Memory Retrieved from Single Neurons

The paper examines the problem of accessing a vector memory from a single neuron in a Hebbian neural network. It begins with the review of the author’s earlier method, which is different from the Hopfield model in that it recruits neighboring neurons by spreading activity, making it possible for single or group of neurons to become associated with vector memories. Some open issues associated with this approach are identified. It is suggested that fragments that generate stored memories could be associated with single neurons through local spreading activity.