This study investigated the impact of mental fatigue and self-controlled versus yoked feedback on learning a force production task. We randomly assigned 44 non-athlete male students (Mage = 21.4, SD = 1.4 years) to four groups; (a) MF&SCF = mental fatigue & self-controlled feedback, (b) MF&Y = mental fatigue & yoked, (c) NMF&SCF = no mental fatigue & self-controlled feedback, and (d) NMF&Y = no mental fatigue & yoked). SCF group participants were provided feedback whenever they requested it, while YK group participants received feedback according to a schedule created by their SCF counterparts. To induce mental fatigue, participants performed a Stroop color-word task for one hour. During the acquisition (practice) phase, participants were asked to produce a given percentage of their maximum force (20%) in 12 blocks of six trials. We recorded the participants’ absolute error at the end of the acquisition phase, the immediate retention test, the first transfer test, and the second transfer test (after 24 hours and without any further mental fatigue). The acquisition phase data were analyzed in a 2 (feedback) × 2 (mental fatigue) × 12 (block) ANOVA with repeated measures on the last factor, while the retention and transfer data were analyzed in 2 (feedback) × 2 (mental fatigue) ANOVAs. We found that all four groups made significant progress during practice ( p < .001), but there were no significant group differences during this phase ( p>.05). There was a significant interaction effect of self-controlled feedback and mental fatigue at retention ( p = .018) and transfer testing ( p < .001). In the mental fatigue condition, participants in the self-controlled group had poorer learning compared to participants in the yoked group; but when not mentally fatigued, participants in the self-controlled group had better learning than those in the yoked group. These findings suggest that mental fatigue reduces typical advantages of self-controlled feedback in motor learning.
Error detection in a force-production task: Testing the force-unit monitoring model
