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Related Experiment Video

Updated: May 31, 2026

Assessing Corticospinal Excitability During Goal-Directed Reaching Behavior

Assessing Corticospinal Excitability During Goal-Directed Reaching Behavior

Published on: December 2, 2022

Human sensorimotor learning: adaptation, skill, and beyond.

John W Krakauer¹, Pietro Mazzoni

¹Department of Neurology, Johns Hopkins University, Baltimore, United States. krakau1@jhmi.edu

Current Opinion in Neurobiology

|July 19, 2011

Summary

This summary is machine-generated.

Human sensorimotor learning involves distinct processes like adaptation and reinforcement, weighted differently by motor tasks. Understanding these mechanisms aids in analyzing upper limb movements and brain structures involved.

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Area of Science:

Neuroscience
Motor Control
Cognitive Science

Background:

Human sensorimotor learning is crucial for upper limb movements.
Different motor tasks rely on distinct learning processes.
Adaptation, use-dependent plasticity, and reinforcement are key learning mechanisms.

Purpose of the Study:

To explore the computations, mechanisms, and taxonomy of human sensorimotor learning.
To differentiate how various motor tasks weight different learning processes.
To investigate the role of explicit awareness and declarative memory in motor learning.

Main Methods:

Analysis of recent studies on upper limb movements.
Comparison of learning processes in visuomotor rotation, force-field, and skill learning tasks.
Examination of the contribution of explicit awareness and declarative memory.

Main Results:

Motor tasks differentially weight learning processes such as adaptation and reinforcement.
Visuomotor and force-field tasks emphasize adaptation due to systematic errors.
Skill learning tasks, often without perturbation, rely more on success-based exploration and reduced motor variability.
Explicit awareness and declarative memory contribute variably to motor learning.

Conclusions:

Sensorimotor learning is a complex process involving multiple, differentially weighted mechanisms.
The modularity of motor learning processes is reflected in distinct brain structures.
Understanding these processes provides insights into motor control and learning.