  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.
