Use this URL to cite or link to this record in EThOS:
Title: STDP, rate-coded Hebbian learning and auto-associative network models of the hippocampus
Author: Bush, Daniel
ISNI:       0000 0004 2671 2399
Current Institution: University of Sussex
Date of Award: 2009
Availability of Full Text:
Full text unavailable from EThOS. Restricted access.
Please contact the current institution’s library for further details.
Auto-associative network models have proven extremely useful in modelling the hypothesised function of the CA3 region of the hippocampus in declarative memory. To date, the majority of these models have made use of Hebbian plasticity rules mediated by correlations between mean firing rates. However, recent neurobiological evidence suggests that synaptic plasticity in the hippocampus, and many other cortical regions, also depends explicitly on the temporal relationship between afferent action potentials and efferent spiking - a phenomena known as spike-timing dependent plasticity (STDP). Few attempts have been made to reconcile previous rate-coded Hebbian learning rules or auto-associative network function with this novel plasticity formulation.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available