Despite their simple auditory systems, some insect species recognize certain temporal aspects of acoustic stimuli with an acuity equal to that of vertebrates; however, the underlying neural mechanisms and coding schemes are only partially understood. In this study, we analyze the response characteristics of the peripheral auditory system of grasshoppers with special emphasis on the representation of species-specific communication signals. We use both natural calling songs and artificial random stimuli designed to focus on two low-order statistical properties of the songs: their typical time scales and the distribution of their modulation amplitudes.Based on stimulus reconstruction techniques and quantified within an information-theoretic framework, our data show that artificial stimuli with typical time scales of Ͼ40 msec can be read from single spike trains with high accuracy. Faster stimulus variations can be reconstructed only for behaviorally relevant amplitude distributions. The highest rates of information transmission (180 bits/sec) and the highest coding efficiencies (40%) are obtained for stimuli that capture both the time scales and amplitude distributions of natural songs.Use of multiple spike trains significantly improves the reconstruction of stimuli that vary on time scales Ͻ40 msec or feature amplitude distributions as occur when several grasshopper songs overlap. Signal-to-noise ratios obtained from the reconstructions of natural songs do not exceed those obtained from artificial stimuli with the same low-order statistical properties. We conclude that auditory receptor neurons are optimized to extract both the time scales and the amplitude distribution of natural songs. They are not optimized, however, to extract higher-order statistical properties of the song-specific rhythmic patterns. Key words: auditory receptor; neural coding; acoustic communication; natural stimuli; stimulus reconstruction; insectEvolutionary processes have shaped acoustic communication behaviors of remarkable complexity (Hauser, 1996;Bradbury and Vehrenkamp, 1998). These behaviors are made possible by sophisticated neural systems in both sender and receiver. In human beings, for example, highly specialized cortical areas process auditory stimuli, extract language information, and generate finetuned motor signals required for proper speech production (Levelt, 1993;Ehret and Romand, 1997).Auditory systems of insects have a much simpler architecture, and with up to a few hundred neurons, they are orders of magnitude smaller than those of most vertebrates. Nevertheless, these systems are capable of astounding computations. Some grasshoppers, for instance, detect gaps in conspecific songs as short as 1-2 msec (von Helversen, 1972), a performance level similar to that reached by birds and mammals.These observations trigger the general question of how a small insect auditory system could possibly be organized to process acoustic signals reliably and with high temporal precision. Important clues will come from understanding the au...

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The temporal resolution of auditory receptors of locusts was investigated by applying noise stimuli with sinusoidal amplitude modulations and by computing temporal modulation transfer functions. These transfer functions showed mostly bandpass characteristics, which are rarely found in other species at the level of receptors. From the upper cut-off frequencies of the modulation transfer functions the minimum integration times were calculated. Minimum integration times showed no significant correlation to the receptor spike rates but depended strongly on the body temperature. At 20 degrees C the average minimum integration time was 1.7 ms, dropping to 0.95 ms at 30 degrees C. The values found in this study correspond well to the range of minimum integration times found in birds and mammals. Gap detection is another standard paradigm to investigate temporal resolution. In locusts and other grasshoppers application of this paradigm yielded values of the minimum detectable gap widths that are approximately twice as large than the minimum integration times reported here.