Fitt's Law MI Experiment

Neural Aspects of Motor Learning Through Real Execution and Motor Imagery in Children

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.

Study Overview

• Status: Unknown
• Conditions: Healthy
• Intervention / Treatment: Behavioral: Real execution of Fitts's law tasks; Behavioral: Motor imagery of Fitts's law tasks; Behavioral: Skip counting

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).

• Study Type: Interventional
• Enrollment (Anticipated): 45
• Phase: Not Applicable

Contacts and Locations

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 11 years to 12 years (Child)
• Accepts Healthy Volunteers: Yes
• Genders Eligible for Study: All

Description

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

Study Plan

How is the study designed?

Design Details

• Primary Purpose: Basic Science
• Allocation: Randomized
• Interventional Model: Parallel Assignment
• Masking: Single

Number of Arms

3

Arms and Interventions

Participant Group / Arm	Intervention / Treatment
Experimental: Real execution group; The real execution group will perform the acute intervention by the actual performance of the Fitt's law task.	Behavioral: Real execution of Fitts's law tasks; 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; Other Names: REg
Experimental: Motor imagery group; The motor imagery group will perform the acute intervention by simulating (mental process) the Fitt's law task.	Behavioral: Motor imagery of Fitts's law tasks; 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.; Other Names: MIg
Active Comparator: Control group; The control group will perform skip counting.	Behavioral: Skip counting; 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.; Other Names: SCg

What is the study measuring?

Primary Outcome Measures

Outcome Measure	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

Secondary Outcome Measures

Outcome Measure	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	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

Collaborators and Investigators

• Sponsor: Science and Research Centre Koper
• Collaborators: University of Trieste; University of Franche-Comté
• Investigators: Principal Investigator: Uroš Marušič, PhD, Science and research center Koper

Publications and helpful links

General Publications

• 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.
• 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.
• 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.
• 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.
• 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.
• 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.

Study record dates

Study Major Dates

• Study Start (Anticipated): February 1, 2021
• Primary Completion (Anticipated): May 10, 2021
• Study Completion (Anticipated): June 1, 2021

Study Registration Dates

• First Submitted: January 25, 2021
• First Submitted That Met QC Criteria: February 4, 2021
• First Posted (Actual): February 9, 2021

Study Record Updates

• Last Update Posted (Actual): February 9, 2021
• Last Update Submitted That Met QC Criteria: February 4, 2021
• Last Verified: February 1, 2021

More Information

Terms related to this study

• Keywords: EEG; Motor learning; Motor imagery; Fitt's law
• Other Study ID Numbers: TwinBrainFittsLaw

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No