ausblenden:
Schlagwörter:
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Zusammenfassung:
Introduction:
Extensive usage of a finger during acquisition of a new skill implies specific changes of the corresponding muscle representations in the primary motor cortex (M1)1,2. Taking advantage of this use-dependent neural plasticity, early initiated procedures have attempted to improve the capability to learn or the potential for motor learning3,4. Along the same line, we aimed 1) to depict the fine changes in muscle representations associated with motor improvement using a novel highly focal TMS approach and 2) to examine the effects of immobilizing the non-trained fingers.
Methods:
30 participants were equally randomized into four experimental groups. They were asked to train on 7 successive days 3 times per day for 10 minutes with their Index (Groups 13) or their Little finger (Groups 24). Half of them had their three non-trained fingers immobilized (Groups 34). A visuomotor tracking task was used that required abduction-adduction movements of one finger. Their initial and final performance was recorded using both their Index and their Little fingers. We used neuronavigated TMS with a highly focal small figure-8 coil combined with individually located target sites to map muscle representations along the longitudinal axis of M1 before and after training. Resting motor evoked potentials (MEPs) were recorded from the first dorsal interosseus (FDI) and the abductor digiti minimi (ADM) muscles. We looked at the muscle excitability profiles along the longitudinal axis of M1 before and after training.
Results:
Preliminary Results (n=30):
Tracking performance: Training led to better performance for the trained and non-trained fingers. A repeated measure ANOVA using the behavioural data of the trained finger with the factors Session (Pre/Post) and Adjacent-fingers (Immobilized/Free) showed a significant Session*Adjacent-finger interaction (p = 0.018). A post hoc t-test revealed that the greatest improvement occurred in Groups 3 and 4 undergoing immobilisation of the non-used fingers (p = 0.007).
MEP mapping: We then tested the distribution of the MEPs amplitudes recorded from the ADM and FDI muscles across targets. A repeated measure ANOVA on the MEPs amplitudes of the trained muscle with the factors Session (Pre/Post), Adjacent-fingers (Immobilized/Free) and Target (up to 7) showed a significant Session*Target*Adjacent-finger interaction (p = 0.004). That is, training had a different impact on the muscle excitability profiles depending on the state of the adjacent fingers during training. To describe and quantify the changes in muscle profiles we computed the Full Width at Half Maximum (FWHM) of the curves and found increased FWHM values for the trained muscle in Group 3 (p = 0.03) and Group 4 (p = 0.01) while they tended to decrease for Group 1 (p = 0.06) and Group 2 (p = 0.08) after training. This reflects an enlargement of the trained muscle´s profile for Groups 3 and 4 and a trend towards narrowing for Groups 1 and 2.
Conclusions:
Learning effects on visuomotor tracking were consistently more pronounced when the adjacent fingers had been immobilized during training. The greater behavioural effects were associated with a specific modulation of the corticomusclar excitability profiles: a global up-regulation of the trained motor finger representation and a more prominent inhibition of the non-used finger representation. This is in accordance with the concept of a continuous competition for neural resources in M1: Improved performance for the trained finger is associated with more cortical resources being devoted to the trained finger and the corresponding motor skills. This pattern is especially pronounced when immobilisation causes sensorimotor deprivation of the non-trained fingers. Conversely, when the adjacent body parts were not restricted, the weaker increase in performance was associated with a more focal change in muscle representation. These findings are of relevance for future rehabilitative strategies.
