Each time you see a person that you know, your brain rapidly and seemingly effortlessly recognizes that person by his or her face. “Faces are among the most compelling visual stimulation that we encounter, and recognizing faces taxes our visual perception system to the hilt. Carnegie Mellon has a longstanding history for embracing a full-system account of the brain. We have the computational tools and technology to push further into looking past one single brain region. And, that is what we did here to discover that there are multiple cortical areas working together to recognize faces,” she said.
For the study, participants were shown images of faces while in a magnetic resonance imaging (MRI) scanner. Their task was to recognize different facial identities with varying facial expressions. Using dynamic multivariate mapping, the research team examined the functional MRI (fMRI) data and found a network of fusiform and anterior temporal regions that respond with distinct patterns to different identities. Furthermore, they found that the information is evenly distributed among the anterior regions and that the right fusiform region plays a central role within the network. “Not only do we have a more clearly defined architectural model of the brain, but we were able to determine the involvement of multiple brain areas in face recognition as well as in other types of processes, such as visual word recognition,” Behrmann said.