Topic: evolutionary strategy

Synaptic plasticity is known to be a key player in the brain’s life-long learning abilities. However, due to experimental limitations, the nature of the local changes at individual synapses and their link with emerging network-level computations remain unclear. In theoretical work, synaptic plasticity is often modelled with unsupervised local plasticity rules. However, deriving a complete set of functional plasticity rules analytically will require divine intuition and numerous assumptions. Here, we approach the problem numerically. We show how to deduce plasticity rules in silico with supervi