Associative Memory in a Network of `Biological' Neurons

The Hopfield network (Hopfield, 1982,1984) provides a simple model of an associative memory in a neuronal structure. This model, however, is based on highly artificial assumptions, especially the use of formal-two state neu(cid:173) rons (Hopfield, 1982) or graded-response neurons (Hopfield, 1984). First, we show that a simple model of a neuron can capture all relevant features of neuron spiking, i. e., a wide range of spiking frequencies and a realistic distribution of interspike inter(cid:173) vals. Second, we construct an associative memory by linking these neurons together. The analytical solution for a large and fully connected network shows that the Hopfield solution is valid only for neurons with a short re(cid:173) fractory period.