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Rodent Behavioral Testing to Assess Functional Deficits Caused by Microelectrode Implantation in the Rat Motor Cortex

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Implantable brain machine interfaces: first-in-human studies, technology challenges and trends.

Adrien B Rapeaux¹, Timothy G Constandinou¹

¹Department of Electrical and Electronic Engineering, Imperial College London, UK; Centre for Bio-Inspired Technology, Imperial College London, UK; Care Research and Technology (CR&T) based at Imperial College London and the University of Surrey, UK Dementia Research Institute (UK DRI), UK.

Current Opinion in Biotechnology

|November 8, 2021

Summary

Implantable brain-machine interfaces (BMIs) are advancing rapidly, moving from last resort treatments to elective options. Recent breakthroughs enable sophisticated control of cursors, prosthetics, and communication through decoded brain activity.

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An Experimental Platform to Study the Closed-loop Performance of Brain-machine Interfaces

An Experimental Platform to Study the Closed-loop Performance of Brain-machine Interfaces

Published on: March 10, 2011

Area of Science:

Neuroscience
Biomedical Engineering
Medical Technology

Background:

Implantable brain-machine interfaces (BMIs) are transitioning from niche applications to mainstream use.
BMIs are increasingly considered for earlier intervention in disease treatment.
Technological advancements are driving significant progress in BMI capabilities.

Purpose of the Study:

To review recent developments in implantable brain-machine interfaces.
To describe the paradigm shift in BMI development.
To highlight innovations, insights, and translation of BMIs.

Main Methods:

Review of first-in-human successes in decoding dexterous motor skills and speech from cortical activity.
Analysis of technological advancements in neural activity observation, implant architectures, flexible substrates, packaging, surgical workflows, and data processing.
Examination of new regulatory guidance, funding, and investment in BMI commercialization.

Main Results:

Demonstrated ability to decode handwriting and speech for cursor/prosthesis control, direct-to-text communication, and speech synthesis.
Advancements in observing more neural activity channels via new implant architectures.
Progress in materials, surgical techniques, and data processing for enhanced BMI performance.

Conclusions:

The field of BMIs is experiencing a paradigm shift driven by technological progress and increased investment.
BMIs are poised for broader adoption and commercialization, offering new therapeutic and assistive possibilities.
Continued innovation in hardware, software, and regulatory pathways is crucial for BMI translation.