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. 2011 Nov;106(5):2632-41.
doi: 10.1152/jn.00399.2011. Epub 2011 Aug 10.

Mechanisms of the Contextual Interference Effect in Individuals Poststroke

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Free PMC article

Mechanisms of the Contextual Interference Effect in Individuals Poststroke

Nicolas Schweighofer et al. J Neurophysiol. .
Free PMC article

Abstract

Although intermixing different motor learning tasks via random schedules enhances long-term retention compared with "blocked" schedules, the mechanism underlying this contextual interference effect has been unclear. Furthermore, previous studies have reported inconclusive results in individuals poststroke. We instructed participants to learn to produce three grip force patterns in either random or blocked schedules and measured the contextual interference effect by long-term forgetting: the change in performance between immediate and 24-h posttests. Nondisabled participants exhibited the contextual interference effect: no forgetting in the random condition but forgetting in the blocked condition. Participants at least 3 mo poststroke exhibited no forgetting in the random condition but marginal forgetting in the blocked condition. However, in participants poststroke, the integrity of visuospatial working memory modulated long-term retention after blocked schedule training: participants with poor visuospatial working memory exhibited little forgetting at 24 h. These counterintuitive results were predicted by a computational model of motor memory that contains a common fast process and multiple slow processes, which are competitively updated by motor errors. In blocked schedules, the fast process quickly improved performance, therefore reducing error-driven update of the slow processes and thus poor long-term retention. In random schedules, interferences in the fast process led to slower change in performance, therefore increasing error-driven update of slow processes and thus good long-term retention. Increased forgetting rates in the fast process, as would be expected in individuals with visuospatial working memory deficits, led to small updates of the fast process during blocked schedules and thus better long-term retention.

Figures

Fig. 1.
Fig. 1.
Motor task. At each trial, 1 of 3 target force profiles was shown during the “ready” period. The specific force profile was selected according to a predetermined schedule (random or blocked). Two seconds later, a “GO” signal appeared and the participant was instructed to reach and grasp the apparatus and modulate the power grip force to approximate the target profile that lasted 2 s. The computer screen then became blank for 4 s, and feedback was shown for 4 s. Feedback included the actual force profile superimposed with the desired profile, the root mean squared error (RMSE) between the 2 profiles, as a well as a “best score,” which reflected the smallest error so far and was included for motivational purposes.
Fig. 2.
Fig. 2.
Examples of force trajectories for 4 participants for 1 task for the first trial of practice (left), the first trial of the immediate retention test (middle), and the first trial of the delayed test (right). Representative data are from a participant poststroke in blocked schedule (stroke-blocked), a participant poststroke in random schedule (stroke-random), a nondisabled participant in blocked schedule (healthy-blocked), and a nondisabled participant in random schedule (healthy-random). The gray line indicates the desired force profile; the black line indicates the actual force (in N) exerted by the participant during 2 s.
Fig. 3.
Fig. 3.
Computer simulations: contextual interference (CI) effect in the nondisabled model. Performance (black line), fast process (dotted line), and slow process (gray line) are shown during blocked (A) and random schedule training (C). Immediate and long-term retention are shown following blocked (B) and random schedule training (D). Imm, immediate test; Del, 24-h delayed test. Notice the large forgetting following blocked training and slower performance improvement during random than during blocked training. The jitter in the fast process memory (reflected in performance) during random training in C was due to both decay and interferences between the tasks.
Fig. 4.
Fig. 4.
Computer simulations: reduced CI effect in a model with poor visuospatial working memory. Performance (black line), fast process (dotted line), and slow process (gray line) are shown during blocked (A) and random schedule training (C). Immediate and long-term retention are shown following blocked (B) and random schedule training (D). In blocked schedules, there was little forgetting in the delayed retention test (B; compare with Fig. 3B) because of relatively higher buildup of slow process and lower buildup of fast process during training (A; compare with Fig. 3A). In random schedules, there was little difference during training (C) and testing (D) compared with the normal model (compare with Fig. 3, C and D).
Fig. 5.
Fig. 5.
Computer simulations: forgetting measured at the delayed retention test as a function of the time constant of decay of fast process after either blocked (A) or random schedule (B) for 2 tasks. Overall, and notably for larger time constants, there was less forgetting following random schedule than blocked schedule. However, for smaller time constants, forgetting was comparable following random and blocked schedule.
Fig. 6.
Fig. 6.
Data: CI effect in nondisabled participants. Performance (mean and SE) is shown during blocked (A) and random training (C). Immediate and long-term retention are shown following blocked (B) and random training (D).
Fig. 7.
Fig. 7.
Data: CI effect in participants poststroke. Performance (mean and SE) is shown during blocked (A) and random training (C). Immediate and long-term retention are shown following blocked (B) and random training (D).
Fig. 8.
Fig. 8.
Data: forgetting in individuals poststroke in a 24-h posttraining period is shown as a function of Wechsler visual memory score (figural) following training in either blocked (A) or random schedule (B) in the individuals poststroke who participated in the study. Black lines are regression lines; the gray line in B is a robust regression line (with default weighting function in Matlab robustfit function); the robust regression line is superimposed on the regression line in A. Compare with the computer simulations of Fig. 5.

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