Shannon's Capacity Theorem is the main concept behind the Theory of
Communication. It says that if the amount of information contained in a signal
is smaller than the channel capacity of a physical media of communication, it
can be transmitted with arbitrarily small probability of error. This theorem is
usually applicable to ideal channels of communication in which the information
to be transmitted does not alter the passive characteristics of the channel
that basically tries to reproduce the source of information. For an {\it active
channel}, a network formed by elements that are dynamical systems (such as
neurons, chaotic or periodic oscillators), it is unclear if such theorem is
applicable, once an active channel can adapt to the input of a signal, altering
its capacity. To shed light into this matter, we show, among other results, how
to calculate the information capacity of an active channel of communication.
Then, we show that the {\it channel capacity} depends on whether the active
channel is self-excitable or not and that, contrary to a current belief,
desynchronization can provide an environment in which large amounts of
information can be transmitted in a channel that is self-excitable. An
interesting case of a self-excitable active channel is a network of
electrically connected Hindmarsh-Rose chaotic neurons.Comment: 15 pages, 5 figures. submitted for publication. to appear in Phys.
Rev.