When Plato set out to define what made a human a human, he settled on two primary characteristics: We do not have feathers, and we are bipedal (walking upright on two legs). Plato’s characterization may not encompass all of what identifies a human, but his reduction of an object to its fundamental characteristics provides an example of a technique known as principal component analysis.

Now, Caltech researchers have combined tools from machine learning and neuroscience to discover that the brain uses a mathematical system to organize visual objects according to their principal components. The work shows that the brain contains a two-dimensional map of cells representing different objects. The location of each cell in this map is determined by the principal components (or features) of its preferred objects; for example, cells that respond to round, curvy objects like faces and apples are grouped together, while cells that respond to spiky objects like helicopters or chairs form another group.

The research was conducted in the laboratory of Doris Tsao (BS ’96), professor of biology, director of the Tianqiao and Chrissy Chen Center for Systems Neuroscience and holder of its leadership chair, and Howard Hughes Medical Institute Investigator. A paper describing the study appears in the journal Nature on June 3.

“For the past 15 years, our lab has been studying a peculiar network in the primate brain’s temporal lobe that is specialized for processing faces. We called this network the ‘face patch network.’ From the very beginning, there was a question of whether understanding this face network would teach us anything about the general problem of how we recognize objects. I always dreamed it would, and now this has been vindicated in a startling way. It turns out that the face patch network has multiple siblings, which together form an orderly map of object space. So, face patches are one piece of a much bigger puzzle, and we can now begin to see how the entire puzzle is put together,” says Tsao.

The brain’s inferotemporal (IT) cortex is a critical center for the recognition of objects. Different regions or “patches” within the IT cortex encode for the recognition of different things. In 2003, Tsao and her collaborators discovered that there are six face patches; there are also patches that encode for bodies, scenes, and colors. But these well-studied islands only make up some of IT cortex, and the functions of the brain cells located in between them have not been well understood.