Decoding the Brain’s Facial Recognition

In what’s being called “a major breakthrough that is destined to be famous for as long as people read about neuroscience,” researchers at Pasadena’s California Institute of Technology have successfully reconstructed facial images by monitoring just 205 neurons in monkey brains.

It was previously thought that facial recognition in the brain was much more complex; perhaps specific facial features were encoded somehow, and matched against a database of people you know in order to yield instant recognition of the people that are important to you. But, all it takes is a couple of hundred neurons to successfully distill a face down to the features you need to recognize it.

This study correlated the output of the brain’s “face patch” of neurons with measurements of the shapes of faces – for example, the distance between the eyes – and the color and texture of the skin. Nothing more. By doing this, they were able to reconstruct images of faces based purely on the activity of these neurons, which humans were able to recognize compared to original photos 80% of the time.

These findings were reported yesterday in the journal Cell.

As a computer scientist, I find these results especially exciting. It suggests that a task as complex as facial recognition can be accomplished with hardly any “hardware” – the magic is in the algorithms our brains have evolved. This means artificial intelligence may be closer than we thought, if we can continue to crack this code.


Image credit: iStock.com / bowie15

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