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| Name | Class |
|---|---|
| University of Trieste | OTHER |
| University of Franche-Comté | OTHER |
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The aim of our study is to investigate the acute effects of real execution (RE) and motor imagery (MI) of Fitts law tasks on near and far transfer of learning.
Studies show changes in alpha (7.5 - 15 Hz) and beta (15 - 30 Hz) frequencies before and during motor tasks. However, researchers still disagree on the origin, timing, and direction of this. The neurophysiological mechanisms of motor learning are not yet fully understood. The authors note that event-related beta desynchronization is most commonly associated with motor learning. Reduced beta wave power can be observed in motor cortex, but it is still unclear whether this change is related to motor learning, performance, or movement repetition.
A comparative study of motor imagery and actual performance showed the occurrence of similar neurophysiological processes in the motor cortex. All the mentioned studies were conducted on adults and the results were mainly from the analysis of upper limb movements. In the present study, the investigators will comprehensively evaluate the upper and lower limb movements of children: from the recognition of visual stimuli to the generation of the motor program and the execution itself (behavioral data).
Forty-five children (year 2009) will be recruited from local primary schools. In a single-blinded design, children will be randomized into three groups (1st - real execution, 2nd - motor imagery, 3rd - control) and compared at baseline, immediately post-intervention and at follow-up 24 hours post-intervention. At pre-, post-, and follow-up assessments, participants will perform two different patterns of the Fitts Law task with the predefined difficulty: lower limbs/whole body and upper limbs/hands on an interactive whiteboard. The intervention period lasts approximately 10 minutes, during which participants perform the Fitts law task with different difficulty according to the intervention group to which they belong.
During the upper limb/hand tasks, brain activity will be recorded with electroencephalography (EEG).
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Real execution group | Experimental | The real execution group will perform the acute intervention by the actual performance of the Fitt's law task. |
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| Motor imagery group | Experimental | The motor imagery group will perform the acute intervention by simulating (mental process) the Fitt's law task. |
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| Control group | Active Comparator | The control group will perform skip counting. |
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| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Real execution of Fitts's law tasks | Behavioral | Children will be training Fitts's law tasks of different difficulties. Once each task will be solved, they will receive a new, more demanding task |
| Measure | Description | Time Frame |
|---|---|---|
| Change from baseline Movement related cortical potential at 24-yhours follow-up post intervention | Event related potential that are typically linked with updating of internal models, decision-making and motor preparation. | Assessed at baseline, immediately post intervention and at 24-yhours follow-up post intervention |
| Measure | Description | Time Frame |
|---|---|---|
| Change from baseline Fitts's law task performance at 24-yhours follow-up post intervention | Change in movement time (seconds) needed to solve Fitts's law tasks of different difficulites | Assessed at baseline, immediately post intervention and at 24-yhours follow-up post intervention |
| Change from baseline Fitts's law task performance at 24-yhours follow-up post intervention |
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Inclusion Criteria:
Exclusion Criteria:
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| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Luka Šlosar, PhD | Contact | 0038640612132 | luka.slosar@zrs-kp.si |
| Name | Affiliation | Role |
|---|---|---|
| Uroš Marušič, PhD | Science and research center Koper | Principal Investigator |
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| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 25309823 | Background | Kiefer AW, Gualberto Cremades J, Myer GD. Train the Brain: Novel Electroencephalography Data Indicate Links between Motor Learning and Brain Adaptations. J Nov Physiother. 2014 Apr;4(2):198. doi: 10.4172/2165-7025.1000198. | |
| 28824406 | Background | Thurer B, Stockinger C, Putze F, Schultz T, Stein T. Mechanisms within the Parietal Cortex Correlate with the Benefits of Random Practice in Motor Adaptation. Front Hum Neurosci. 2017 Aug 2;11:403. doi: 10.3389/fnhum.2017.00403. eCollection 2017. |
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In a single-blind design children will be randomized into three groups: 1st - real execution, 2nd - motor imagery, 3rd - control (skip counting)
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| Motor imagery of Fitts's law tasks | Behavioral | Children will be training Fitts's law tasks of different difficulties, same as RE group but the exception of doing it mentally - motor imagery of Fitts's law tasks with eyes open. |
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| Skip counting | Behavioral | Children in SCg will silently count (one number per second) in the same working blocks as both experimental groups with a task of saying the number they reached during each block - control condition to keep them mentally active at very low mental engagement. |
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Accuracy, namely, a group of trials repeatedly hitting a narrow band (precise) but off the center of the target (inaccurate) |
| Assessed at baseline, immediately post intervention and at 24-yhours follow-up post intervention |
| 29093171 | Background | Wu J, Knapp F, Cramer SC, Srinivasan R. Electroencephalographic connectivity measures predict learning of a motor sequencing task. J Neurophysiol. 2018 Feb 1;119(2):490-498. doi: 10.1152/jn.00580.2017. Epub 2017 Nov 1. |
| 28840774 | Background | Ghasemian M, Taheri H, Saberi Kakhki A, Ghoshuni M. Electroencephalography Pattern Variations During Motor Skill Acquisition. Percept Mot Skills. 2017 Dec;124(6):1069-1084. doi: 10.1177/0031512517727404. Epub 2017 Aug 25. |
| 28367834 | Background | Ozdenizci O, Yalcin M, Erdogan A, Patoglu V, Grosse-Wentrup M, Cetin M. Electroencephalographic identifiers of motor adaptation learning. J Neural Eng. 2017 Aug;14(4):046027. doi: 10.1088/1741-2552/aa6abd. |
| 27714404 | Background | Sobierajewicz J, Przekoracka-Krawczyk A, Jaskowski W, Verwey WB, van der Lubbe R. The influence of motor imagery on the learning of a fine hand motor skill. Exp Brain Res. 2017 Jan;235(1):305-320. doi: 10.1007/s00221-016-4794-2. Epub 2016 Oct 6. |