Brain Computer Interfaces have been around for several years and have benefitted from evolution in both sensors, communication and signal processing domains. Underlying these evolutions are several technologies and sciences including smart materials, optoelectronics, microelectronics, artificial intelligence.
There are still many issues that are hindering the effectiveness and applicability of BCI, among them of crucial importance is the sensitivity in capturing the electrical activity of the brain that in turns is related to the placement and number of sensors, their quality and the transmission of the signals detected to a computer for processing. So far the best sensitivity, and resolution, can be achieved through invasive -surgical- implantation of electrodes (sensors) on the brain cortex and in the brain itself. Apart (and it is no little issue, I understand) from the fact that an invasive procedure is not appealing there is the problem of connecting the implanted sensors to a computer, something that so far has required placing cables to go across the skull. This is both an unpleasant encumbrance and a source of infection.
Now a team at the Brown University and at the University of California San Diego (the Qualcomm Institute Circuits Lab at UC) have presented their results in developing tiny motes, they call them neurograins, some 0.25 square millimetre in size, that can be implanted on the brain cortex in hundreds and thousands. Each neurograin has an RF antenna that harvest RF coming from outside of the skull converting it into an electrical power sufficient to operate the grain and to establish wireless communications among the grains. This wireless brain networking is extended to the outside of the brain where a gateway picks up the signals transmitted by the neurograins and sends them to a computer, wirelessly of course. The researchers have shown that these brain wirelss network can sustain an uplink bandwidth up to 10 Mbps and a downlink bandwidth up to 1Mbps.
The use of RF to power the neurograins and their very low power need solve both the connection problem -no need for wires to go across the skull, and the heat dissipation -you don’t want to have the motes damaging the neurones on the brain cortex.
We are clearly at a very early stage but this result represent a significant step forward BCI that can detect complex patterns, such as the ones involved in playing a piano, whilst today’s BCI can just manage detecting a two axes movement (like a mouse moving a pointer). The neurograins are not detecting movement intentions, nor “thoughts floating around”; they just provide a much more accurate map of electrical activity. It is up to the computer, and the artificial intelligence software processing those signals, to work out the meaning.