Izhikevich – Solving the distal reward problem

A few years ago Eugene Izhikevich introduced the concept of polychronization, a perspective on neural networks with conduction delays in which temporal input sequences generate signature-like temporal patterns in a neural network. In a follow-up article he proposes a solution for the distal reward problem. Here, a STDP-function is combined with a reward-function (representing Dopamine signaling) to strengthen certain connections of the recent past and thereby facilitating conditioning effects.

All publications come along with Matlab-code to reproduce the figures. I find the concept of polychronization very interesting but wonder whether there are further useful categories in which neural networks with various conduction delays can be characterized.


Izhikevich EM (2006) Polychronization: computation with spikes. Neural computation 18:245–82
Izhikevich EM (2007) Solving the distal reward problem through linkage of STDP and dopamine signaling. Cerebral cortex 17:2443–52