By Helen Shen
Brain-controlled prosthetic devices have the potential to dramatically improve the lives of people with limited mobility resulting from injury or disease. To drive such brain-computer interfaces, neuroscientists have developed a variety of algorithms to decode movement-related thoughts with increasing accuracy and precision. Now researchers are expanding their tool chest by borrowing from the world of cryptography to decode neural signals into movements.
During World War II, codebreakers cracked the German Enigma cipher by exploiting known language patterns in the encrypted messages. These included the typical frequencies and distributions of certain letters and words. Knowing something about what they expected to read helped British computer scientist Alan Turing and his colleagues find the key to translate gibberish into plain language.
Many human movements, such as walking or reaching, follow predictable patterns, too. Limb position, speed and several other movement features tend to play out in an orderly way. With this regularity in mind, Eva Dyer, a neuroscientist at the Georgia Institute of Technology, decided to try a cryptography-inspired strategy for neural decoding. She and her colleagues published their results in a recent study in Nature Biomedical Engineering.
Continue reading by clicking the name of the source below.