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Neuroplasticity

Neuroplasticity

Neuroplasticity reflects the brain's remarkable capacity to adapt and evolve, responding dynamically to learning, experiences, or injury by reorganizing its neural circuitry. This reorganization involves creating new neural connections and refining old ones through a series of biological processes that contribute to the brain's lifelong development and adaptability.

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Updated: Apr 23, 2026

Structured Motor Rehabilitation After Selective Nerve Transfers

Structured Motor Rehabilitation After Selective Nerve Transfers

Published on: August 15, 2019

Neural coding for effective rehabilitation.

Xiaoling Hu¹, Yiwen Wang², Ting Zhao³

¹Interdisciplinary Division of Biomedical Engineering, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong.

Biomed Research International

|September 27, 2014

Summary

This summary is machine-generated.

Neural coding advances neuroimaging and brain-machine interfaces for rehabilitation. This review covers breakthroughs in diagnosis, BMI, and robotic evaluation, paving the way for future home-based, automated patient care.

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Area of Science:

Neuroscience
Biomedical Engineering
Rehabilitation Science

Background:

Neurological rehabilitation success relies on accurate diagnosis, effective treatment, and quantitative evaluation.
Neural coding interprets nervous system information, driving progress in neuroimaging, brain-machine interfaces (BMI), and rehabilitation training devices.

Purpose of the Study:

To review recent advancements in neural coding applications for neurological rehabilitation.
To highlight breakthroughs in neuroimaging, BMI, and robotic-assisted evaluation.

Main Methods:

Literature review of microscale to macroscale neuroimaging techniques.
Analysis of electrocorticography (ECoG) and electromyography (EMG) coding for BMI and robotic interaction.
Examination of robot-assisted quantitative evaluation methods.

Main Results:

Summarized latest neuroimaging breakthroughs with diagnostic potential for rehabilitation.
Reviewed ECoG and EMG coding achievements for BMI and robotic systems.
Highlighted robot-assisted evaluation for rehabilitation progress.

Conclusions:

Future rehabilitation will be increasingly home-based, automated, and patient-driven.
Further research is needed to enhance computational efficiency, validate BMI programs, and simplify device operation.