WORKING MEMORY AND TEMPORAL PATTERNS: THE IMPLICATIONS OF NEURAL POPULATIONS

Working memory, the ability to temporarily retain information which will be used to guidesubsequent behavior, is a central component of our cognitive abilities. Almost 40 years ago,electrophysiological experiments in monkeys established that persistent activity may be theneuronal substrate of working memory. Many computational models have been proposedin order to explain persistent activity, with recurrent connections playing a prominent rolein many of these. No model, however, has captured all the important features in workingmemory networks. This work presents three related models which seek to understand someof these features. In particular, the first model explores the formation of firing rate patternsduring the delay period of working memory tasks; the second model explores the dynamicsof working memory networks with reduced inhibition, and their possible role in epilepsy;the third model explores the formation of temporal sequences and closed loops of activity.The three models assume the existence of densely connected neural populations (such asminicolumns), which respond similarly to the same stimuli. Another common feature is therole of dynamic synapses: the first two models rely on synaptic facilitation, whereas thethird uses temporally asymmetric Hebbian plasticity