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Higher Mental Functions of the Brain: Language

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Language is a system of communication that allows the expression of thoughts, ideas, and feelings. The brain processes language in both hemispheres.
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Author Spotlight: Using Motor Imagery Brain-Computer Interface to Improve Motor and Cognitive Function in Stroke Patients

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Published on: September 1, 2023

Restoring Speech Using Brain-Computer Interfaces.

Sergey D Stavisky¹

¹Department of Neurological Surgery, University of California, Davis, California, USA;

Annual Review of Biomedical Engineering

|January 2, 2025

Summary

This summary is machine-generated.

Brain-computer interfaces (BCIs) offer a new communication pathway for individuals with speech loss from neurological injuries. This review explores the progress and challenges in developing effective speech BCIs for restoring naturalistic communication.

Keywords:

assistive technology brain–machine interface communication motor paralysis speech

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Area of Science:

Neuroscience
Biomedical Engineering
Assistive Technology

Background:

Neurological injuries can lead to speech loss, creating a critical need for advanced communication aids.
Brain-computer interfaces (BCIs) offer a potential solution by translating neural activity into speech or text.
Existing BCIs have shown success in restoring movement and typing, positioning speech BCIs as the next major advancement.

Purpose of the Study:

To review the clinical demand for speech BCIs.
To survey foundational research on decoding speech from brain activity.
To outline recent advancements and future challenges in speech BCI development.

Main Methods:

Review of foundational neuroscience studies on speech representation in the brain.
Analysis of recent progress in discrete and continuous speech decoding techniques.
Examination of closed-loop speech BCI systems and performance metrics.

Main Results:

Identification of key brain regions and neural patterns associated with speech production.
Demonstration of progress in decoding both individual sounds and continuous speech.
Development of metrics for evaluating speech BCI performance.

Conclusions:

Speech BCIs represent a promising frontier in assistive technology for communication restoration.
Significant advancements have been made in decoding neural signals for speech.
Further research is crucial to overcome remaining challenges and achieve clinically viable speech neuroprostheses.