Benefits of contrast normalization demonstrated in neurons and model cells

The large dynamic range of natural stimuli poses a challenge for neural coding: how is a neuron to encode large differences at high contrast while remaining sensitive to small differences at low contrast? Many sensory neurons exhibit contrast normalization: gain depends on the range of stimuli presented, such that firing-rate modulation is not proportional to contrast. However, coding depends strongly on the precision of spike timing and the reliability of spike number, neither of which can be predicted from neural gain. The presumption that contrast normalization is associated with maintained coding efficiency remained untested. We report that, as contrast decreases, responses are more variable and encode less information, as expected. Nevertheless, these changes can be small, and information transmission is even better preserved across contrasts than rate modulation. The extent of contrast normalization is correlated with the extent to which information transmission is preserved across contrasts. Specifically, normalization is associated with maintaining the bits of information per spike rather than bits per second. Finally, we show that a nonadapting model can exhibit both contrast normalization and the associated information preservation.