  The coding mechanism of sensory memory on the neuron scale is one of the most
important questions in neuroscience. We have put forward a quantitative neural
network model, which is self organized, self similar, and self adaptive, just
like an ecosystem following Darwin theory. According to this model, neural
coding is a mult to one mapping from objects to neurons. And the whole cerebrum
is a real-time statistical Turing Machine, with powerful representing and
learning ability. This model can reconcile some important disputations, such
as: temporal coding versus rate based coding, grandmother cell versus
population coding, and decay theory versus interference theory. And it has also
provided explanations for some key questions such as memory consolidation,
episodic memory, consciousness, and sentiment. Philosophical significance is
indicated at last.
