Mapping neural activity to corresponding behaviors is a major goal for neuroscientists developing brain–machine interfaces (BMIs): devices that read and interpret brain activity and transmit instructions to a computer or machine. Though this may seem like science fiction, existing BMIs can, for example, connect a paralyzed person with a robotic arm; the device interprets the person’s neural activity and intentions and moves the robotic arm correspondingly.
A major limitation for the development of BMIs is that the devices require invasive brain surgery to read out neural activity. But now, a collaboration at Caltech between the laboratories of Richard Andersen, James G. Boswell Professor of Neuroscience and Leadership Chair and director of the Tianqiao and Chrissy Chen Brain–Machine Interface Center and Mikhail Shapiro, professor of chemical engineering, HMRI Investigator and affiliated faculty member with the Chen Institute, has developed a new type of minimally invasive BMI to read out brain activity corresponding to the planning of movement. Using functional ultrasound (fUS) technology, it can accurately map brain activity from precise regions deep within the brain at a resolution of 100 micrometers (the size of a single neuron is approximately 10 micrometers).
The new fUS technology is a major step in creating less invasive, yet still highly capable, BMIs.