Which model to use for cortical spiking neurons?
IEEE Transactions on Neural Networks
| Hi-index | 0.02 |
Theta frequency oscillations are a prominent feature of the hippocampal EEG during active locomotion and learning. It has also been observed that the relative timing of place cell firing recedes as its place field is traversed --- a phenomena known as phase precession. This has led to the development of a theory of theta phase coding, whereby spatial sequences being encountered on a behavioural timescale are compressed into a firing sequence of place cells which is repeated in each theta cycle and stored in an auto-associative network using spike-timing dependent plasticity. This paper provides an abstract, descriptive model of theta phase coding in a spiking neural network, and aims to investigate how learning and recall functions may be separated by the neuromodulatory action of Acetylcholine (ACh). It is demonstrated that ACh is not essential for concurrent learning and recall without interference in this case, thanks to the robust nature of the theta phase coding implementation. However, the neuromodulation of synaptic plasticity offers other advantages, and may be essential to avoid continually consolidating false predictions when learning new routes.