Reverse image searching with your brain is now for real, so long as you're looking for either Josh Brolin or Marilyn Monroe and can provide your own set of intracranial electrodes. In a recent experiment, researchers hooked twelve people up to a game where they fought to display a particular image on a screen by firing the correct neurons in their brain. Though the device was only successful about two-thirds of the time, it works much more rapidly than many other brain-machine interfaces and on much more specific targets.

Brain-computer interfacing has made some impressive progress over the last few years in both humans and primates. But researchers have recently become interested in whether people are able to exert control over specific neurons in real time, to the exclusion of other neurons. This level of fine-grained control may be essential to get a computer to accomplish a task.

In the new work, scientists used twelve people who already have intracranial electrodes installed in their brains to help prevent epileptic episodes. They presented the subjects with two pictures—one of Josh Brolin, the other of Marilyn Monroe—and recorded which sets of neurons in the medial temporal lobe (MTL) fired as the subjects viewed each picture.

The subjects were then shown the two images superimposed on each other, and had to "will" the superposition to fade into a distinct Josh Brolin or Marilyn Monroe by trying to fire the relevant set of neurons. They were given between three and five seconds to complete the task.

Despite having no training in firing particular sets of neurons, the subjects were successful in forcing the image to resolve into one subject 69 percent of the time. The authors found that the subjects had slightly more success if the sets of neurons associated with each picture were in different hemispheres or regions of the brain.

The authors note that a single concept can be represented by up to one million MTL neurons, though often far fewer are required. Googling with your brain rather than your keyboard may still be a ways into the future, but we may be getting closer.

Nature, 2010. DOI: 10.1038/nature09510 (About DOIs).