Researchers discover 'spooky' similarity in how brains and computers see

The brain detects 3-D shape fragments (bumps, hollows, shafts, spheres) in the beginning stages of object vision--a newly discovered strategy of natural intelligence that Johns Hopkins University researchers also found in artificial intelligence networks trained to recognize visual objects. A new paper in Current Biology details how neurons in area V4, the first stage specific to the brain's object vision pathway, represent 3-D shape fragments, not just the 2-D shapes used to study V4 for the last 40 years. The Johns Hopkins researchers then identified nearly identical responses of artificial neurons, in an early stage (layer 3) of AlexNet, an advanced computer vision network. In both natural and artificial vision, early detection of 3-D shape presumably aids interpretation of solid, 3-D objects in the real world. "I was surprised to see strong, clear signals for 3-D shape as early as V4," said Ed Connor, a neuroscience professor and director of the Zanvyl Krieger Mind/Brain Institute.