Abstract
In order to understand a neural basis for the binding problem, we propose a neural network model that is constructed based on dynamical map theory. In the architecture, object stimulation activates sets of neurons of the different sensory networks, where all the features of an object are stored as point attractors in the networks. Relations among these features are encoded as a point attractor in the integration network. Model simulations show that dynamic linkages among point attractors across the different networks play a key role in solving the binding problem, in which the integration network serves to mediate the binding.
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