Abstract
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 language | English |
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Pages (from-to) | 447-470 |
Number of pages | 24 |
Journal | Neural Network World |
Volume | 19 |
Issue number | 5 |
Publication status | Published - 18 Dec 2009 |
Keywords
- associative memory
- basket cell
- inhibition
- mammalian hippocampus
- neural networks
- pattern recall