Fitt's Law MI Experiment

NCT ID: NCT04744597

Last Updated: 2021-02-09

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

UNKNOWN

Clinical Phase

NA

Total Enrollment

45 participants

Study Classification

INTERVENTIONAL

Study Start Date

2021-02-01

Study Completion Date

2021-06-01

Brief Summary

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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.

Detailed Description

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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).

Conditions

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Healthy

Study Design

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Allocation Method

RANDOMIZED

Intervention Model

PARALLEL

In a single-blind design children will be randomized into three groups: 1st - real execution, 2nd - motor imagery, 3rd - control (skip counting)
Primary Study Purpose

BASIC_SCIENCE

Blinding Strategy

SINGLE

Participants

Study Groups

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Real execution group

The real execution group will perform the acute intervention by the actual performance of the Fitt's law task.

Group Type EXPERIMENTAL

Real execution of Fitts's law tasks

Intervention Type 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

Motor imagery group

The motor imagery group will perform the acute intervention by simulating (mental process) the Fitt's law task.

Group Type EXPERIMENTAL

Motor imagery of Fitts's law tasks

Intervention Type 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.

Control group

The control group will perform skip counting.

Group Type ACTIVE_COMPARATOR

Skip counting

Intervention Type 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.

Interventions

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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

Intervention Type 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.

Intervention Type 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.

Intervention Type BEHAVIORAL

Other Intervention Names

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REg MIg SCg

Eligibility Criteria

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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
Minimum Eligible Age

11 Years

Maximum Eligible Age

12 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

Yes

Sponsors

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University of Trieste

OTHER

Sponsor Role collaborator

University of Franche-Comté

OTHER

Sponsor Role collaborator

Science and Research Centre Koper

OTHER

Sponsor Role lead

Responsible Party

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Responsibility Role SPONSOR

Principal Investigators

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Uroš Marušič, PhD

Role: PRINCIPAL_INVESTIGATOR

Science and research center Koper

Central Contacts

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Luka Šlosar, PhD

Role: CONTACT

0038640612132

References

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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.

Reference Type BACKGROUND
PMID: 25309823 (View on PubMed)

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.

Reference Type BACKGROUND
PMID: 28824406 (View on PubMed)

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.

Reference Type BACKGROUND
PMID: 29093171 (View on PubMed)

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.

Reference Type BACKGROUND
PMID: 28840774 (View on PubMed)

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.

Reference Type BACKGROUND
PMID: 28367834 (View on PubMed)

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.

Reference Type BACKGROUND
PMID: 27714404 (View on PubMed)

Other Identifiers

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TwinBrainFittsLaw

Identifier Type: -

Identifier Source: org_study_id

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