Mind-reading AI: Researchers decode faces from brainwave patterns (PHOTOS)

Researchers from the Kuhl Lab at the University of Oregon explored how faces could be decoded from neural activity in the study Reconstructing Perceived and Retrieved Faces from Activity Patterns in Lateral Parietal Cortex, published in the Journal of Neuroscience. Hongmi Lee and Brice A. Kuhl tested whether faces could be reconstructed from the'angular gyrus' (ANG) located in the upper back area of the brain through functional magnetic resonance imaging (fMRI) activity patterns. They conducted the experiment by making facial reconstructions based on brainwave patterns from participants, initially during their perception of faces and later just from memory. Participants were shown more than 1,000 color photos of different faces, one after another, while an fMRI scan recorded their neural responses. The researchers then applied principal component analysis (PCA) to generate 300 'eigenfaces' - a set of vectors used in human face recognition.