Update: Standardizing the Brain-Machine Interface

Researchers have endowed subjects with seemingly telekinetic powers by extracting the patterns of brain activity that occur when we move parts of our bodies. However those patterns are tapped electronically, algorithms are needed to interpret them and discern their salient features so that the appropriate signals can be sent to external devices. Groups working on brain-machine interfaces have designed brain decoders differently, depending on the type of neural data they collect and the purposes of their research. As a result, most algorithms have to be written from the ground up. But some in the field say it's time to develop a generic algorithm that will incorporate the best work of the last decade and serve as a foundation for all labs working on neural prosthetics. This paper discsusses the work done by Srinivasan et al., wherein they pulled together elements of algorithms from all the major labs that design brain-machine interfaces and proposed a new approach that theoretically would support and enhance each design.