Abstract
Synaptic plasticity that delicately depends on the relative timing of pre- and post-synaptic spikes was recently observed in several brain areas. Here we derive a time-dependent learning rule from the basic principle of mutual information maximization for a leaky integrator neuron with spiking inputs, and study its relation to the experimentally observed rule. The comparison shows that not only is the biological learning rule similar in form to the analytically derived one, but it also increases mutual information to a near-optimal level. The analysis yields insights into the temporal characteristics of the observed learning rule and its dependency on neuronal biophysical parameters.
Original language | English |
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Pages (from-to) | 147-152 |
Number of pages | 6 |
Journal | Neurocomputing |
Volume | 38-40 |
DOIs | |
State | Published - Jun 2001 |
Externally published | Yes |
Keywords
- Information theory
- Learning rules
- Spike timing dependent plasticity
- Synaptic plasticity