgetting).

The amounts of forgetting were similar in participants with PD whether they practiced under a blocked-order condition or a random-order condition (Fig. 2C). The amounts of forgetting between the last acquisition block and each retention test were similar between participants in the PDB group and those in the PDR group (Fig. 2C), suggesting that participants in the PD groups did not benefit from random practice to the same extent as age-matched control subjects.

Discussion

This theory-driven pilot study was based on the CPF. We manipulated both the challenge level of task practice (blocked- and random-order practice) and the relative skill level of the learner (participants with PD and age-matched control participants) in the process of motor learning. We aimed to determine whether random-order practice, known to benefit motor learning in young adults without disabilities, can be generalized to people with a specific task-switching impairment, in this case, mild PD. Our findings suggest that the benefits of random-order practice can be generalized to older adults learning a set of discrete arm movements but not to older adults who have mild PD and who also demonstrate task-switching deficits.

The CPF describes how task difficulty, learner skill level, and the effects of various practice conditions interact in motor performance and motor learning.7 This theoretical framework suggests that there is a point at which an individual should be challenged optimally by a specific practice protocol. At this point, practice performance may be attenuated, but learning is enhanced.53 Our study design fits the CPF because we manipulated both the practice condition and the relative skill level of the learner in the process of learning a set of arm movements.

Consistent with what has been shown in the motor learning literature for young adults, blocked-order practice resulted in greater improvements across practice trials than random-order practice for both age-matched control participants and participants with mild PD.3033,35,37,38 The retention phase findings revealed that participants with PD who engaged in blocked practice retained the practiced skill as well as counterpart control participants. However, and more importantly, participants with PD who engaged in random practice showed poorer retention than control participants who practiced under the same condition. We suggest that these results may be associated with the more impaired task-switching capability exhibited by participants with PD than by control participants.3,5458 The known task-switching deficits common in PD and reflected here by performance on the Trail Making Test could have compromised the known benefits of random practice. However, a post hoc analysis of the relationship between the Trail Making Test score and retention performance showed no reliable correlation. Therefore, there may be other cognitive factors that can explain the group × practice condition results. The fact that participants with mild PD showed some benefit from practice suggests that their motor learning deficits were not general but depended rather importantly on the cognitive demands of the specific practice condition.53

The challenge provided through the random-order practice condition attenuated the performance of participants in both the PD group and the age-matched control group in the acquisition phase, relative to that provided through the blocked-order practice condition. The fact that there was no significant group × practice order interaction during the acquisition phase suggests that the cognitive effort required in either practice condition may have been similar for both participant groups. Additionally, participants with PD generally performed with more error than control participants throughout the entire acquisition phase (Fig. 2A). This result, along with the insignificant group × practice order interaction, supports the view that explicit motor control deficits were responsible for the poorer performance (higher error rate) of participants with PD. In addition, visual inspection of the acquisition data suggested that participants in the PDR group never achieved the level of performance of participants in the other 3 groups, even after 9 blocks of practice (Fig. 2C). This result, together with the lack of differences between the PDB and PDR groups in forgetting, suggests the possibility that the random-order practice condition exceeded the ideal challenge point for participants with PD. The latter participants did not acquire motor skills well under a random-order practice condition, a situation likely resulting in poor retention performance.

An alternative interpretation is that people with PD may lose the capability to maintain an action plan in working memory against competing alternatives.56 Although the present study could not differentiate among these possible explanations, our findings are consistent with known deficits previously described for people with PD performing 2 or more different tasks in an intermixed fashion.55

Although there were tendencies for participants in the PDB group to retain skills as well as those in the CB group and for participants in the PDR group not to retain skills as well as those in the CR group, the results yielded no significant group × practice order interaction in the random retention test (Fig. 4B). Our interpretation is that the group × practice order interaction could have been attenuated by practice-test congruity, participants’ task-switching capability, or both. For participants who practiced in the blocked-order condition, the random retention test provided less practice-test congruity than the blocked retention test. In addition, the random testing condition did not favor participants with PD, whose capability for switching among tasks was impaired (Tab. 1). Therefore, for motor learning in adults with mild PD, the benefit of blocked-order practice appeared to be weaker with the random retention test than with the blocked retention test (Fig. 4A).

Our study has several limitations that compromise the generalizability of the findings. First, although our small sample was chosen because this work began as a pilot study, the small sample reduced our power to detect group differences; however, our ESs provide justification for designing follow-up studies with a larger sample. Second, the laboratory tasks that we used are only analogs of real-world skills, bringing into question the generalizability of task learning in a clinical practice environment with its meaningful motor skills. Finally, our limited practice duration (135 practice trials) might have compromised motor learning, especially in the PD group. Perhaps participants with PD could have overcome the detrimental effects of the random-order practice had more trials been provided.59 Alternatively, limited practice is likely to be a better representation of the clinical practice environment, making our design appropriate for generalization to such an environment.

Conclusion

Our findings have implications for the physical rehabilitation of older adults and adults with PD-related motor deficits. Our findings indicated that a more variable practice condition—random-order practice—appeared to increase the challenge level and result in enhanced motor learning in older adults without disabilities, relative to what was achieved with blocked-order practice. The same practice condition, however, exceeded the optimal challenge point in people with mild PD, who showed attenuated acquisition and retention performance. It is conceivable that introducing additional challenges (ie, random-order practice) for adults with specific cognitive deficits can be detrimental, rather than beneficial, for learning; perhaps because these practice-induced demands compete for an already compromised system that is engaged in essential learning processes. The direct application of practice conditions known to be effective for motor learning, but without a hypothesis for the mechanism mediating the expected effect, can be detrimental, especially in populations with known cognitive deficits. Caution should be taken before translating motor learning principles into protocols for rehabilitation, especially in light of recent work showing that motor skill learning depends on a complex interaction among task difficulty, individual differences in skill level, and the effects of various practice conditions.

This theory-driven study was designed to provide relevant information about the selection of task practice variations for people with mild PD. Our results fit within the CPF by demonstrating an interaction between practice condition (ie, blocked and random) and individual capability (ie, PD and control participants) for motor learning. The results provide further indirect evidence that the basal ganglia and their interconnections can influence the cognitive processes involved in motor performance and learning. Despite a few limitations that compromised the generalizability of the findings, this study provides preliminary data and suggests future direction for research into the cognitive demands of relevant practice conditions for motor learning. For example, previous studies suggested that low, rather than high, relative frequencies of postmovement feedback are better for motor learning. However, the degree to which adults with specific brain damage would benefit from this motor learning principle remains to be determined. This kind of research can be useful in the development of a foundation for the translation of motor learning principles for neurorehabilitation.

Footnotes

  • Ms Lin, Dr Sullivan, Dr Wu, and Dr Winstein provided concept/idea/research design and data analysis. Ms Lin, Dr Sullivan, and Dr Winstein provided writing. Ms Lin and Mr Kantak provided data collection. Ms Lin provided project management. Dr Winstein provided facilities/equipment and institutional liaisons. Dr Wu and Dr Winstein provided fund procurement. Dr Sullivan, Dr Wu, Mr Kantak, and Dr Winstein provided consultation (including review of manuscript before submission). The authors thank Dr Jeanine Yip for assistance with participant recruitment, Dr Mickie Welsh for comments about the questionnaires, and Lung-Ching Lee for aspects of data analysis.

  • The protocol was approved by the Institutional Review Board of the University of Southern California Health Sciences Campus.

  • This study was presented as an oral poster at the Combined Sections Meeting of the American Physical Therapy Association; February 1–5, 2006; San Diego, Calif.

  • This study was supported by a research grant from the California Physical Therapy Fund from the California Physical Therapy Association.

  • * Hewlett-Packard Co, 3000 Hanover St, Palo Alto, CA 94304-1501.

  • SPSS Inc, 233 S Wacker Dr, Chicago, IL 60606.

  • Received August 10, 2006.
  • Accepted April 6, 2007.

References

View Abstract