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What is the Brain-Machine Interface

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Jul. 2013

The ability to dynamically reconfigure hardware components has become critical to many computing systems. For example, to maintain optimal performance when the protocols, data rates, or physical medium attachment (PMA) layers change in communications systems, it is often essential to able to change more than just the software. Modern FPGA (field-programmable gate array) chips, which can be partially reconfigured at run time, are now in ubiquitous use to meet some of these needs in dedicated systems. For the rapidly advancing class of chips that have been developed to communicate with the brain, the ability to dynamically reconfigure the interface nodes has emerged as one of the most desirable features. A group of researchers from the Swiss Federal Institute of Technology has built a powerful new chip that can be rapidly adapted to changing conditions at its interface points. Furthermore, they have used their chip to show that the speed of communication between neurons is not independent from any computations a brain might be said to perform, but rather, it is an essential component of the computation itself.

The chip developed by the Swiss group has some 11,011 electrodes packed into a CMOS chip with area less than 2x2mm. At 3,150 electrodes per square millimeter, that’s a higher density than anything we have seen to date. High-density chips with up to 65,000 stimulation sites have been manufactured before by other groups, but they generally have had little or no record (measure) ability. The key feature here is that the 126 signal-conditioned and amplified channels can be dynamically switched within a few milliseconds to any of the electrode sites in the grid, permitting multiresolutional access to neurons in its field on different spatial scales. The analog switch matrix which makes this possible consists of 13,00 static RAM cells which set the routing.

What the researchers have essentially built here is a voltage microscope for neurons. When they trained it on an individual cell, the researchers could actually watch the real time propagation of an electrical spike down an axon. Suprisingly, they found that the speed of this pulse changed from moment to moment at every segment along the axon. Normally in the brain, the axons are wrapped up by special glial cells called oligodendrocytes, which make signal transmission more efficient. Glial cells were part of the culture preparation used here, but it is not clear to what extent, if any, they participated in these regulatory effects. In the absence of functional oligodendrocytes, the axons themselves could in theory control propagation speed by altering the density of ion channels in their membranes.

The researchers were able to stimulate different points in the grid to generate spikes going in either direction down axons. Their analysis did not specifically address the interesting question of whether spikes sent in the normal direction (away from the cell body), actually propagate faster by virtue of directionally-organized machinery based on the subcellular cytoskeleton ? but that could in principle be investigated later.

The ability to “watch” neurons electrically on multiple scales has many advantages over techniques that rely on slower, and potentially phototoxic, imaging dyes. Not to take anything away from them them, bu these optical reporters sometimes interfere with the natural cell physiology and, as for the case of calcium dyes, can modulate the very effect they attempt to measure. When mapped to its highest resolution, the chip could actually resolve changes in the shape and position of the axons over time. Theoretically these movements could be correlated with the electrical activity, giving new insight into how neurons grow and interconnect. Being able to watch these movements is useful to understand what happens when the signal drops out after the recording has been going on for a while. Often this loss is attributed to changes in electrode impedance from build up of extracellular material, or other reactive tissue effects, but in fact it could just be that the cell has moved.

As these new chips are adapted to more complex 3D geometries they will be better suited for use inside intact brains. Undoubtedly they will be of great value in creating stable, and more nimble, interfaces to the brain.

What is the Brain-Computer Interface Technology

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