IMPROVING ASSOCIATIVE MEMORY IN A NETWORK OF SPIKING NEURONS

Associative neural network models arc a commonly used methodology when investigating the theory of associative memory in the brain. Comparisons between the mammalian hippocampus and associative memory models of neural networks have been investigated [12]. Biologically based networks are systems built of complex biologically realistic cells with a variety of properties. Here we compare and contrast associative memory function in a network of biologically-based spiking neurons [22] with previously, published results for a simple. artificial neural network model [11]. We shall focus primarily oil the recall process from a memory where patterns have previously been stored by Hebbian learning. we investigate biologically plausible implementations of methods for improving recall under biologically realistic conditions, such as a, sparsely connected network. Network dynamics under recall conditions are. further tested using network configurations including complex multi-compartment inhibitory interneurons, known as basket cells.