Interaction of neuronal filters involved in perceptual decisions of grasshoppers

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How can a relatively small nervous system process and discern the fast changes which are characteristic for acoustic signals, and how can it attain a high overall reliability in spite of its unreliable components, the neurons? These questions will be investigated using the acoustic communication of grasshoppers as a model system. In these animals, species-specific communication signals (songs) serve to initiate the meeting of sexual partners and reproduction. The decision of whether or not they should respond to a song signal of a potential partner is particularly important for females, due to their high investment into large eggs.Since the auditory pathway of grasshoppers is relatively simply organized it offers the opportunity to understand how information about these highly relevant sensory signals is extracted and represented in a small nervous system. In accord with optimal coding theory we find that responses of different neurons become increasingly decorrelated and sparse early in the auditory pathway of grasshoppers. This resembles the situation at higher stages of sensory systems of vertebrates. The manageable number of auditory neurons allows us to better understand the neuronal operations that guide such transformations in signal representation. A temporally and population-sparse representation of the communication signals probably allows for a more efficient information read-out by downstream neurons and may facilitate behavioral decisions. We began to investigate the decisions that occur on the top of these processing steps by means of a linear-nonlinear (LN)-model approach. Using only two feature detectors, this LN-model yielded a high predictive power, explaining ~ 90% of the variance in behavioral data of the investigated species. In addition, the model explained several so far enigmatic observations of behavioral as well as of neurophysiological experiments. A main part of the proposal will be to search for the neuronal implementations of the specific predictions derived from the LN-model. Furthermore, we will extend this modeling approach to additional stimulus features, and in particular also to other grasshopper species. Closely related species often differ considerably in their song patterns and the corresponding preferences in the signal receivers. These tests aim at revealing the models universality as well as potential constraints. By analyzing the auditory processing in different species we also expect to obtain insights into evolutionary constraints of song evolution and speciation events.