A recurrent attractor network model of memory in the cortex

The talk will describe a spiking neural network model of mammalian cortex and illustrate its learning and associative memory functions. It will start from the properties of component model neurons and plastic synapses and a modular cortical architecture.

The dynamics of such a network in terms of bursting, spike synchronization and oscillations will be described.
Network function will be illustrated in terms of how encoding and recall of different forms of memories can be modelled and understood, with specific examples of sequence learning and of synaptic working memory.