The post-synaptic potential of a neuron for a long time has been known to be a crosscorrelation between an input axonal frequency pattern and an excititory synaptic strength connection strength pattern. In order for correlations to be useful, they must be able to be compared and must be normalized (covariance of the connection strengths must be constant over all the correlations). A biologically feasible net of neurons was studied (net of N excitatory neurons interacting with an inhibitory neuron) and a very simple Pavlovian rule used for connection strength variation (same rule for both excititory and inhibitory neurons). The surprise was that the neurons of
such a net are able to compare their correlations in a normalized way. Also, the net exhibited greater learning for new input patterns than for old input patterns, thereby explaining the brain’s curiosity drive and reduction of permanent memory plasticity as one ages.