Scientists at Johns Hopkins University are developing a new early warning system for seizures that is sensitive enough to detect imminent seizures without setting off a large number of false alarms. The software may someday be embedded in a microchip that would continually check electrical activity in the brain and launch electrical stimulation whenever a seizure is beginning to form.
During the President’s Lecture Series at San Diego State University two weeks ago, Qualcomm CEO Paul Jacobs said that the company is building a digital human brain. Stating that the brain isn’t programmed but rather taught, Jacobs emphasized that the company’s work was meant to help humanity through the “digital sixth sense” — the merging of the cyber and real worlds.
He described the process of discovery this way:
The team actually started out by building a retina and they came to me and said: ‘Look, it responds to these optical illusions the same way a human does.’ They put another layer of cells behind that [and] it started to find features. They put another layer, it started to find corners or oriented lines or something. Another layer, it started to find patterns.
Jacobs is talking about Brain Corporation, a small research company that is developing novel algorithms based on the functionality of the nervous system, with applications in visual perception, motor control, and autonomous navigation. The intention is to equip consumer devices, such as mobile phones or household robots, with artificial nervous systems. Qualcomm funds Brain Corporation research and hosts the company on its campus in San Diego, California.
Scientists at Brain Corporation are re-creating in the computer the shapes of every one of the billions of nerve cells that make up our brains, the component parts of intricate neural circuits that allow us to move, see and hear, to feel and to think. With this new tool, researchers are beginning to decipher the secrets of the brain’s architecture, which may one day enable us to build smart technologies that surpass the capabilities of anything we have today.
This video is based on a paper published by neuroscientist Hermann Cuntz, and colleagues in the online journal PLoS Computational Biology.