Clinical trial NCT04744597: Fitt's Law MI Experiment
Official title: Neural Aspects of Motor Learning Through Real Execution and Motor Imagery in Children
Study type: INTERVENTIONAL
Overall status: UNKNOWN
Phase: NA
Conditions: Healthy
Keywords: EEG
Motor learning
Fitt's law
Motor imagery
Lead sponsor: Science and Research Centre Koper
Sponsor class: OTHER
Collaborators: name: University of Trieste
name: University of Franche-Comté
First posted: 2021-02-09
Enrollment: 45
Sex: ALL
Minimum age (years): 11
Maximum age (years): 12
Standard ages: CHILD
Accepts healthy volunteers: yes
Allocation: RANDOMIZED
Intervention model: PARALLEL
Intervention model description: In a single-blind design children will be randomized into three groups: 1st - real execution, 2nd - motor imagery, 3rd - control (skip counting)
Primary purpose: BASIC_SCIENCE

Brief summary: 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.

Detailed description: 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).

Eligibility criteria: Inclusion Criteria:

* born in 2009
* no significant muscular, skeleton or nervous system damage
* the earlier-signed agreement to take part in the protocol.

Exclusion Criteria:

* Nervous system disorders

Primary outcomes:
measure: Change from baseline Movement related cortical potential at 24-yhours follow-up post intervention
timeFrame: Assessed at baseline, immediately post intervention and at 24-yhours follow-up post intervention
Secondary outcomes:
measure: Change from baseline Fitts's law task performance at 24-yhours follow-up post intervention
timeFrame: Assessed at baseline, immediately post intervention and at 24-yhours follow-up post intervention
measure: Change from baseline Fitts's law task performance at 24-yhours follow-up post intervention
timeFrame: Assessed at baseline, immediately post intervention and at 24-yhours follow-up post intervention
Other outcomes:
Locations:
Study officials:
affiliation: Science and research center Koper
name: Uroš Marušič, PhD
role: PRINCIPAL_INVESTIGATOR
References:
citation: 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.
citation: 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.
citation: 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.
citation: 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.
citation: 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.
citation: 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.