Improving associative memory in a network of spiking neurons

Russell Hunter, Stuart Cobb, Bruce P. Graham

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)


Associative neural network models are 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 arc 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 on 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.

Original languageEnglish
Pages (from-to)447-470
Number of pages24
JournalNeural Network World
Issue number5
Publication statusPublished - 18 Dec 2009


  • associative memory
  • basket cell
  • inhibition
  • mammalian hippocampus
  • neural networks
  • pattern recall


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