  The paper investigates a new type of truly critical echo state networks where
individual transfer functions for every neuron can be modified to anticipate
the expected next input. Deviations from expected input are only forgotten
slowly in power law fashion. The paper outlines the theory, numerically
analyzes a one neuron model network and finally discusses technical and also
biological implications of this type of approach.
