Scientists in the US have accurately reconstructed images of human faces by monitoring the responses of monkey brain cells.
The brains of primates can resolve different faces with remarkable speed and reliability, but the underlying mechanisms are not fully understood.
The researchers showed pictures of human faces to macaques and then recorded patterns of brain activity.
The work could inspire new facial recognition algorithms, they report.
In earlier investigations, Prof Doris Tsao from the California Institute of Technology (Caltech) and colleagues had used functional magnetic resonance imaging (fMRI) in humans and other primates to work out which areas of the brain were responsible for identifying faces.
Six areas were found to be involved, all of which are located in part of the brain known as the inferior temporal (IT) cortex. The researchers described these six areas as “face patches”.
Further research showed that face patches were jammed with particular nerve cells (neurons) that emit signals more strongly when they’re presented with faces, rather than when they “see” other objects. The team members called these neurons “face cells”.
Prof Tsao’s team came up with 50 different dimensions that could describe a face, such as the distance between the eyes, or the width of the hairline, as well as non-shape-related features such as skin tone.
Then they inserted electrodes into the brains of macaque monkeys so that they could record individual signals from single face cells within the face patches.
The results, published in the journal Cell, suggest that around 200 neurons each encode different characteristics of a face. But when all are combined, the information contributed by each nerve cell allows the macaque brain to build a clear image of someone’s face.
“We’ve discovered that this code is extremely simple,” said Prof Tsao, who is based at Caltech’s campus in Pasadena.
“A practical consequence of our findings is that we can now reconstruct a face that a monkey is seeing by monitoring the electrical activity of only 205 neurons in the monkey’s brain.”
When placed side by side, photos that the monkeys were shown and faces recreated from their brain activity (using an algorithm) were nearly identical.
Face cells from just two of the face patches – 106 cells in one patch and 99 cells in another – were enough to reconstruct the faces.
“People always say a picture is worth a thousand words,” said Prof Tsao. “But I like to say that a picture of a face is worth about 200 neurons.”
Although the work is based on macaques, the close relationships between primates suggest that a comparable mechanism may operate in the human brain.
The findings challenge the idea, held by other scientists in the field, that each face cell in the brain recognises a particular type of face.
Further evidence against this idea came from the observation that when a large set of faces are engineered to look extremely different, they all cause a given face cell to fire in exactly the same way.
“This was completely shocking to us – we had always thought face cells were more complex. But it turns out each face cell is just measuring distance along a single axis of face space, and is blind to other features,” said Prof Tsao.
The Cell paper’s first author, Steve Le Chang, said the work suggested that “other objects could be encoded with similarly simple coordinate systems”.
One obvious potential application for the work is in the design of new machine learning algorithms for recognising faces. But there are others.
“One can imagine applications in forensics where one could reconstruct the face of a criminal by analysing a witness’s brain activity,” said Prof Chao.
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