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Related Concept Videos

Hierarchy of Motor Control01:18

Hierarchy of Motor Control

The hierarchy of motor control refers to the different levels of organization and processing involved in controlling movement in the body. These levels range from higher cortical areas involved in planning and decision-making to lower spinal cord reflexes that respond automatically to external stimuli.
Open and closed-loop control systems01:17

Open and closed-loop control systems

Control systems are foundational elements in automation and engineering. They are broadly categorized into open-loop and closed-loop systems. These classifications hinge on the presence or absence of feedback mechanisms, significantly influencing the system's performance, complexity, and application.
An open-loop control system operates without feedback from the output. It consists of two primary elements: the controller and the controlled process. The controller receives an input signal and...
Steps in the Modeling Process01:14

Steps in the Modeling Process

Albert Bandura's theory of observational learning identifies four critical processes: attention, retention, motor reproduction, and reinforcement or motivation.
Attention is the first necessary component for observational learning. It involves focusing on what the model is doing and saying. For example, if you decide to take a drawing class to enhance your skills, you need to pay close attention to the instructor's words and hand movements. The characteristics of the model significantly...
PD Controller: Design01:26

PD Controller: Design

In automotive engineering, car suspension systems often employ Proportional Derivative (PD) controllers to enhance performance. PD controllers are utilized to adjust the damping force in response to road conditions. A controller, acting as an amplifier with a constant gain, demonstrates proportional control, with output directly mirroring input.
Designing a continuous-data controller requires selecting and linking components like adders and integrators, which are fundamental in Proportional,...
Motor Units00:46

Motor Units

A motor unit consists of two main components: a single efferent motor neuron (i.e., a neuron that carries impulses away from the central nervous system) and all of the muscle fibers it innervates. The motor neuron may innervate multiple muscle fibers, which are single cells, but only one motor neuron innervates a single muscle fiber.
Motor Units01:13

Motor Units

The motor unit is a fundamental component of the neuromuscular system and plays a crucial role in coordinating muscle contractions. It consists of a somatic motor neuron, which connects and controls multiple skeletal muscle fibers, forming a single functional segment. The axon of the motor neuron branches out and establishes synaptic connections known as neuromuscular junctions with individual muscle fibers within the motor unit.
Motor units come in different sizes, with smaller units...

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Related Experiment Video

Updated: Jul 10, 2026

The "Motor" in Implicit Motor Sequence Learning: A Foot-stepping Serial Reaction Time Task
10:39

The "Motor" in Implicit Motor Sequence Learning: A Foot-stepping Serial Reaction Time Task

Published on: May 3, 2018

Taking steps toward open data in motor control, learning, and development.

Keith R Lohse1,2

  • 1Program in Physical Therapy, Washington University School of Medicine, Saint Louis, MO, USA.

Journal of Motor Learning and Development
|July 9, 2026
PubMed
Summary

Promoting data sharing accelerates scientific discovery and reduces research waste. Implementing robust data sharing practices, especially in motor control, learning, and development (MCLD), is crucial for scientific advancement.

Keywords:
Data SharingOpen DataReproducibility

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Related Experiment Videos

Last Updated: Jul 10, 2026

The "Motor" in Implicit Motor Sequence Learning: A Foot-stepping Serial Reaction Time Task
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Published on: May 3, 2018

Investigating Motor Skill Learning Processes with a Robotic Manipulandum
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Published on: February 12, 2017

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Area of Science:

  • Biomedical Research
  • Motor Control, Learning, and Development (MCLD)

Background:

  • Scientific research faces inefficiencies, with long timelines to impactful outcomes and significant research waste.
  • Limited access to existing data hinders progress, leading to redundant studies and suboptimal research design.
  • While data sharing is a growing norm, adoption remains low in specialized fields like MCLD.

Purpose of the Study:

  • To highlight the critical advantages of data sharing in scientific research.
  • To advocate for increased data sharing practices across all research domains, irrespective of funding.
  • To address and propose solutions for challenges hindering data sharing adoption.

Main Methods:

  • This editorial synthesizes current perspectives on data sharing.
  • It reviews the benefits, including accelerated discovery and enhanced collaboration.
  • It discusses concerns such as privacy, data misuse, and recognition.

Main Results:

  • Data sharing accelerates discovery, improves transparency, and enhances reproducibility.
  • It fosters collaboration and reduces redundant research efforts.
  • Addressing concerns can facilitate wider adoption.

Conclusions:

  • Wider adoption of data sharing is essential for scientific progress, particularly in MCLD research.
  • Proactive strategies are needed to overcome barriers related to privacy, recognition, and data integrity.
  • Implementing effective data sharing policies will maximize research impact and efficiency.