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Spatial navigation model based on chaotic attractor networks
2004
Connection science
We present a model of spatial navigation based on the non-convergent dynamics of brain activity. The system includes a hippocampal module that processes global spatial information and a cortical module that deals with local sensory information. We test the model using several spatial navigation paradigms: goal finding, shortcutting and detouring. Computer simulations show that the performance of the agent qualitatively matches that of animals and related models. This new approach provides a
doi:10.1080/09540090410001664641
fatcat:bkijao4ly5clzpmees2hshc7j4