Abstract / Description of output
A model of topographic map refinement is presented which combines both weight plasticity and the formation and elimination of synapses, as well as both activity-dependent and activity-independent processes. The question of whether an activity-dependent process can refine a mapping created by an activity-independent process is addressed statistically. A new method of evaluating the quality of topographic projections is presented which allows independent consideration of the development of the centres and spatial variances of receptive fields for a projection. Synapse formation and elimination embed in the network topology changes in the weight distributions of synapses due to the activity-dependent learning rule used (spike-timing-dependent plasticity). In this model, the spatial variance of receptive fields can be reduced by an activity-dependent mechanism with or without spatially correlated inputs, but the accuracy of receptive field centres will not necessarily improve when synapses are formed based on distributions with on-average perfect topography.
Original language | English |
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Pages (from-to) | 517-527 |
Number of pages | 11 |
Journal | Neural Networks |
Volume | 23 |
Issue number | 4 |
DOIs | |
Publication status | Published - May 2010 |
Keywords / Materials (for Non-textual outputs)
- Synapse formation
- Synapse elimination
- Synaptic rewiring
- Synaptic plasticity
- Spike-timing-dependent plasticity (STDP)
- Activity dependent
- Activity independent
- Integrate-and-fire
- Receptive field
- Topographic map
- Mapping
- Map development
- Ocular dominance
- Topographic refinement