  In the light of recent experimental findings that gap junctions are essential
for low level intensity detection in the sensory periphery, the
Greenberg-Hastings cellular automaton is employed to model the response of a
two-dimensional sensory network to external stimuli. We show that excitable
elements (sensory neurons) that have a small dynamical range are shown to give
rise to a collective large dynamical range. Therefore the network transfer
(gain) function (which is Hill or Stevens law-like) is an emergent property
generated from a pool of small dynamical range cells, providing a basis for a
"neural psychophysics". The growth of the dynamical range with the system size
is approximately logarithmic, suggesting a functional role for electrical
coupling. For a fixed number of neurons, the dynamical range displays a maximum
as a function of the refractory period, which suggests experimental tests for
the model. A biological application to ephaptic interactions in olfactory nerve
fascicles is proposed.
