Jove
Visualize
Contáctanos
JoVE
x logofacebook logolinkedin logoyoutube logo
ACERCA DE JoVE
Visión GeneralLiderazgoBlogCentro de Ayuda JoVE
AUTORES
Proceso de PublicaciónConsejo EditorialAlcance y PolíticasRevisión por ParesPreguntas FrecuentesEnviar
BIBLIOTECARIOS
TestimoniosSuscripcionesAccesoRecursosConsejo Asesor de BibliotecasPreguntas Frecuentes
INVESTIGACIÓN
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchivo
EDUCACIÓN
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualCentro de Recursos para ProfesoresSitio de Profesores
Términos y Condiciones de Uso
Política de Privacidad
Políticas

Videos de Conceptos Relacionados

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.
Mechanical Efficiency of Real Machines01:14

Mechanical Efficiency of Real Machines

The mechanical efficiency of a machine is a fundamental concept that describes how effectively a machine can convert input work into output work. According to this concept, the efficiency of a machine is equal to the ratio of the output work to the input work. An ideal machine, meaning a machine that has no energy losses, has an efficiency of one. This implies that the input work and the output work are equal.
However, in reality, no machine can be truly ideal, and all of them experience some...
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...
Relative Motion Analysis using Rotating Axes-Problem Solving01:29

Relative Motion Analysis using Rotating Axes-Problem Solving

Consider a crane whose telescopic boom rotates with an angular velocity of 0.04 rad/s and angular acceleration of 0.02 rad/s2. Along with the rotation, the boom also extends linearly with a uniform speed of 5 m/s. The extension of the boom is measured at point D, which is measured with respect to the fixed point C on the other end of the boom. For the given instant, the distance between points C and D is 60 meters.
Here, in order to determine the magnitude of velocity and acceleration for point...
Relative Motion Analysis - Acceleration01:10

Relative Motion Analysis - Acceleration

A slider-crank mechanism converts rotational motion from the crank into linear motion of the slider or vice versa. This mechanism consists of three main parts: the crank, the connecting rod, and the slider. The movement of the slider-crank is an example of general plane motion as the fluctuating angle between the crank and the connecting rod. Consider a segment AB where point A is at the end of the slider and point B is on the diametrically opposite end to point A, on a crack. The variance in...
Sequence Networks of Rotating Machines01:24

Sequence Networks of Rotating Machines

A Y-connected synchronous generator, grounded through a neutral impedance, is designed to produce balanced internal phase voltages with only positive-sequence components. The generator's sequence networks include a source voltage that is exclusively in the positive-sequence network. The sequence components of line-to-ground voltages at the generator terminals illustrate this configuration.
Zero-sequence current induces a voltage drop across the generator's neutral impedance and other...

También podría leer

Artículos Relacionados

Artículos vinculados a este trabajo por autores compartidos, revista y gráfico de citas.

Ordenar por
Same author

Anxiety disorders alter cognitive-motor integration during visuomotor adaptation and retention.

Experimental brain research·2026
Same author

Acute Effects of a Multi-Ingredient Preworkout Supplement on Peak Torque and Muscle Excitation During an Isokinetic Fatigue Protocol.

Sports (Basel, Switzerland)·2025
Same author

Punishing temporal judgement boosts sense of agency and modulates its underlying neural correlates.

Consciousness and cognition·2025
Same author

Editorial: Reinforcement feedback in motor learning: neural underpinnings of skill refinement.

Frontiers in behavioral neuroscience·2025
Same author

Validity and Inter-Device Reliability of the OTBeat Burn<sup>TM</sup> Monitor to Estimate Heart Rate During Exercise.

Sports (Basel, Switzerland)·2025
Same author

Examining body mass index and health-related fitness marker progression of incarcerated minority youth engaged in a sport-leadership program.

International journal of prison health·2024

Video Experimental Relacionado

Updated: May 14, 2026

Asymmetric Walkway: A Novel Behavioral Assay for Studying Asymmetric Locomotion
08:19

Asymmetric Walkway: A Novel Behavioral Assay for Studying Asymmetric Locomotion

Published on: January 15, 2016

8.9K

Comparación del análisis de datos secuenciales y del análisis de datos funcionales para la adaptación locomotora

Torin Quinlivan1, Kacy Kane2, Christopher M Hill3

  • 1Department of Mathematics, Knox College, Galesburg, Illinois, United States of America.

PloS one
|August 29, 2025
PubMed
Resumen
Este resumen es generado por máquina.

Este estudio explora cómo las recompensas y los castigos influyen en las tasas de aprendizaje de habilidades humanas. Los investigadores desarrollaron métodos computacionales eficientes para estimar estas tasas de aprendizaje dinámicas, ofreciendo información sobre la adquisición de habilidades.

Más Videos Relacionados

Using a Split-belt Treadmill to Evaluate Generalization of Human Locomotor Adaptation
08:04

Using a Split-belt Treadmill to Evaluate Generalization of Human Locomotor Adaptation

Published on: August 23, 2017

8.3K
Comprehensive Understanding of Inactivity-Induced Gait Alteration in Rodents
04:37

Comprehensive Understanding of Inactivity-Induced Gait Alteration in Rodents

Published on: July 6, 2022

2.5K

Videos de Experimentos Relacionados

Last Updated: May 14, 2026

Asymmetric Walkway: A Novel Behavioral Assay for Studying Asymmetric Locomotion
08:19

Asymmetric Walkway: A Novel Behavioral Assay for Studying Asymmetric Locomotion

Published on: January 15, 2016

8.9K
Using a Split-belt Treadmill to Evaluate Generalization of Human Locomotor Adaptation
08:04

Using a Split-belt Treadmill to Evaluate Generalization of Human Locomotor Adaptation

Published on: August 23, 2017

8.3K
Comprehensive Understanding of Inactivity-Induced Gait Alteration in Rodents
04:37

Comprehensive Understanding of Inactivity-Induced Gait Alteration in Rodents

Published on: July 6, 2022

2.5K

Área de la Ciencia:

  • Ciencias cognitivas
  • Neurociencia computacional
  • Aprendizaje automático

Sus antecedentes:

  • Las tasas de aprendizaje de habilidades humanas pueden fluctuar en función de factores externos y tiempo.
  • Los incentivos, como las recompensas o los castigos, tienen un impacto significativo en la velocidad y la eficiencia de la adquisición de habilidades.

Objetivo del estudio:

  • Modele los cambios dinámicos en las tasas de aprendizaje de las habilidades humanas.
  • Investigar la influencia de la incentivación en estas tasas de aprendizaje.
  • Abordar los desafíos computacionales en la estimación de parámetros de la tasa de aprendizaje a partir de datos extensos.

Principales métodos:

  • Se empleó un modelo de espacio de estados para representar las tasas de aprendizaje dinámicas.
  • Se utilizó un filtro de partículas ponderado dinámicamente, un eficiente método secuencial de Monte Carlo, para la estimación de los parámetros.
  • El análisis de datos funcionales fue explorado como un enfoque alternativo para analizar las tasas de aprendizaje y los efectos de incentivación.

Principales resultados:

  • Tanto el filtro de partículas ponderado dinámicamente como el análisis de datos funcionales arrojaron estimaciones razonables de las tasas de aprendizaje.
  • El estudio presenta tasas de aprendizaje estimadas y cuantifica el impacto de la incentivación.
  • Se realizaron comparaciones entre los dos enfoques analíticos.

Conclusiones:

  • Las tasas de aprendizaje que cambian dinámicamente son un aspecto clave de la adquisición de habilidades humanas.
  • Los métodos computacionales eficientes como el filtro de partículas ponderado dinámicamente pueden superar la carga de la estimación de parámetros.
  • Los resultados proporcionan un marco para comprender cómo los incentivos modulan la dinámica del aprendizaje.