Untangling invariant object recognition.
Despite tremendous variation in the appearance of visual objects, primates can recognize a multitude of objects, each in a fraction of a second, with no apparent effort. However, the brain mechanisms that enable this fundamental ability are not understood. Drawing on ideas from neurophysiology and computation, we present a graphical perspective on the key computational challenges of object recognition, and argue that the format of neuronal population representation and a property that we term 'object tangling' are central. We use this perspective to show that the primate ventral visual processing stream achieves a particularly effective solution in which single-neuron invariance is not the goal. Finally, we speculate on the key neuronal mechanisms that could enable this solution, which, if understood, would have far-reaching implications for cognitive neuroscience.
DiCarlo
James J
JJ
McGovern Institute for Brain Research, and Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA. dicarlo@mit.edu
Cox
David D
DD
D000818:Animals; D001288:Attention / Q000502:physiology; D001921:Brain / Q000502:physiology*; D003071:Cognition / Q000502:physiology*; D003210:Concept Formation / Q000502:physiology; D003657:Decision Making / Q000502:physiology; D003867:Depth Perception / Q000502:physiology; D004193:Discrimination Learning / Q000502:physiology; D006801:Humans; D008962:Models, Theoretical; D009474:Neurons / Q000502:physiology; D010364:Pattern Recognition, Visual / Q000502:physiology*; D011323:Primates; D012160:Retina / Q000502:physiology*; D014795:Visual Pathways / Q000502:physiology