Editorial Feature

Neural Dust to Decode Brain Signals

There is a vast amount of engineering effort to understand the intricacies of how neural networks communicate in the brain.

A recent paper has described a system concept termed ‘neural dust’- a low power miniaturized system to support brain–machine interfaces described as free-floating sensor nodes at 10-100 μm in scale.

We are continuing to see advancements in imaging technology including magnetic resonance imaging and positron emission tomography techniques to help scientists unravel communication behaviour of neuron-to-neuron interaction. Of course, these systems typically carry the limitation of being invasive and having limited spatial resolution.

Dongjin Seo and a team of researchers and the University of California, Berkeley, have devised a system design that involves a neural dust system, either in the active node as a piezoelectric transducer measuring the amount of power retrieved at a target site in the brain (i.e., the amount of power required to achieve activation of a CMOS sensing element to collect and process the data on nearby neurons), or a passive node which focuses on the reflectivity of the neural dust and generates electrophysiological data.

Credits: Photos.com

A sub-cranial interrogator is also part of this system concept used for powering the neural dust. In their most recent work, these researchers describe implantation of the interrogator.

The external transceiver sits on the skull and is in control of the data processing. The sub-dural transceiver acts as the ultrasound transceiver to the neural dust encapsulated with a polymer layer.

The neural dust is coated with a polymer, has a recording site and drive electrodes. The main functional process of this system then involves coupling of ultrasound energy by the interrogator delivering this into the brain tissue to provide spatial and frequency information on each sensing node.

This advancement really does bring science one step closer to unravelling the key to making brain–machine interfaces last a lifetime. However, with all such intricate developments there are constraints.

With the current concept, size and power are a constraint. Miniaturisation of a sensor device limits the distance between the different recording points and this will be a major challenge for miniaturised sensor devices.

This system concept takes mind control to a new level of decoding brain signals. By being able to transmit data on neural activity from the surface of the brain, these implantable sensor nodes could eliminate the need for wires to be attached to the surface of the skull in order to monitor and analyse brain activity.

Could this control our thoughts? The idea of creating a more sophisticated method to making brain-machine interface systems viable for a lifetime will be particularly fundamental to helping people with disabilities have better control and freedom of robotic prosthetic limbs.

Whilst neural dust is still a concept, it requires further development of the design and implementation of sub-cranial electronic sensor nodes particularly on methods to help the delivery of this dust into the brain without damage to surrounding tissue.



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