Rapid neural adaptation to sound level statistics.

Auditory neurons must represent accurately a wide range of sound levels using firing rates that vary over a far narrower range of levels. Recently, we demonstrated that this "dynamic range problem" is lessened by neural adaptation, whereby neurons adjust their input-output functions for sound level according to the prevailing distribution of levels. These adjustments in input-output functions increase the accuracy with which levels around those occurring most commonly are coded by the neural population. Here, we examine how quickly this adaptation occurs. We recorded from single neurons in the auditory midbrain during a stimulus that switched repeatedly between two distributions of sound levels differing in mean level. The high-resolution analysis afforded by this stimulus showed that a prominent component of the adaptation occurs rapidly, with an average time constant across neurons of 160 ms after an increase in mean level, much faster than our previous experiments were able to assess. This time course appears to be independent of both the timescale over which sound levels varied and that over which sound level distributions varied, but is related to neural characteristic frequency. We find that adaptation to an increase in mean level occurs more rapidly than to a decrease. Finally, we observe an additional, slow adaptation in some neurons, which occurs over a timescale of tens of seconds. Our findings provide constraints in the search for mechanisms underlying adaptation to sound level. They also have functional implications for the role of adaptation in the representation of natural sounds.