  We describe a form of memory exhibited by extended excitable systems driven
by stochastic fluctuations. Under such conditions, the system self-organizes
into a state characterized by power-law correlations thus retaining long-term
memory of previous states. The exponents are robust and model-independent. We
discuss novel implications of these results for the functioning of cortical
neurons as well as for networks of neurons.
