Cracking the brain's code for facial identity.

Chang and Tsao appear to have figured out how facial identity is represented in the brain:

Highlights

•Facial images can be linearly reconstructed using responses of ∼200 face cells 

•Face cells display flat tuning along dimensions orthogonal to the axis being coded 

•The axis model is more efficient, robust, and flexible than the exemplar model 

•Face patches ML/MF and AM carry complementary information about faces

Summary

Primates recognize complex objects such as faces with remarkable speed and reliability. Here, we reveal the brain’s code for facial identity. Experiments in macaques demonstrate an extraordinarily simple transformation between faces and responses of cells in face patches. By formatting faces as points in a high-dimensional linear space, we discovered that each face cell’s firing rate is proportional to the projection of an incoming face stimulus onto a single axis in this space, allowing a face cell ensemble to encode the location of any face in the space. Using this code, we could precisely decode faces from neural population responses and predict neural firing rates to faces. Furthermore, this code disavows the long-standing assumption that face cells encode specific facial identities, confirmed by engineering faces with drastically different appearance that elicited identical responses in single face cells. Our work suggests that other objects could be encoded by analogous metric coordinate systems.

From their introduction, their rationale for where they recorded in the inferior temporal cortex (IT):

To explore the geometry of tuning of high-level sensory neurons in a high-dimensional space, we recorded responses of cells in face patches middle lateral (ML)/middle fundus (MF) and anterior medial (AM) to a large set of realistic faces parameterized by 50 dimensions. We chose to record in ML/MF and AM because previous functional and anatomical experiments have demonstrated a hierarchical relationship between ML/MF and AM and suggest that AM is the final output stage of IT face processing. In particular, a population of sparse cells has been found in AM, which appear to encode exemplars for specific individuals, as they respond to faces of only a few specific individuals, regardless of head orientation. These cells encode the most explicit concept of facial identity across the entire face patch system, and understanding them seems crucial for gaining a full understanding of the neural code for faces in IT cortex.