Attractor Network Models of Cortical Associative Memory

Attractor network models of cortical associative memory functions have developed considerably over the past few years. Here we show that we can improve them further, in terms of correspondence with cortical connectivity, by using multiple cells in lamina II/III of cortical columns connected by long-range bers as the functional unit in the network instead of just a single cell. The connectivity of the model then becomes more realistic, since the original dense and symmetric connectivity now may be sparse and strongly asymmetric at the cell-to-cell level. Our simulations show that this kind of network, with model neurons of the Hodgkin-Huxley type arranged in columns, can operate as an associative memory in much the same way as previous models having a simpler connectivity. Cell activities comply with experimental ndings and reaction times are within biological and psychological limits. By introducing a scaling model we make it plausible that a network approaching experimentally repor...

• Type: Conference
• Year: 1997
• Where: BCEC
• Authors: Anders Lansner, Erik Fransén
• Keywords: Applied Computing, Attractor Network Models, BCEC 1997, Cortical Associative Memory, Cortical Connectivity