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What is the Brain-Machine Interface
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University of California Berkeley neuroscientists have proposed a new brain-machine interface system that allows for thousands of ultra-tiny "neural dust" chips to be inserted into the brain to monitor neural signals at high resolution and communicate data highly efficiently via ultrasound.
Emerging technologies like functional magnetic resonance imaging (FMRI), magnetoencephalopathy and positron emission tomography are allowing the measurement of neuron clusters in the living brain.
This work is revolutionizing our understanding of the way the brain is structured and behaves. It has also lead to a new engineering discipline of brain-machine interfaces (BMI), which allows people to communicate and control machines by thought alone. For paralyzed people this development has allowed users to control robotic arms with thought alone.
Now, University of California Berkeley neuroscientists have proposed a concept system that uses thousands of ultra-tiny neural dust chips to be inserted into the brain to monitor neural signals at high resolution and communicate data highly efficiently via ultrasound.
The neural dust design promises to overcome a serious limitation of current invasive brain-machine interfaces: the present range of implantable neural interface devices are, over time, rejected by the body. Current BMI systems are also limited to several hundred implantable recording sites, they generate tissue responses around the implanted electrodes that degrade recording performance over time.
Neural dust potentially provide the large-scale recording of neurons required for the Brain Research through Advancing Innovative Neurotechnologies (BRAIN) initiative, the scientists suggest.
The concept, published recently in the papter, "Neural Dust: An Ultrasonic, Low Power Solution for Chronic Brain-Machine Interfaces," is to sprinkle electronic sensors the size of dust particles into the cortex and to interrogate them remotely using ultrasound. The ultrasound also powers this so-called neural dust.
Each particle of neural dust consists of standard CMOS circuits and sensors that measure the electrical activity in neurons nearby. This is coupled to a piezoelectric material that converts ultra-high-frequency sound waves into electrical signals.
The neural dust is interrogated by another microprocessor placed beneath the skull but powered from outside the body. This generates the ultrasound that powers the neural dust and sensors that listen out for their response.
The researchers calculate that the neural dust chips can be as much as 10 million times more efficient that chips using electromagnetics (magnetic or electric signals), which have high attenuation in brain tissue. They would be encapsulated in an inert polymer or insulator ?lm.
The study authors, Dongjin Seo, Jose M. Carmena, Jan M. Rabaey, Elad Alon, Michel M. Maharbiz, who a few years ago came to prominence with their work on remote controlling insects, have published the concept in order to get others thinking about the challenges and technical issues involved in the neural dust concept.
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