  Reduction of costs in biological signalling seems an evolutionary advantage,
but recent experiments have shown signalling codes shifted to signals of high
cost with a underutilisation of low cost signals. Here I show that errors in
the efficient translation of biological states into signals shift codes to
higher costs, effectively performing a quality control. The statistical
structure of signal usage is predicted to be of a generalised Boltzmann form
that penalises signals that are costly and sensitive to errors. This predicted
distribution of signal usage against signal cost has two main features: an
exponential tail required for cost efficiency and an underutilisation of the
low cost signals required to protect the signalling quality from the errors.
These predictions are shown to correspond quantitatively to the experiments in
which gathering signal statistics is feasible as in visual cortex neurons.
