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Frontiers | Locations in the Neocortex: A Theory of Sensorimotor Object Recognition Using Cortical Grid Cells

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Citation numbers are available from Dimensions University of Zurich, Switzerland International School for Advanced Studies (SISSA), Italy University of Edinburgh, United Kingdom Jeff Hawkins, Marcus Lewis, Mirko Klukas, Scott Purdy and Subutai Ahmad Jeff Hawkins, Subutai Ahmad and Yuwei Cui Jeff Hawkins and Subutai Ahmad Yuwei Cui, Subutai Ahmad and Jeff Hawkins Max Bennett The neocortex is capable of anticipating the sensory results of movement but the neural mechanisms are poorly understood. In the entorhinal cortex, grid cells represent the location of an animal in its environment, and this location is updated through movement and path integration. In this paper, we propose that sensory neocortex incorporates movement using grid cell-like neurons that represent the location of sensors on an object. We describe a two-layer neural network model that uses cortical grid cells and path integration to robustly learn and recognize objects through movement and predict sensory stimuli after

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