The
brain has an amazing capacity for recognizing faces. It can identify a
face in a few thousandths of a second, form a first impression of its
owner and retain the memory for decades.
Central
to these abilities is a longstanding puzzle: how the image of a face is
encoded by the brain. Two Caltech biologists, Le Chang and Doris Y.
Tsao, reported in Thursday’s issue of Cell that they have deciphered the code of how faces are recognized.
Their
experiments were based on electrical recordings from face cells, the
name given to neurons that respond with a burst of electric signals when
an image of a face is presented to the retina.
By
noting how face cells in macaque monkeys responded to manipulated
photos of some 2,000 human faces, the Caltech team figured out exactly
what aspects of the faces triggered the cells and how the features of
the face were being encoded. The monkey face recognition system seems to
be very similar to that of humans.
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Just
200 face cells are required to identify a face, the biologists say.
After discovering how its features are encoded, the biologists were able
to reconstruct the faces a monkey was looking at just by monitoring the
pattern in which its face cells were firing.
The
finding needs to be confirmed in other laboratories. But, if correct,
it could help understand how the brain encodes all seen objects, as well
as suggesting new approaches to artificial vision.
“Cracking the code for faces would definitely be a big deal,” said Brad Duchaine, an expert on face recognition at Dartmouth.
It
is a remarkable advance to have identified the dimensions used by the
primate brain to decode faces, he added — and impressive that the
researchers were able to reconstruct from neural signals the face a
monkey is looking at.
Human
and monkey brains have evolved dedicated systems for recognizing faces,
presumably because, as social animals, survival depends on identifying
members of one’s own social group and distinguishing them from
strangers.
In
both species, the face recognition system consists of face cells that
are grouped into patches of at least 10,000 each. There are six of these
patches on each side of the brain, situated on the cortex, or surface,
just behind the ear.
When
the image of a face hits the retina of the eye, it is converted into
electric signals. These pass through five or six sets of neurons and are
processed at each stage before they reach the face cells. As a result,
these cells receive high-level information about the shape and features
of a face.
One
way in which the brain might identify faces is simply to dedicate a
cell to each face. Indeed, there are cells in another part of the brain
that do respond to images of specific people.
They are known to neuroscientists as Jennifer Aniston cells, after one such cell in an epilepsy
patient undergoing surgery in 2005 responded when the patient was shown
images of the actress. The cell ignored all other images, including one
of her with Brad Pitt.
But
this can’t be the way the brain identifies faces, because we can
perceive a face we have never seen before. Instead, the Caltech team has
found, the brain’s face cells respond to the dimensions and features of
a face in an elegantly simple, though abstract, way.
In their experiments, the biologists first identified groups of face cells in a macaque monkey’s brain by magnetic resonance imaging, and then probed individual face cells with a fine electrode that records their signals.
The
monkeys were shown photos of human faces that were systematically
manipulated to show differences in the size and appearance of facial
features.
Cells
at a high level in the brain often respond to a medley of things,
making it hard to figure out what the cell is meant to do. The Caltech
team was able to create faces that showed exactly what each face cell
was tuned to.
The
tuning of each face cell is to a combination of facial dimensions, a
holistic system that explains why when someone shaves off his mustache,
his friends may not notice for a while. Some 50 such dimensions are
required to identify a face, the Caltech team reports.
These
dimensions create a mental “face space” in which an infinite number of
faces can be recognized. There is probably an average face, or something
like it, at the origin, and the brain measures the deviation from this
base.
A
newly encountered face might lie five units away from the average face
in one dimension, seven units in another, and so forth. Each face cell
reads the combined vector of about six of these dimensions. The signals
from 200 face cells altogether serve to uniquely identify a face.
Dr.
Tsao said she was particularly impressed to find she could design a
whole series of faces that a given face cell would not respond to,
because they lacked its preferred combination of dimensions. This ruled
out a possible alternative method of face identification: that the face
cells were comparing incoming images with a set of standard reference
faces and looking for differences.
Nancy
Kanwisher, a neuroscientist at M.I.T., said it was a major advance to
describe what a face cell does and predict how it will respond to a new
stimulus. But she suggested that more than 50 dimensions might be needed
to capture the full richness of human perception and the idiosyncrasies
of particular faces.
“Do we need a dimension for Jack Nicholson’s eyebrows?” she asked.
Dr.
Tsao has been working on face cells for 15 years and views her new
report, with Dr. Chang, as “the capstone of all these efforts.” She said
she hoped her new finding will restore a sense of optimism to
neuroscience.
Advances
in machine learning have been made by training a computerized mimic of a
neural network on a given task. Though the networks are successful,
they are also a black box because it is hard to reconstruct how they
achieve their result.
“This
has given neuroscience a sense of pessimism that the brain is similarly
a black box,” she said. “Our paper provides a counterexample. We’re
recording from neurons at the highest stage of the visual system and can
see that there’s no black box. My bet is that that will be true
throughout the brain.”
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