Author(s): RUFFINO, C., JACQUET, T., LEPERS, R., PAPAXANTHIS, C., TRUONG, C. , Institution: LABORATORY C3S, UNIVERSITY OF FRANCHE-COMTÉ, BESANÇON, FRANCE, Country: FRANCE, Abstract-ID: 843

INTRODUCTION:
Mental fatigue (MF) is a psychobiological state induced by the realization of prolonged and/or intensive cognitive tasks and characterized by a subjective feeling of tiredness1. It is well established that MF negatively impacts both cognitive and physical performances. Recent research has shown that MF affects motor adaptation2, mainly due to difficulties in engaging explicit strategies. However, its impact on motor learning remains unclear.
METHODS:
To address this gap, we used a finger-tapping-task (FTT) and divided 28 participants into one of two groups: an MF group (n=14), which completed a 30-min modified Stroop task, and a Control group (n=14), which watched a documentary of equivalent duration. Following these tasks, both groups trained on the FTT, which required tapping a predetermined sequence as quickly as possible. The training consisted of 48 trials, divided into 12 blocks of 4 trials, with 5-s rest intervals between trials and 30-s rest intervals between blocks. Movement duration and accuracy of each trial were recorded to calculate a composite ratio to characterize motor skill3. We analyzed motor skill improvement between the beginning (T1) and the end (T2) of the training, the learning curve across all trials, and the online and offline processes. The online process represents motor skill evolution within each block, while the micro-offline process reflects changes during the rest periods between blocks. Additionally, to assess the impact of the Stroop task and documentary viewing, MF was evaluated using a visual analog scale (100mm).
RESULTS:
Results. MF significantly differed between groups (p<.001), with a higher level of MF after the Stroop (61/100) task than after the control task (26/100). Concerning motor skill improvement, the rmANOVA revealed a significant increase in motor skill in both groups between T1 and T2 (p<.001) without difference between them (p=.53). Similarly, the analysis of the learning curve showed no difference in the learning rate between groups (p=.82). However, motor skill deterioration during online process and motor skill improvement during micro-offline process were greater in the MF group (for both, p=.02). Interestingly, a strong negative correlation (r=-0.96, p<.001) was observed between the online and micro-offline processes, meaning that a greater decrease in motor skill during online process is associated with a greater increase during the micro-offline process, and vice versa.
CONCLUSION:
Conclusion. While the total motor skill improvement was similar between groups after MF, the dynamic of motor learning differs. The deterioration observed during the online process was compensated by the offline period between blocks with greater motor skill regain in the MF group. These results highlight the potential role of rest periods in optimizing motor learning under MF.

1) Boksem & Tops M, Brain Research Reviews, 2008
2) Apreutesei & Cressman, PloS One, 2024
3) Truong et. Npj Science of Learning, 2023