Conclusion of Long Term Plasticity Lecture

• The way we typically model neural nets is as graphs.
• The nodes are neurons and the synapses arcs.
• However, the nodes and the arcs are actually very sophicticated biological systems.
• Changing the weight of synapse can be done with Hebbian learning and there is good evidence for STDP.
• However, long term plasiticity also is far from well understood.
• The reading for this week is Trappenberg Chapter 4, but particularly Section 4.2.