School of Computer Science and Communication, Stockholm University, Sweden
Wednesday 26 September 2007
Seminar Room B10 (Basement)
Alexandra House, 17 Queen Square, London, WC1N 3AR
Dynamic associative memory properties of a biophysically detailed neuronal network model of neocortical layers 2/3
One of the earliest and longest surviving theories of brain function is the theory of cell assemblies the conception of which is commonly attributed to Donald Hebb. A critical component of the theory is Hebbian synapses displaying associative plasticity, another one is the cell assembly formed in the recurrent cortical "attractor" neuronal networks by means of Hebbian synaptic plasticity. The relevance of such a cell assembly or attractor networks theory for describing the associative memory properties of the real neuronal networks of the brain has been unclear for quite some time. I will describe some simulations of a biophysically detailed large-scale network model developed at KTH aimed at investigating this issue. We have demonstrated that a network of pyramidal cells and two types of inhibitory interneurons connected by glutamatergic and GABA-ergic synapses, forming a network similar to that of the mammalian neocortex, could indeed work according to Hebb's conceputal theories. The simulated network displays the relevant associative memory functions, e.g. recall and rivalry, on time scales compatible with those seen psychologically. It reproduces several dynamic phenomena seen experimentally at the cellular as well as at the microcircuit and global network levels, and further provides possible explanations for cognitive phenomena like e.g. attentional blink.