Researchers Crack the Brain's Facial-Recognition Code

Two Caltech biologists, Le Chang and Doris Y. Tsao, reportedly have deciphered the code of how faces are recognized. Tsao and coauthor Le Chang used statistical analyses to identify 50 variables that accounted for the greatest differences between 200 face photos. Those variables represented somewhat complex changes in the face — for instance, the hairline rising while the face becomes wider and the eyes becomes further-set.


The researchers turned those variables into a 50-dimensional “face space,” with each face being a point and each dimension being an axis along which a set of features varied.


Sensors 2018 Hits Silicon Valley June 26-28!

Join thousands of engineers this June in San Jose at the sensor industry’s biggest event! With 65+ Technical Sessions, 100+ Leading Speakers, and 300+ Interactive Exhibits, there’s more opportunity than ever to connect with this booming industry and the technologies driving it. See thousands of the newest technologies in action, learn about the latest applications, including AI, Autonomous Vehicles, IoT, and Medical, and develop invaluable partnerships at the only event dedicated to sensors, connectivity, and systems.


Then, Tsao and Chang extracted 2,000 faces from that map, each linked to specific coordinates. While projecting the faces one at a time onto a screens in front of two macaque monkeys, the team recorded the activity in single neurons in parts of the monkey’s temporal lobe known to respond specifically to faces. All together, the recordings captured activity from 205 neurons.


Each face cell was tuned to one of the 50 axes previously identified, Tsao and Chang found. The rate at which each cell sent electrical signals was proportional to a given face’s coordinate position along an axis. But a cell didn’t respond to changes in features not captured by that axis. For instance, a cell tuned to an axis where nose width and eye size changed wouldn’t respond to changes in lip shape. 


“We've really cracked the code for how facial identity is represented in the brain,” says Doris Tsao, a neuroscientist at the California Institute of Technology (Caltech) in Pasadena who led the study. “This is the first time [we’ve understood] the code for a high-level object in any sensory system.”


The finding needs to be confirmed in other laboratories, said Science News. But, if correct, it could help understand how the brain encodes all seen objects, as well as suggesting new approaches to artificial vision.


“It’s a turning point in neuroscience — a major breakthrough,” says Rodrigo Quian Quiroga, a neuroscientist at the University of Leicester in England who wasn’t part of the work. “It’s a very simple mechanism to explain something as complex as recognizing faces.”


Added, says Ed Connor, a neuroscientist at Johns Hopkins University in Baltimore, Maryland, to Science Magazine, the study represents a major breakthrough that is “destined to be famous” for as long as people read about neuroscience. “It’s something very close to the core of human experience, but here we're seeing the neural basis. For me, it just doesn't get more exciting.”