The connectionist model of reasoning presented here, INFERNET, implements a working memory that is the activated part of long-term memory. This is achieved by making use of temporal properties of the node spikes. A particular solution of the problem of multiple instantiation is proposed. This model makes predictions that have been tested experimentally and the results of these experiments are reported here. These results would seem to challenge modular models of memory. 1 Introduction Connectionist models of working memory face two main problems. The first is the binding problem; the second is the problem of multiple instantiation. The model presented here draws its inspiration from neurobiology in an attempt to solve these problems. Different aspects of the same stimulus are not processed by the same neurons. The brain has to link together these various aspects (e.g., color, contours, movement) in order to differenciate them from other objects. This is referred to as variable..
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