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Assessment and Communication for People with Disorders of Consciousness

Assessment and Communication for People with Disorders of Consciousness

Published on: August 1, 2017

Intracortical Brain-Machine Interfaces Advance Sensorimotor Neuroscience.

Karen E Schroeder¹, Cynthia A Chestek²

¹Department of Biomedical Engineering, University of Michigan Ann Arbor, MI, USA.

Frontiers in Neuroscience

|July 23, 2016

Summary

This summary is machine-generated.

Brain-machine interfaces (BMIs) decode brain activity for prosthetic control. This review highlights advances in neural coding, motor cortex plasticity, and sensory feedback understanding from BMI research.

Keywords:

brain-machine interface motor cortex motor learning neuroprosthetics reaching

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Published on: December 5, 2014

Area of Science:

Neuroscience
Biomedical Engineering
Rehabilitation Technology

Background:

Brain-machine interfaces (BMIs) translate neural activity into device control.
Significant progress has been made, including human clinical trials with intracortical electrodes.
BMI research has yielded crucial insights into fundamental neuroscience.

Purpose of the Study:

To review neuroscience achievements driven by BMI research, focusing on upper limb prosthetics.
To highlight advancements in neural coding, motor learning, and sensory feedback.
To discuss the impact of BMIs on understanding motor cortex function.

Main Methods:

Review of studies utilizing intracortical microelectrodes for upper limb prosthetic control.
Analysis of research on neural representations of movement in the motor cortex.
Examination of findings related to motor cortex plasticity and learning.
Investigation of insights gained from bidirectional BMIs regarding somatosensation.

Main Results:

Progress in understanding high-dimensional neural representations of reach movements.
Characterization of neural plasticity in the motor cortex across different timescales.
Enhanced comprehension of somatosensory processing linked to motor control through bidirectional BMIs.

Conclusions:

BMI research, particularly for upper limb prosthetics, has significantly advanced neuroscience.
Understanding neural coding, plasticity, and sensory feedback is crucial for effective BMI development.
BMIs offer a powerful tool for both technological innovation and basic neuroscience discovery.